From fd08f83387e33b2cb1cafcc68d57f7ad4d2c403d Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 12:00:49 -0500 Subject: [PATCH 01/29] Added: - initial updates to notebooks --- Dockerfile | 9 +- README.md | 5 +- docs_src/rl.agents.doubledqn.ipynb | 36 +- docs_src/rl.agents.dqn.ipynb | 853 ++++++++++++++++++++++-- docs_src/rl.agents.dqnfixedtarget.ipynb | 384 ++++++----- environment.yaml | 7 +- fast_rl/agents/dqn.py | 2 +- fast_rl/core/agent_core.py | 24 +- 8 files changed, 1039 insertions(+), 281 deletions(-) diff --git a/Dockerfile b/Dockerfile index 5682902..c77f804 100644 --- a/Dockerfile +++ b/Dockerfile @@ -5,7 +5,7 @@ LABEL com.nvidia.volumes.needed="nvidia_driver" RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential cmake git curl vim ca-certificates python-qt4 libjpeg-dev \ - zip nano unzip libpng-dev strace && \ + zip nano unzip libpng-dev strace python-opengl xvfb && \ rm -rf /var/lib/apt/lists/* ENV LD_LIBRARY_PATH /usr/local/nvidia/lib:/usr/local/nvidia/lib64 @@ -28,10 +28,7 @@ RUN conda env create -f environment.yaml RUN rm -rf /var/lib/apt/lists/* \ && apt-get -y autoremove -COPY /fast_rl /fast-reinforcement-learning/fast_rl -COPY /setup.py /fast-reinforcement-learning/setup.py -COPY /README.md /fast-reinforcement-learning/README.md -WORKDIR /fast-reinforcement-learning -RUN /bin/bash -c "source activate fastrl && pip install -e ." +EXPOSE 8888 +ENV CONDA_DEFAULT_ENV fastrl CMD ["/bin/bash -c"] diff --git a/README.md b/README.md index 3d19f5e..43883eb 100644 --- a/README.md +++ b/README.md @@ -162,4 +162,7 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe |:------:|:-------:|:-----:|:--------------------:| | **RL** | State | st | | | | Action | acn | | -| | Bounds | bb | Same as Bounding Box | \ No newline at end of file +| | Bounds | bb | Same as Bounding Box | + +## Examples + diff --git a/docs_src/rl.agents.doubledqn.ipynb b/docs_src/rl.agents.doubledqn.ipynb index 8a8a16f..7cd5b53 100644 --- a/docs_src/rl.agents.doubledqn.ipynb +++ b/docs_src/rl.agents.doubledqn.ipynb @@ -2,23 +2,33 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Can't import one of these: No module named 'pybullet'\n", + "Can't import one of these: No module named 'gym_maze'\n", + "Can't import one of these: No module named 'gym_minigrid'\n" + ] + } + ], "source": [ - "from fast_rl.core.basic_train import AgentLearner\n", - "from fast_rl.agents.dqn import FixedTargetDQNTrainer\n", - "from fast_rl.core.train import AgentInterpretation, GroupAgentInterpretation\n", - "from fast_rl.core.data_block import MDPDataBunch\n", - "from fast_rl.core.agent_core import ExperienceReplay, GreedyEpsilon\n", - "from fastai.basic_data import DatasetType\n", + "from fast_rl.agents.dqn import create_dqn_model, dqn_learner\n", "from fast_rl.agents.dqn_models import *\n", - "from fast_rl.core.metrics import *\n", - "from fastai.gen_doc.nbdoc import *" + "from fast_rl.agents.dqn import *\n", + "from fast_rl.core.agent_core import ExperienceReplay, PriorityExperienceReplay, GreedyEpsilon\n", + "from fast_rl.core.data_block import MDPDataBunch\n", + "from fast_rl.core.metrics import RewardMetric, EpsilonMetric\n", + "from fastai.gen_doc.nbdoc import show_doc\n", + "from fast_rl.core.train import GroupAgentInterpretation, AgentInterpretation\n", + "from fastai.basic_data import DatasetType" ] }, { @@ -339,12 +349,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 3, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -382,7 +392,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/docs_src/rl.agents.dqn.ipynb b/docs_src/rl.agents.dqn.ipynb index 5a4ed33..04dcc82 100644 --- a/docs_src/rl.agents.dqn.ipynb +++ b/docs_src/rl.agents.dqn.ipynb @@ -2,22 +2,32 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Can't import one of these: No module named 'pybullet'\n", + "Can't import one of these: No module named 'gym_maze'\n", + "Can't import one of these: No module named 'gym_minigrid'\n" + ] + } + ], "source": [ - "from fast_rl.core.basic_train import AgentLearner\n", - "from fast_rl.agents.dqn import create_dqn_model, dqn_learner, DQNLearner\n", + "from fast_rl.agents.dqn import create_dqn_model, dqn_learner\n", "from fast_rl.agents.dqn_models import *\n", - "from fast_rl.core.train import AgentInterpretation, GroupAgentInterpretation\n", + "from fast_rl.agents.dqn import *\n", + "from fast_rl.core.agent_core import ExperienceReplay, PriorityExperienceReplay, GreedyEpsilon\n", "from fast_rl.core.data_block import MDPDataBunch\n", - "from fast_rl.core.agent_core import ExperienceReplay, GreedyEpsilon, PriorityExperienceReplay\n", - "import torch\n", - "from fastai.gen_doc.nbdoc import *\n", + "from fast_rl.core.metrics import RewardMetric, EpsilonMetric\n", + "from fastai.gen_doc.nbdoc import show_doc\n", + "from fast_rl.core.train import GroupAgentInterpretation, AgentInterpretation\n", "from fastai.basic_data import DatasetType" ] }, @@ -38,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": { "pycharm": { "is_executing": false @@ -46,34 +56,96 @@ }, "outputs": [], "source": [ - "data = MDPDataBunch.from_env('CartPole-v1', render='rgb_array', bs=32)" + "data = MDPDataBunch.from_env('CartPole-v1', render='human', bs=64, add_valid=False)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "

__init__[test]

\n", + "\n", + "> __init__(**`ni`**:`int`, **`ao`**:`int`, **`layers`**:`Collection`\\[`int`\\], **`discount`**:`float`=***`0.99`***, **`lr`**=***`0.001`***, **`n_conv_blocks`**:`Collection`\\[`int`\\]=***`0`***, **`nc`**=***`3`***, **`opt`**=***`None`***, **`emb_szs`**:`ListSizes`=***`None`***, **`loss_func`**=***`None`***, **`w`**=***`-1`***, **`h`**=***`-1`***, **`ks`**:`Union`\\[`NoneType`, `list`\\]=***`None`***, **`stride`**:`Union`\\[`NoneType`, `list`\\]=***`None`***, **`grad_clip`**=***`5`***, **`conv_kern_proportion`**=***`0.1`***, **`stride_proportion`**=***`0.1`***, **`pad`**=***`False`***, **`batch_norm`**=***`False`***)\n", + "\n", + "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", + "\n", + "Basic DQN Module. Args:\n", + " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", + " ao: Number of actions to output.\n", + " layers: Number of layers where is determined per element.\n", + " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", + " to the head on top of existing linear layers.\n", + " nc: Number of channels that will be expected by the convolutional blocks. " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "show_doc(DQN.__init__)" + "show_doc(DQNModule.__init__)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "data": { + "text/markdown": [ + "

__init__[test]

\n", + "\n", + "> __init__(**`learn`**:`DQNLearner`, **`max_episodes`**=***`None`***)\n", + "\n", + "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", + "\n", + "Handles basic DQN end of step model optimization. " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/markdown": [ + "

on_loss_begin[test]

\n", + "\n", + "> on_loss_begin(**\\*\\*`kwargs`**:`Any`)\n", + "\n", + "
×

No tests found for on_loss_begin. To contribute a test please refer to this guide and this discussion.

\n", + "\n", + "Performs tree updates, exploration updates, and model optimization. " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "show_doc(BaseDQNCallback.__init__)\n", - "show_doc(BaseDQNCallback.on_loss_begin)" + "show_doc(BaseDQNTrainer.__init__)\n", + "show_doc(BaseDQNTrainer.on_loss_begin)" ] }, { @@ -93,37 +165,79 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], - "source": [ - "model = DQN(data, memory=ExperienceReplay(memory_size=100000, reduce_ram=True),\n", - " lr=0.00025, optimizer=torch.optim.RMSprop)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "pycharm": { - "is_executing": false + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
01.115965#na#81.00000000.93080500:01
11.038706#na#34.00000000.90303200:00
21.015652#na#28.00000000.88085900:00
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" } - }, - "outputs": [], + ], "source": [ - "learn = AgentLearner(data, model)\n", - "learn.fit(450)\n", - "data.close()\n", - "learn.recorder.plot_losses()" + "memory = ExperienceReplay(memory_size=1000000, reduce_ram=True)\n", + "explore = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001)\n", + "model = create_dqn_model(data=data, base_arch=DQNModule, lr=0.001, layers=[32,32], opt=optim.RMSprop)\n", + "learn = dqn_learner(data, model, memory=memory, exploration_method=explore, \n", + " callback_fns=[RewardMetric, EpsilonMetric])\n", + "learn.fit(3)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": { "pycharm": { "is_executing": false @@ -131,18 +245,31 @@ }, "outputs": [], "source": [ - "interp = AgentInterpretation(learn)" + "interp = AgentInterpretation(learn, ds_type=DatasetType.Train)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "group_interp = GroupAgentInterpretation()\n", "group_interp.add_interpretation(interp)\n", "for i in range(5):\n", " data = MDPDataBunch.from_env('CartPole-v1', render='rgb_array', bs=32, add_valid=False)\n", - " model = DQN(data, memory=ExperienceReplay(memory_size=1000000, reduce_ram=True),\n", - " lr=0.001, optimizer=torch.optim.RMSprop)\n", - " learn = AgentLearner(data, model)\n", - " learn.fit(450)\n", + " model = create_dqn_model(data=data, base_arch=DQNModule, lr=0.001, layers=[32,32], opt=optim.RMSprop)\n", + " memory = ExperienceReplay(memory_size=1000000, reduce_ram=True)\n", + " explore = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001)\n", + " learn = dqn_learner(data, model, memory=memory, exploration_method=explore, \n", + " callback_fns=[RewardMetric, EpsilonMetric])\n", + " learn.fit(3)\n", " interp = AgentInterpretation(learn, ds_type=DatasetType.Train)\n", " interp.plot_rewards(cumulative=True, per_episode=True, group_name='er_rms', no_show=True)\n", " group_interp.add_interpretation(interp)\n", @@ -179,15 +574,35 @@ " data.close()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Below are runs produced by `test_dqn.py`" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "per_group_interp = GroupAgentInterpretation()\n", "per_group_interp.add_interpretation(interp)\n", "for i in range(4):\n", " data = MDPDataBunch.from_env('CartPole-v1', render='rgb_array', bs=32)\n", - " model = DQN(data, memory=PriorityExperienceReplay(memory_size=100000, reduce_ram=True))\n", - " learn = AgentLearner(data, model)\n", - " learn.fit(450)\n", + " model = create_dqn_model(data=data, base_arch=DQNModule, lr=0.001, layers=[32,32], opt=optim.RMSprop)\n", + " memory = PriorityExperienceReplay(memory_size=1000000, reduce_ram=True)\n", + " explore = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001)\n", + " learn = dqn_learner(data, model, memory=memory, exploration_method=explore, \n", + " callback_fns=[RewardMetric, EpsilonMetric])\n", + " learn.fit(3)\n", " interp = AgentInterpretation(learn, ds_type=DatasetType.Train)\n", " interp.plot_rewards(cumulative=True, per_episode=True, group_name='per_rms', no_show=True)\n", " per_group_interp.add_interpretation(interp)\n", @@ -239,29 +892,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], "source": [ "per_group_interp = GroupAgentInterpretation.from_pickle('data/cartpole_dqn', 'dqn_PriorityExperienceReplay_FEED_TYPE_STATE')\n", "per_group_interp.add_interpretation(group_interp)\n", "per_group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "CartPole envs might be too simple for PER to be effective. We also tested with lunar lander to see if PER improves performance, and noticed that it actually performs worse than ER. There is a possibility that you could increase the random sampling for PER to see if there is an improvement." - ] - }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "metadata": { "pycharm": { "is_executing": false @@ -270,7 +929,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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Wj7UcN8dAUit8ahcneIRKn/pyAwAgxRf9+CmvCUPVdEgSxbX3aDSdM8V04hQ5vox0WO8M3HlmMQbkpOHSSQMBADe9tQxFd3yEtbtrW7wXhmGYrgILN4ZhACBm0sA9c1e1eHzEDpVG97mLE1QPy+3rdRUAAEWKfvw0RtSEOW5WyNM6XPHo/6ELgf7ZaQCA7DRfzHMvfbOlxXthGIbpKrBwY5hDiLpgxG5062b7vkZ7+4ct+1q8liXSdOGR4yYldtwsnNWjqiagmj3ZFFeOW21QhSwRyNzvVfCQmRItkE/zK/jluGg4tbk1MAzDdDVYuDHMIcR976/GjFmL8OPm+GrMNa0MKYY8ctz2NRh5Zal+I3+tOc3kNM4imm4Kt2ioND1gXKOsJgiJAIKx39KJw/Mz8L+Xjsd1Jw7FBeP7x1zbmQfnFVplGIbpqnSYcCOil4monIhWOvblENEXRLTB/Dfb3E9E9BQRbSSi5UQ0vqPWxTCHMtYc0aU7q+OeW7O7rlXXinhUla7cVQNFIhTmGGFLtZl5oamO8VXWvFLJESrtmWqEPOtDluNmHDs8PwNnje6DaeP6wSdLGDegJ/r0SE34OorMf58yDNN96MhPtFcBnOHadweAL4UQwwB8aT4GgDMBDDO/fgfgfztwXQxzyJKb7gcAVNbFV1zWNEUrSQt6pLR4LS/HLRjWEFAku/DAWbjgpndmANccPzjmWgqRPTRekSU7n805SJ6IcN74/hiWn9niGgHvnDiGYZiuSocJNyHEvwG4E2V+CWCmuT0TwFTH/lnC4HsAPYmoAAzDtCtWLlitR7uPiKYjM0VBYU5aTM5YImzHTcS2A1FkgtxMjltRbhoKc9JQXJCFzBTDVbMcNyKyCxsyUxR7W5asQGnrcRc7MAzDdGUOdAwhXwixGwDMf3ub+/sB2OE4bqe5Lw4i+h0RLSKiRRUVFR26WIbpbqT5DUHW4DHHU9WMqs4Un2Q7YM1hFSc4iwXCqg5ZkmCllXkVEoRVHbnpfvhkyRZVVssPWSKM6JOJE0fk4aQRve3KU5kIbVZuDMMw3YiDJfnD6yPZMzlGCPG8EGKiEGJiXl5eBy+LYboXlvm0pyaEojs+immVEdF0yERI8ckIRfQ4t2zu0lK8uGBzzPEAoDlafoRUHYpEdl5ZxNUO5Ket+7CrJmgXDFjCbVmpURjRM9UHRZJw6aSBGNu/p32cJFFMuDQZinKNPLuD5UOOYRimPTjQn2l7rBCo+W+5uX8ngAGO4/oDSDw9mmGYNmEJqVW7agAA//3haqwsNbbDmm44boqEsKbHjau68Z9L8cBHaxDRdPy8vcputqu6JicoEsFnCrKIy7m78NnvAEQFm/Xvxyt2AwCy02N7sFnjrtpSGHrVMYMAABmpLYd9GYZhugoHWri9D+AKc/sKAHMd+y83q0uPBFBjhVQZhmk/LLHVYA5uB4Aft+4znzOEW0CREVI1eIwZBWD0bbv/g9Uxjy3Cmg5ZjjpuwQQhV8s9c88ldfZ2s64HGOKwtdrNbgPSctSXYRimy9CR7UDeBPAdgBFEtJOIrgbwMIBTiWgDgFPNxwDwMYDNADYCeAHA7ztqXQxzKBP2mGTw7NebABiiTiJCwCehIaShoi5oH1NeG90WIjYEarX8uPi57/Dv9RWQKSrcwgmEm9txs3A337WIaKLVOW6WOHQWTzAMw3R1OiyGIIT4VYKnTvY4VgD4Q0ethWEYA3foEgDK64zebpbj1sOs9Pxu814U5qYDAHZUxc4udQo3SxhZ0xZkiWznLFGRg5JAuMmS99+S9SEVra0rtYUbO24Mw3QjOG+XYQ4hvKo8LQzhBowsyAIANIWjisdphOlC2CFXANB1QHdc1+fovxZWoyFZJ5aYcgs394B5J60NlVqXYseNYZjuBAs3hjmE8AqVWlih0hRzXFWdo9ebs8JUCCDHbOQLGMLImecWUKLCrTaoYsn2qrjXCpqCzt0vzj2e6tJJhQCAIXnpaGVRqT3bVEuUrMcwDNMFYeHGMIcQXqFSwHDMjB5sRlUpANQ7er05R1cJAHkZfvjNcVO6LmJmkvoVye6/Nuu7bZj2zLeoC0bw5o/b7WOsvm0+WcIfTxlm73dXjx49OBe/GJiN8w7vZwuxZLEdN9ZtDMN0I7hOnmEOIdx91Sx0IaCaOW5WfpolrgC34yZQF1SR3yOAVJ8c57j5ZCnOOSurCeLOd1fYj48d1ivmeAv3XNGAT8Z/TB7Smlu0kdhxYximG8LCjWEOISIeQ99liaAJgYgukKJICChGqNTZMiTiED9j7vscADC0dwZkiaDrAs40Mr8jx83CKcjOGtMHEwfmxLy+fVxr46HNYAm3ZtL6GIZhuhwcKmWYQwhnjpsiEY4anIMUnwRdN9w4SSLIkjEvtNFsfrunNojtexvjrhVQjJFVmh7ruGWmKHFFBxEtKgL9LlfN56gkbc+5otFQKSs3hmG6D+y4MUwXYvnOalTUhXDyyPw2ne8MlcoSIT8rBQ2b96G0uhGqWZwAGOKqKaIhGNEw6aEvPa8VUCT4ZIKqC/y4Za+9f1BeOojIFnUAEHRUqLrDqLLjcaJ2IG3BqlDlqlKGYboTLNwYpgtx7tMLAQDrHzgzbspAMjiLDCSJ0CsjAADYWdUETRd2cUDAJyMY0fDwJ2sTXksAUCRjIP2Vry6y9/dKN67pdLqueX2xva24xFlMWLUdB8lbUVedHTeGYboRHCplmC5Ig6NwoDXEOG5EdtiyMaQhout2qDKgGI7burK6hNeqrA/F5bIBQFaqL27fruro5AW/4sp/c1yjHXWboziBhRvDMN0HFm4M0wVpDHs3tgWAkKrhqS83oOiOj6C5qkidI6hkieD3mcItosWESgOKhFBET1iFCgAEigt7Hj0kFxmB5o18t+Pm1FV6O4Y1uTiBYZjuCIdKGaYLUlbbhH7ZqXH7VU3HiP/61H68bk8dSvr2sB+7G/CmmBWkTSEVmi7svLCAIiGkaugpxbtnTtwirMIcn9Uc7uKE3Aw/0vwyMlMUW2y1FxJxjhvDMN0LFm4M04XICCioD6lYvK0KExwtNSzcwmxfQzjmsdNB04Www5b1YdXo42YKJ58soSGsQTNbhAQ9GvcW98mMc9x21wTjjnPjHmslEeGpSw6HLkS7CzcigubRAoVhGKarwqFShulCFPfJBAB8s6HS83l3PldtU2wunLOPmxCGswYYVZ+qw3FTZAmqJqDqAvk9Ujxf65SR+ahtisTsS6abR06a33N/e4s245rtG35lGIbpbFi4MUwXwhIh9a7ihN++8iMe+HB1TNUoANQGY4VVRNPhk63cL2E3222MqFB1ASuKabT50KHqui3u3PgVCRX1saHRlsZSXTppAApz05o9pj2RiDhUyjBMt4KFG8N0ISzHzB0S/XpdBV78ZgtqXA5YMBJbxKBqut1GxOm4NZjNdi3XS5EkqLow8t6IMGlQfFiWAIwb0DNmn3vWqJs+WSkd4qwlQiJuB8IwTPeChRvDdCFUU7BF1KgYqW6M5rFd8vz3Mcc//dVG1Dlct4gm7IIEAWGLOMuZi+a4Gc1zrUrTq48ZhD9PG40LJ/SPuf6kQbkxjxM5bgTg7rNGYljvzKTvdX/YUtmAYEQDEXFVKcMw3QoWbgzThYjoUcetPqRiT20QWx3jqMpqY4sDKuvDuP+D1QAM50nVRYzjJkvG9AMr9OqV4yaRsT8vMwWnj+pjX7sl4+zP08ZgytgCAECvjAAG5qbFDZHvCLbubcCDH6/BM19vNEKlrNwYhulGsHBjmC6Eag57VzUdU/++EJMe+hKlVYZwS5SLVtNkOHLWoPgUh3ADjPYcjZZwczhuqq7HtAix+OMpw3DiiDz4PESYcOST5WUG0D/byGfLSm3/Vh+JeOCjNQCANWV1XJzAMEy3g4Ubw3QhrOIDVRfYWF4PANhrtvxIJIw+X10OXRd2fpzfZ4RKLUHjV4zWHwCixQmS5bjpcdcd1bcHLp000BZu048psp9zd96wmvEO7pXe6nttK2P7GX3r+vYw8ulYuDEM051g4cYwXQhbuDkUUk2jkZ/WnKG1vrwOEbMXm+XMWVfwK1I0VGoVJ8gEAWNUVUstPo4c0gsPTh0NABhZEJvDNqJPJv7f2SMx5bC+Ld5be5FuikVJIhAXJzAM083gBrwM04Wwwp0hNVotarXkaE5fNYRURNKMc60cN8uJys9MwZqyWgDRHDfZodYiSTSwzc9KwTO/Hg9Nj2/UOzD3wLltQHSsVziim+1ADujLMwzDdCjsuDFMF8ISJc5JBlVmVWlDM/NLNR34YPlu44EpZKwIYl5mwBZnznYgFmoz80qd+BUJqf7O/1vQErUhTQdRbN4dwzBMV4eFG8McQP7feytx9lML2ny+1ZfNOSzea+C8O2SpC4H//XoTgOgYLNkxl9TCynFTnI5bFws1Wu9NyHTcOMeNYZjuROf/ecwwhxD/+H4bACN0aeViJYtmFhik+eUYsdbgmqIAGC7amt11jnN1jOqbhfnrK5CflYJR/bLsnm0Bs1gBAGQylJvs6KSbrON2sBC0XUkNWaSgiy2fYRimWVi4MUwn0BYXyHLbMgJKjHBr8nDcyJXxpunAxIHZmL++AicX56GoV4bna1hGm9NxUw8Cx62iLoSsFCVGZCbCctyst5gdN4ZhuhMcKmWYLsKmCqP9R4pLvLhz24bkpeO4Yb1i9hlunQ4CkJMeO+TdOfdUskOl0Y8G99iszuDOf63Aw5+uTepYZ+EGBAs3hmG6FyzcGKYTaGkYuxc3z14GANjrGuze6AqVXjqpEEWuSs6IpiOsCSgyxb22MxRqOXXOqtIThvdu9VrbE6u4YEdVU1LHRzSBVIe4Zd3GMEx3goUbw3QRrJy43IxAzP5dNbFjrnxS/I91WNUR0XTIEsWFUc919FiznlHMHLdUn4wzRvdBZxKMRIVlfSjSzJEGIVVDj1QfAKOAlkdeMQzTnWDhxjDtyNfrynHdGz+3eFxbWlQM723kpZ08Mt4BmzAw2972eYy+imiGcFMkKa7hW2aKzw6fRtuBGP8KdL7oeW7BJnv7rZ92NHtseV0QEU2gZ1pUuHE7EIZhuhMs3BimHfntKz/hw+W7sX1vQ7PHtUVK1AVV9MlKQS9XjhoApPujoUGfKbr+evE4XHl0EQBjKH3UcYvHEmrk7uN2EGieVbtq7e2WCiXu+tdKAEBWill3JQQ34GUYplvBwo1h2hErN2xndfP5WG0xgSzh5eWopTkb35riKyOgoF92KgAjVBpWBRRzDJSb8YWGY2eFFa1Q6UGheRyLcBdmJMIKK1uOG7tuDMN0F7gdCMO0I2k+GXUhFdXmNIOEtEFHhDUdsgT4PXLY0gMyhuSlY1NFQ0xOlyUkm8txA4DzxvfD4Lx0FPfJjDnvYNA7ziX4PUSrFxkpUeGmC+M+2lAPwjAMc9DRKcKNiP4IYDqMz9UVAK4EUADgnwByAPwM4DdCiBZ++zHMwYVPkYAQUNMU3xTXSVtyxyKaMQnAS7ykBxTcfOpw7KpushPzgWgINOQUbh4CRiKyXTfneR2d47azqhFpfiWuRUkiQpHE3XSdbUv6ZKUAiLptB4H+ZBiGaRcOeKiUiPoBuAHARCHEaAAygEsAPALgCSHEMABVAK4+0GtjmP3FSu73mmbgpC1NbSOagCQlEG5+BQFFxqBeGTGtPKxctYgjxy0ZrPM62nG774PV+M85y5M+vjaYuKo0ZDbeHdwrHVcdMwg+mSCE5bixdGMYpnvQWTluCoBUIlIApAHYDeAkAO+Yz88EMLWT1sYwbcbSRXXB5oXbjn2NnuFUXRc4/Yl/Y+7S0rjnwqoORSIosleOm3fulzNUGtZEwuKEROdZckdSg0ivXpfEme2H5ZYNM6tpJQKqGhKb8NbEhLPGFqCgZyoyAoot2li2MQzTXTjgwk0IUQrgMQDbYQi2GgCLAVQLIazfdjsB9DvQa2OY/YVs4dZ8v7Fpz3yL4//yVdz+oKph3Z463GI223WiajpkIvjkeOmVKPfLCnmGNR0RU/gl0/zXLk4wnaoRS+7HUZ9PQUp98+042pNZ323DfR+sQp+sFGQGFJxako+miAZV9w6XWhMT0swChoyAAiEEdJ6ewOoL2DsAACAASURBVDBMN6IzQqXZAH4JYBCAvgDSAZzpcajnJy0R/Y6IFhHRooqKio5bKMO0AWtw+wfLd7d4bK2HKxdRjf/tvbRV2Koq9ShO8Hu4cEBUgG2qaEDYzJFLJklfcYVUM6vXAAB6VvzU8sntxIKNlSitDmLr3gZIEqFHqg8hVU/YUNdy3NIDsvmv6bhBHBRFFgzDMO1BZ4RKTwGwRQhRIYSIAHgXwNEAepqhUwDoD2CX18lCiOeFEBOFEBPz8vIOzIoZJkkipqhITbJthZuYOZvua5s5bpJHnpqXCwdEQ57/t7Yci7dVJZ3j5q4qDQdyAAC9yuYndX57YC11T20IskTITPEhGNGQwHBD2Bzdle4zPkYyUxTopuPGMAzTXegM4bYdwJFElEZGzOZkAKsBfAXgAvOYKwDM7YS1MUyr2VxRb7s9TebAd8Plab1isBLsvWiuuMCrtxsQOyweMBzB5Bw3szjBfFzfoxgAEGgqb/nkJHGGL71CmVZvurAZIs4IKIhoAqEEQ++t70FaiiXcfIZw09lxYxim+9AZOW4/wChC+BlGKxAJwPMAbgdwMxFtBJAL4KUDvTaGaS2V9SGc9Ph83DFnOYQQtnDT9bZVZFrCLaIJXD3zpxjxF9b0uBCmhZxAjbkPJ4pWvjaH+3V02ZiPKquNLZ6bLKpjpMHynTXYXdOEn7bus/elOgouJCkaAm1K4EpGzOulKM4cN+P7wOUJDMN0Fzqlj5sQ4l4A97p2bwZwRCcsh2HajFU9+s3GSkQ0Ac0UWnqSlYy6LmJCn2GH4/blmnJs3duAQb2MqsqIqicUaIkKDtz7JYmSEm6SRMhJ8+Fwq7ebMNalRJof5dUanEUGT3+10d4e068HUnxyTPWrs39dRPN2Jd1THzJSFGi64HApwzDdCh55xTD7gSUudCHsHCvAEBHuUKlX6FRz7XPnuL38zRZ7uzGswe9r/Y/shMKe9nayOW4A8JcLDsOFE/sDAMgs+Ja0IEhvvtVJskQSDBFtNF1L53sjS4SA6aQlOs8Kt1rCLTOgQBOGcOM+bgzDdBdYuDHMfmCJCyGMdh0WXo6bVzWkO7fLneP2j++348THvsa63bVQdRHX9uOXh/XFwNy0ZgXZrycNtLdbI9yAaK4bmY4bCd123/YXNYFzZuF8vyQiBMzK2XVldTEhVft48730mcelm6FSo7KUYRime8CzShlmP7DCdl6Om1uUeU1LcFdIhj2KE7ZUNuC/PzLacQRcbT9OGJGHs8cUeFaaWjjDq0obB3ZajhshOdGm6jqCER0ZgcQfMZGE8Utjf+zMVdhu47tLjObEEwqzY+7bDpWa+6zXNhy3pJbNMAxz0MOOG8PsBx8uM/q1GY6bs0oyvjjBKzfL7cslqiq1QqiWm3TnmcU4raQ3AorcrGgDoqFDoPWOm4XluEHooCT8q5e/2Yqb3loKvZnkskSOm9Uw1zl7VJbIvneLXTVNseeZr2X1tLMGzXOolGGY7gQLN4ZpI1srG+ykel0IW7jJEnm2t1A9crPcusbLcQOiItAKlQ7Jy8BFEwsTTkxw4hRrcoJ+by1h5bUZodKWRdCPZihzT10w4THW+3FSce+Y/UIIvLJwa0wum0wU12T4vg9Wx4g7d3FCpu24dfzMVYZhmAMFCzeGaSNWEr2FFSr1yeTZO8wrVOp2ghI14LW0V6J2IM3hDJXut+MG3fxKjkRTDoCoA5mZEhtO1XSB7zbvjdknS1Kc4wYAr32/LXqeleMmxTpuPKuUYZjuBAs3hmkHdBFtb+GTJWhCxIVBvWZs6gJ44MPVGHb3xwASO24Wsse4q5ZwhlLbLtyijhu1wr5qNlRqPufOg3v40/hh9rLkPR2i0jF0Puq4Ge+RVYUqhHdFL8MwTFeEhRvDtBFnMYJANFTqlyXP8JxXqFQIgRe/2YKIJlBeF0yY42bNNW2Dbouh7cUJVlWpQGtqNN3tTpxYjptbuNWH4tuNSBJ5Toewe9IJgZMrZqE/VcCnGPssg45FG8Mw3QkWbgzjgaYLzPpua7MOmDO/ikCOUKkEPcmq0p+3VcW8ZqLXW1tWByDxhIRk2V/HrbWtQJrr+JHIcfNCJikuxw0AemcaEx38wQqcVfESXvc9aIeTLXdSB7cDYRim+8DCjWEcbK6ox7a9DXhn8Q7cM3cV/vLZ2oR5Wk0O4Zad5rMdNZ9Mnn3cLIdpYG6ave+qmYtinm9uyDyAFitIW6Kt59uOG1o3y8urSMPCer/SkxBuEiGmEMN6DwPmvmCTMdFhoFRu956zBJzwcD8ZhmG6KizcGMbBSY/Px+RHv7ZHWb24YAsO+9Pnnsc6h51H9Ojwc8UMlbrzuyyH7tihuThzdJ+464XVxI6bRZtDnVZxQ1vP1817TbIdiEUi0fvZqjJ8uqoMQOxMUjfDehvjvnQhYooTvrrlBADAl2vLsXBTJfRgfXSt5i06R3vp7dQ0mGEYprNh4cYwHjirN+tDKho98q6sfDSfTNA0gYawcYzlArlz2qLHS+iR6ou7XljT7Vw2JykOp6mt7Twsx6ntjptm/ts+OW5vL96J7fuMgfVZKd6O2/nj++GCCcbILUO4RdfuvI9XFm6FokV7upE5iMzZv45nlTIM011g4cYwHrhzwSrrQ3HHWH3G+vVMRUTXsW2vIUTyzLyriKuK1HLcFElCeW389UIRDeUefc+seaEAoND+/cjuqGpq+SAPbOEGPW7cgy+0DxnVazzPa66q1CIjgXAb068HskyBKwQ8c9wAIIAwAo1GI+SQ8MF6i5zfw2TWwTAM0xVg4cYwHriFW4OH42Z1/k/xyVA1gT9/shaAke8GxA9DLzVFk0+WbHfOSVjVUVEXK+h+M2kgjijKtR/vZ20C+mSltOk8uzgBACF27ZPnHokjP/+l5/D55qpKAeN9Hp6ficKcNJw4Ii/muex0P1LMMVe6gGcfNwCY478Pxy27DQAQgi9anOB4s7wKQxiGYboiLNwYxgO3PrruzaX454/bY/ZFHMLN2cLCcoYirkKDO95dAcAIraZ55HWFVD2mqW9JQRYmj8hDql+2heT+CrfJw/NaPsgDpygjj350ACCp8W5egkNt/IqENL+C+bedgMuOHBjzXFaKLxr29GgH8viFhwEARktb7X0RyHb/thjHjasTGIbpJrBwYxgP3LlgmyrqbeFVURdCQ0i1HbVMV1Wk1QDW7bhZ6AI4f3x/jCrIitkfVvWYPm5WyBWIisG26rYjinKQlxnwFIzJIOkRe9vLWQOi4VQnLTluTWENikQgorjq0h6pPju87Ffi24EU9Ih3DwOSgJXa5sxx05ov1mUYhukytFyHzzCHIGU13jM2Z323FffMXYWRBZmYdng/APEjm6wkeq+h8oCRb5Xik/HHU4djRWkNnvxyAwCguimMUETD6H5ZGJqXgYkDc+xzFJmAiOflkuJ3xw9GWNUThhtbwinWJEfYtGfFT/a2rDVCRc+YSlItgXh1YjljblHZM81nC9mAIsVNTvAqtFAkMhLiiGIcN5WrShmG6Saw48YwHjwxb4Pn/nvmrgIArNldF3XcUqIVoscP62U3fnXnVQ3OSwcAFPWK9nFzao9b316OHVVN8MsSzhnbF30cjlJ2mh/A/lVHJjOQPhEU47hFtwvXz7S3ZdUQu87RXl5jvtxYOWmpvljhlpmioH92KgCgKDcNlEycmACr6lUmDpUyDNP9YOHGMG3EapabkRIVHL2zArbT43bceqb6MCQv3RZhgPckA69E+utPGopTRvbGgJy0uOc6ivnrK7Cn1hBjzlBpWv1We1uTo+FcSTWqap2OmyVudV3gs1Vlng2GrffA3c/Nr8g4eWQ+3pg+CTedMhyo3IhMNMYcQ14D7013TXHMB0vG+WMYhukKJCXciGgIEQXM7ROI6AYi6tmxS2OYA8uqXTVJH0swctIIQIoSFRyKJNlOjzvHLazqUCQpxjmSPFyk5Tvj15Gd5sclvyj07P/WEWi6wD++34YHPjLafJCIIBToBQBIq9uKd3/eicXbquDMulPM4gSnyWaJ10XbqvD24p147fvYAg8A9vvhFrFWP7yjh/ZCTkYAeHoC3vb/CYU5hgvnkyXkoyrmHF1Er+Hsece6jWGY7kKyOW5zAEwkoqEAXgLwPoA3AJzVUQtjmAPNtL9/m/SxAoYQkyWyqxgBY7C5JUD21AYRUjU0hDTkpPsR1vQYF8g4Pl647WfhaOvQNVS/+0cs7HUBzj7heHu35YxZY70kPQJdMkQjaWF8vNKYenD58Kgish034XTcDOFmieKapnDM0PdTRva2t3tnpqAoNw1bzX54Xn3biqUdePXKIwAAh9d8iQlSbEhbgGzHzRkqTTTBoTUsXry4t6IoLwIYDY5WMAzTMegAVqqqOn3ChAnlXgckK9x0IYRKRNMA/FUI8TciWtJuy2SYg4D46aLNUxdSDeHmc7g8kmTnrd08exk+Wr4bX64tx6MXjEVY1RFIiQ0HejluB1K5ZVavxin6pxhatgGViAo3a/SWtTzSVQjJ+LhQHeHOcEq0x1zhxlnY13eyZ6h04aa95vViB2ZdM3mIvS1LhE9uPB4j7/kUo/tmxRYfaNGCiMF5xhgs6d2r8fdo1BkAkKLAHhPhFMVaErl2LaEoyot9+vQZmZeXVyVJEnt4DMO0O7quU0VFRUlZWdmLAM71OiZZ4RYhol8BuALAFHPfgYnZMMx+sqc2iGBEw8Dc9GaPSw8oqG5MvnSzpjECWaIYZ0iRYgXDl2uNP5je+mmHGSqNVWWyh3A7rP8BzEIIGzM+Q64f56Ap3IQAapoiIF2F5jOKJWpDjhmt/mx7u1fZAsjhOmh6VE1FND3GYQOAlNot6IF6nDRuOMYXZsc8l+qX8cH1x6BnQALCDYDf/J6p3lW+bgwhbLyeIrWv4wZgNIs2hmE6EkmSRF5eXk1ZWdnohMckea0rARwF4EEhxBYiGgTgtfZYJMN0NJMe+hKTH/06TkC4cRYNWNWMzVHTZAi3FEc1pESSZ/izIWz0fXM/J3n8BE4d17fF124vVHM4e4OI7Ym2pbLB3n7w4zWQ9AiEGSqtajLcL5kIcPV0U9SG2FCprsc8JgDHf3YGPg7cCUUmz5YeY/r1xIBv/wt4qK/RgO2vY4Fvnkj+pszXc167HQw345Is2hiG6WDMz5mE+iwp4SaEWC2EuEEI8ab5eIsQ4uF2WiPDHBDCCfqqWRw5OBr2u/LoIozt1wMAkJvu9zz+hy374JMI6f6oca1I5NkrTdWEmePmEm4ux+3oIbnISfB6HQGFDYHWiFjh9tZPO+ztfQ1hkFChkxkqNbvZ6kIAWjjmvJw938aGSlUB1VkZYN5vP9oLqbm5qz+bbUbKVwHV24AFj0Wfa0aAG4FYR96d+fa2k+PGMAzT6TQbKiWiFUDixB8hxNh2XxHDdBJEQIpPwvUnDkW/7FS7PUXAl1hg1IXUmDYWikwoTNCyI6zqMd38gfgmsueOLUCa/8D1xZYihnBrECkx0m3SoBw7zAsAeiSMXeE09ABAuiHcBABdjRVuw5c+hB8mn2E/jmh6jHBz3q2X22ijpBjh0abq+Od0FZATZGoIPUbYSUTQhWhxgkNbeGfRjp4V9eF2+2blZfjVCyYO8LhhhmGYKC05bufAyGn71Py61Pz6GMA7Hbs0htl/nH3DWvrdresCfkXCwNx0KJJkC45AM41r/Upse49UnxwTOnW+dkTT40Kl7kBhUk1m2xHZrARtRCBmv1tQSkLF4lpzRJcefU+/WbfbdUXhKk7QY5vwOr4JXvl9NoopI5v2xj+nhWPWEIOu21Wlzvtoj+IENxX1YaVvz5RIe30lIwJlWZ5QXFxcYn3dddddfdr9xhy8/vrrPTr6NSyeeuqp3Ozs7MOKi4tLBg0aNOpPf/pT75bP8mbdunX+YcOGjWqvtX344YeZmZmZ46z3/eijjx4OADfffHPf3r17j3V+TyorK2X38cXFxSXvvfdeJhD9Hg4dOnTUiBEjSu677758LcFMtjlz5mRZ56elpR1eVFQ0uri4uGTy5MlD+/XrN2b79u32/zOXXXZZ4V133dXHeu2RI0eWDB48eNQtt9xS4HUPzjV5cfvtt/cZOnToqOHDh5cUFxeX/N///V/6qaeeOqS4uLiksLBwtPNaX3zxRToA7Nq1S1EUZfyjjz7ay7rO2LFji4uLi0sKCgrGWN/f4uLiknXr1vn79es3xrp+cXFxyW9/+9sB7nU43+OBAweOPu2004YsXrzY/jszGAzSVVddNWDAgAGjCwsLR5944olDN2zYYIctiGjCjBkz+luP77nnnvybb775wOWjdADNflAIIbYBABEdI4Q4xvHUHUS0EMD9Hbk4hgGMeZaPf74O15wwBL0yAi2f4KDGVWywZHsVxvTrYc8TdaLpAhKRLaYs0VeUm44tlY1xxwOIC32m+rx/pIiMxrqyJIG0MDKr16A297BW3UtHIEeiwk0IYQtHPSa0KOAjDUH4zUfRXzIKNIQpAL8IGddTg/jFhicQwEkIwY+Ipsf0s/NT9PvhlQtoEzSNp8aq+Ocaq4D03Pj9xsrhDBJYErqFKHmXIRAI6GvXrl19IF4rEong0ksvrQGQfIPD/WTKlClVs2bN2l5WViaPHDly9KWXXlo1dOjQ/Rj21n5MnDix/quvvtro3n/NNdfsuf/++/cke7zze1haWqpceOGFg2tqauQnnnhil/vY888/v/b8889fDQBHHHHEiMcee2zH8ccf3wgAf/nLX/Kuv/76AXPnzt3yzTffpP34448ZL7300povvvgiw3rt2tpaacyYMSVTp06taW5NbubNm5f+2Wef9VyxYsXq1NRUsXv3biUUCtEXX3yxCTBE4OOPP57vvtasWbOyDzvssIa3334797bbbqsEgOXLl68FDGG+aNGi9FmzZsU0c5w/f/76goIC7wHIJs73+IUXXsg+/fTTRyxfvnxV37591RtuuKFffX29tGXLlpWKouDJJ5/MPffcc4euXLlytSzL8Pv94uOPP87evXt3WUuv01VItjghnYiOtR4Q0dEAmi/RY5h24rl/b8KL32zBMy1/3sRR3RT9zF++sxrTnvkWD3+y1vNYTQgjJ8rUE5UNRhhwcK90nD++H0b0if/j1O0aJQqrWsPSFYkwdMVjOOLLC5G5d7ltQKX7Zdx5ZjF6ph24/DYAUNQ6AMBp0mKs2V2LprCxTqdr5jOFmiXcyOFe+aBClRzTE0QE43bMwrqU3wIw2oE4HbeH9t0cPTaRcFNDjm2PatJQbVxunY0QsaFS8zW688irvXv3ykVFRaOXLVsWAIApU6YMevzxx3sBQFpa2uEzZszoX1JSMvKoo44avmvXLgUAVq1aFTjuuOOGjRo1auSECRNGLFmyJAUAzj///KLp06f3nzRp0vDf//73/Z966qncyy+/vBAw3JTTTz99yOjRo0eOHj165Oeff54OGI7IhRdeWHTEEUeM6N+//5gHHnjAdsqefvrp3OHDh5eMGDGiZOrUqYOau46TPn36aIWFhaEdO3b4WnrtqVOnDjryyCOHDxw4cLR1307WrVvnnzBhwoiSkpKRJSUlIy13aOrUqYNee+01u4T73HPPHfT666/3aJ/vSnL069dPffHFF7e+8sorvfVWusK33HJLxbZt2wIffPBB5vXXX1/45JNPbg8EAjH/o2dlZeljxoxpXLduXav+4i0tLfXl5OSoqampAgAKCgrUoqKiFgX022+/nfPYY4/tKCsr823ZsqVDOk/MmDGj6rjjjqt56aWXcurq6qTZs2f3evbZZ3coivFH84033rg3LS1Nmzt3bhYAyLIsLr/88oqHHnoovyPW0xkkK9yuAvB3ItpKRFsAPGPuY5gOx2rRURdq/R9Lpz3xb3t7xz6js/+nq8rw/eb4EJyuC5D5HwBMGVsAWSL0z07FmaMLcPMpw+POcYsPK4VtVN8se9+I/Aw0moJIlgiZVcY0gh57l9giMS2gYFRaDfLLvmr1PbaFiKbj6a82ItxgOFvDpFL8dd463DR7KYBYoaPAeN+bhPHZL0TUcfORBp3iQ8MWYZfjNkJssbcTOm5lK6PbXsJNixhfXohYx80q/uiIHLfOIBQKSc5Q1wsvvJCdm5urPfHEE9uvuOKKQc8//3x2dXW1csstt1QCQFNTkzR+/PjG1atXrznmmGPq7rjjjr4AMH369IHPPPPM9lWrVq159NFHd1577bWF1mts2rQpZeHChetfeOGFnc7X/o//+I8BN998856VK1eu+de//rXpmmuuKbKe27hxY8r8+fPX//TTT2see+yxvqFQiBYtWpTy2GOPFcyfP3/9unXrVj/33HPbW7qOxYYNG/yhUEiaNGlSU0vnrFmzJnXevHkbvv/++7WPPvpo361bt8YIhr59+6oLFixYv3r16jVvvfXW5j/+8Y+FADBjxoyKV199NRcwxO/ixYszLrroooTu4qJFizKs9/3222+3w8fPPvtsvrV/0qRJw72OLy4uLlm1apWneCopKQnruo7S0tJW5UvKsoxnnnlm22WXXTZk8ODBwTPPPLPefUxZWZm8ZMmS9HHjxjW1Zk1Tp06t3bVrl7+oqGj0ZZddVvjRRx9ltLSejRs3+iorK30nnnhi47nnnls1c+bMnGTuY/LkycOt9SQbHj/88MMb165dm7J69epAQUFBOCcnJ0b1jhs3rnHlypV2OPW2224rf/fdd3P27t2b+MOqC9Hi/yhEJAEYKoQ4jIiyAJAQ4oBZ5wzjk608pf375Rs0Q587q5pwyfPfY/0DZ8YMXteE8YveMtEmDcrF+MJsOxwqS4Rp4/qiLqRi3hojcd9y3KYfOwjz1u6B35yi8PsThuAPbxg9qlP9sj2BQJEIQjKOIaEjPzOAM0blY1BuOiZ9fip8kTp8NW0JNF/HGtpbKhuwdEc1Sn2VmGh+lPWjCuzQ81HVEIqZl+ozhVvQ6vXmctxqVB+8PtV7pCpmcYK3kyAnipS+eFJ0O9IU/7wWjnXlnLgcN0scdpdZpYlCpdOmTaudPXt29n/+538OXLx48SprvyRJmD59+j4AuOqqq/aed955Q2tqaqQlS5ZkXHjhhXb343A4bH83zjvvvCrLvXCycOHCrA0bNth9curr6+WqqioJAE477bTq1NRUkZqaqubk5ER27typfPbZZ1lTpkypssJT+fn5WkvX+eCDD7KHDh2auXXr1pTHH398a1pammjpnDPPPLM6IyNDZGRkqEcddVTtggUL0o844gg7tyEcDtPVV189cPXq1amSJGHbtm0BADj77LPrb7rppoGlpaXK66+/nn322WdX+XyJTaL2CpV60VKrokQcffTRTcOGDWu67rrrYjrsL1q0KGPkyJElkiSJG2+8sWzixInBDz/80Jfsmnr06KGvXLly9aeffpr55ZdfZl5xxRVD7rnnnp033HCDR9KpwcyZM3POPffcKgD4zW9+s+/qq68uuu++++LeFzfJhErdWO+Xrusgorg3z/1+5uTk6BdeeOHehx9+uHdqamqXT5xoUbgJIXQiug7AbCFE7QFYE8PEIJvlh4kEQLJYYUCLxrAKvxINTeq6gDtf3t3a4+yxfRFW9ahwM4XBkYNzcURRju3AOcdgpSiy/doSAbl7jNFaJFQQES6YYOTj+n40wpa+0L4OF27WbaYh6mhlwhBJP26twrebop/PVqg0bAo3cjpuUNGg+7CjcAoG7PzA3l8hsjCsdzp2VseKQCcpWpxBADS5ctoiHo6bHmkmVBr7PbYqV7tzqBQANE3D+vXrUwKBgF5ZWakMGTLE05IkImiahszMTDVRrlxGRobnD5oQAosWLVqTkZER92Y6Q3SyLENVVTJzJj1/qSa6jpXjNm/evPTzzz9/2LRp02oKCwvV5s5xF/S4Hz/44IP5vXv3jsyZM2eLrutITU2dYD130UUX7X3xxRdz5syZk/Pyyy9v9brvjmb16tV+WZbRr1+/NuVfSZIEWY41klojGhOhKArOOeecunPOOadu7NixTf/4xz9ymxNuc+bMyamsrPS9++67OQBQXl7uW7FiRWDMmDEJ/spqO0uXLk2bMGFC46hRo0K7du0KVFVVSdnZ2fb/t8uXL0+7+OKLYz5M7rzzzj3jx48vueSSSyrbez0HmmRDpV8Q0a1ENICIcqyvtr4oEfUkoneIaC0RrSGio8xrfkFEG8x/s1u+EnMoYDlu7qHtLaG7BIM1MN3C/QGveQg3L5wu3akl0bSJRDlbAZ9sB+/6q9G8XElrxjVqhmBEQ01T++RrZziEm2IKtNLqWJfLctwiUCAgxVRt+qBBhYL3/GchFIgWDKQijNx0BcGIZs8rBYA1erRorEfD1vgF1eyMfax6OW5qM6FS4Vm52hGh0rwMv7qrOuhrr6+8DH+bE6fvv//+/OHDhwdnzpy5+eqrry4KhUIEGI7EK6+8kg0Ar776au4RRxxRl5OTo/fv3z/88ssvZ1vHfPfddy12nD722GNrH3nkETuU9e233zZ7zhlnnFH7/vvv55SVlckAsGfPHjnZ65xyyikN55133t5HHnkkv6VzPvnkk56NjY1UVlYmf//995nHHntsg/NaNTU1ckFBQcQMLeY6Kzivueaayueeey4fACZOnJjceI52ZNeuXcqMGTMGXnnlleVSs/1xDizLli0LrFixwg6jLlmyJLV///4J/loyjm9sbJTLy8uXl5aWrigtLV1x3XXXlc2aNavNOiERr776as8FCxb0uOqqq/ZlZWXpF1xwQeW11147QFWNH5+nn346NxAI6KeeemrMX4b5+fnalClTqt544424PMiuRrIxdSuf7Q+OfQLA4Da+7pMAPhVCXEBEfgBpAO4C8KUQ4mEiugPAHQBub+P1mW5IpJWOWyKnx8It0oziBGrVqNAJA1v++6I39uFX8pd4UzsZt226wt4vqw3eJ4jm7/PeBvwYGAAAIABJREFU91dhb0MYL/xmAmQtiKM/PhVrJv439vY90fsEXcPAdS9hx7DLoCtpGLvw95i8+xs8gpeRRtHfVZZAq3flEipk/KJTIUOQBBIaUhQJQVWHDyrCkDF7SypmpEQ/TjIoiCwphOqmCJ7792Z7fwOiv6Ml2ePjp64s9rGncAsndtxgNgV+dChwyp8gSYaw7ohQaWf0XLNy3KzHJ510Us0111xT+Y9//KPX4sWL12RnZ+vvvPNO3R133FHwxBNP7EpNTdVXrVqVOmrUqD6ZmZnau+++uxkA3nzzzc0zZswY+MgjjxSoqkrTpk3bd9RRR3m82VGef/75HdOnTy8cPnx4iaZpNGnSpLqjjz56e6LjJ06cGLzlllt2H3fcccWSJInRo0c3zpkzZ2uy17n33nvLJk6cWPLAAw/sbu6cww8/vOHkk08etmvXLv+tt966u6ioKLJu3TrbSr/pppvKzz///CHvvfde9rHHHlvnDJUNGDBAHTJkSHDKlClt/l4+++yz+bNnz7b/apk7d+5GIJpPZu2//fbbd1955ZVV1vdQVVWSZVlcfPHFe++9994WQ4rtQaI1uY+rra2Vb7jhhsLa2lpZlmVRVFQUmjlz5rZE1505c2buWWedFXOdSy65pOrXv/714EcffdTdMyiGyZMnD7dE68iRIxv/9a9/bXUfY73HTU1N0vDhw5s+++yzdX379lUB4G9/+1vptdde23/w4MGjg8GglJOToy5atGiNlxC+++67y2bOnJnX3Hq6AtTW2HqbX9DIk1sGYLBwvDgRrQNwghBiNxEVAPhaCDGiuWtNnDhRLFq0qGMXzHQ6D3+yFs/O34Tjh/XCrKsnJX1eU1jDyHs+Tfj88vtOQ1ZKNKfl6ld/wprdtbhnSgmUFv76nT7L+P/u6V8d7tm3DQDeXrQDpdVNeDx4D0Y0/owTQo/j68At9vM7hvwK6yb8yX58ymwjr3nh6Z+gqYeRfjRvzR6MyM/EAEdTX+u1/3rxOPRp2oAjP/8lmtL6YuE5X3uuo/eOTzD2uxuxu/AcrDryf+zXKQq+gXn+WzFUMroQ/Cp8N77TR2FQbhq27I22PxlEu/FV4BbcEP4Dnkh5AZ/7TsZdkavw91+Phz7zXAQogtuUu/BJyt1IbSy1z3t04PP4+7po9ltGQMFr4g6Mkwwh99a4Wbh46i9jF7v6fWD2b6KPx1wArHC1jPzVP4GMfOCFBEL1Dz8Cfz8CUFJxQuBNCCHwxEXjML4o+T/+iWixEGKic9+yZcu2HnbYYV0qzJKWlnZ4Y2Pjks5eR0dx8803983IyNC8csySoa6uTiopKSlZunTpmtzc3ATNAZmuwvbt25XTTjtt+PTp08tvvfXWLvWz6mbZsmW9DjvssCKv55KuYiGi0QBKgGiDdSHErDasZzCACgCvENFhABYDuBFAvhBit3nd3UTU5uaLTPfCap7aeset+ePdxpZu9jFLxnMb3TcLK3fVNps7deHEAdB1Ad/Hxu+DD/13xzyvRKJOfsGWd+1tK4dMCIF/mqOnXrw8RkPYz5PdiLYZoWmOlkqrizdHvBy32mCs42btVyGboVINskTwKRJ00qAKBQJAxJ+JVEe7u3S1CnCULaQHZPiD0d+Nw3q5Pn6EAL7+s7F9zE3Awr/GizbArCqNOm61IhVZ5DCLwuYiiOBXJEhEyEzpkM4ETBfmvffey7z22muLrr322j0s2roHhYWFCXM3uxNJCTciuhfACTCE28cAzgTwDYC2CDcFwHgA1wshfiCiJ2GERZOCiH4H4HcAUFhY2MLRzMHGjFmL8MXqPdj68NlJn2PltrW2qlRtITwmXNPcNGGET5MJld5w8jA0htUWx1NJEqHJnwM0GuHDmOccOW6F61+xty3h1lJOX0TVIenGNUQzyXmqkmG+XnwkLN2V49Y7MxCTP3ftCUPw7/lbjetABkgCCWMChF+WoEFFPVIhQIj4c+zjFGiQ9Ng8tPSAAsUhCrMDrjXX7wHKzc9cn0f6VM5gYN9mY+RVTKjUdR1z/iqIjAkYHTA1oavQnd02APif//mfuKa1yTJ16tS6qVOnrnDumzNnTtbdd9/d37lvwIABIavxbEfSGa9dVlYmn3DCCXGRra+//npdnz59WMwepCTruF0A4DAAS4QQVxJRPoAX2/iaOwHsFEL8YD5+B4Zw20NEBY5QabnXyUKI5wE8Dxih0jaugekkvlhtRDRqmiLokZqcC2IJtpZy1ty0dLxb2Onm5IRklJtEhIxAki6OP7ZZRnnBicip+BGy5hBNjnw30g1x8+aPCdOHAABNqg4lYomU5kK7xn3KWhBypD5mv1O4+aAiJ92P8rqooLz11OH4bv5nAIAwFAgikNAgywSfQpCgmkULQCRg9DKtEenIpVqky7HOXbpfgQINESHDRxr81Iygkj3aS8lm2pLLcfOn9wAaGyHS80ANFUC43n5PZIkQ4V8/TJI4JxUcCq/dp08f7VBwqLobyZaxNAkhdACqmaNWjjYWJgghygDsICJL5Z8MYDWA9wFYmdtXAJjbluszXQN3xWdzWI5Jqx23FpyWsGs+oFVV2t7TQjN7xBYw6EoqdDkASfUeo2U5bgs2RlM0vHJRt+1tgBIxWoiIZn6UyXS+SGgo+ekue38AESgO8ZQqqXH5erIs2Q14VSjQIRuOGxEkEHzQDOEmgEjAuE8JxjVz/LHvb5pfhg8aQmZbEZ/UzPfHy3GTrD5yEeC18+3dKX4/cPEboGGnGzss4QaCLFG3bwXCMMyhRbKO2yIi6gngBRg5afUAftyP170ewOtmRelmAFfCEJGziehqANsBXLgf12e6EVbIsNWOW0uhRs0dKhUgdMSg99jrCUmBIBmS8LaCyGO/JgQUc13pARkNIQ0VdSGkpBgFW5qSFneOheQQbqkNO+z9zh5uAJBCqt16BQBuO90oYrjmuELgRyAiFLOqVDedLB1pUKFCRrZfR9hvOG4pMNywUwbKxp9kJv2kfRggVdiPfXAJN2eLD9nDzbT2/eg2+4XRsM3qyTfnauNfIigSYT/7NjMMwxxUJCXchBC/NzefJaJPAWQJIZa39UWFEEsBxGdbG+4bcwjQmkIDy2lrjUsHtCz03GuwQ6XNMHDN86jLHoV9fY5Jeh3kyvXSyWe31fA8XsS383KaRn5ZQgM0NIRVpOhGFadoJlQaFW46nCKyJxlh1lXySIzS1uBU+hHb5Wn28yUFxtjGU4ZnG8INMnSzj5ssEQbkpKEWKsJQ0C9NRcRvOG4BGK8XEGFsfugs/LB5L/Y2hrFnyScx6/K5e7PqjvuWPISb9SbsXuK93/0eSApkidrclZ5hGOZgJNnihFkAFgBYIITwntDNMK3gL5+tw2MXHpbUsZbAaq3jprUQKnU7ci024BUCw1Y8BgCYd9H6pNch6bE9xwQZzhWEDggdI36+H6kNOx3HG4JuVN8srNplDCvRdQGYUUxdCNytvIbztv8APd94DwPBckPAeNyALQSFFlPE0BtG66pl6UdhVO0anCz9jFmOSRH2LFEt2oBXgwTJFG490/zokSXh+1oFILJz3JaLwRhHmwAtBEkiHDXU6Hf5Q0UOsAWoFWnIosZ4gbrsn9Ft2QcMPQXYOC+6L9DCuES3cMvI71jHbenrPVFf3qr5ks2S0VvFuEsPeG84hmG6FsnmuL0KoADA34hoExHNIaIbO25ZTHfn/7P35fFVVOf7z5mZu2QPCUnY1wBJWAWEFrEqYn9YFamodQW1iqh8cRcXrK1VqlXrWpeWqoW6FwXFFasgrixVCWtYDJIFErLnrrOc3x9n9pl7c8OiQuf5fJR7Z87MnJk7N/Pc533f591YnXq7W01x66z7fUdEL25T3ERFSdz4HIAv7vCpTAn26kpFDZUSKiG9bRd673zRsl5T4nrksDwvgSOWc4+KCq4Q3kG+0oD09u/UubW4Vo2CUhRUf6TuV4H5K19EGtl8MvV+2ZZQqaATN0Y8JfCQwYNAhk/1uSNSFCJ8UCiB7MvEX3Juw83SVZbtNIzvxZyEnpKmsm1jtntg1X3Ga44HutqK3bJ7OM8PMHxd7MStbjPuqbsGVJFxWLhbe52AnF7iIfsvBRLI8/yYkpKSskGDBg099dRTB7S1tbn+DT/hhBOK9+/f36mG2to2+/fv5++7774OTUqXL1+elZWVNcrctHzp0qVZnTlmZ3Hdddf1ONzH0DB9+vR+PXv2HF5SUlI2ZMiQsmXLlh3wcR977LH8GTNmHDIbhBtuuKFHYWHhCO26X3311T0BYNy4cUP69es3TFs+ZcqUAW7jS0pKyvbv389rn2FpaWlZv379ho0dO3bISy+9lJPouPPmzeumba/diyUlJWX33HNP4ahRo0oU9ceyJEkoKSkpW7FiRYb52IMGDRr6wgsv5CSbk9tx29rauKlTp/YfPHhw2aBBg4aOGTNmSEVFhV/brmvXriPN+4pGowQAFi1alEsIGfP1118HAWDNmjVp2picnJxR2uc7YcKEwdu2bfMHg8HR5vk88cQT+fa5aNd48ODBZf379x86Y8aMPuZ579y503fyyScP7Nu377BevXoNnzFjRp9IJEIA9p0hhIx58cUX9Wt80kknFS9fvrxT91ZKxI1S+hGAewHcCVZNOhbAVZ05kAcPZnQUkjQjJh1gcYKqqJ00xP0ZFJcUx/tkxrv9Nz/VqeNrsIdKQVRbDcUautRXq8RNI2uSQvVz2V7Xpl8PAOC1qlJKVWJmRUHNhyiqelffr/kK5qih0r5dgvhYHolvlAGW3qw+RSWC6vxF8GgQBUQlgOcNUifBB028/DheirQ0tbBAsnU3UG062tTuCenv35i4vRchjr6jFjUxzVTwoV1fl3Bxf3EH8uSGoyZcqjWZ3759+yafz0cfeughy82tKApkWcaqVat2dO3aNaV6Wvs2DQ0N/D/+8Y+UfDTHjh3bvnXr1s3af9OmTWs7kPNKBZIk4ZFHHqk5nMew45577qnaunXr5gcffHDP3Llz+/5Qx00Fs2fP3qdd9yeffFJ3vl60aNEubfl77723y2381q1bN2v3x9ixY9u3bNmyubKycuNjjz32/U033dQnEUm9//7792rba/fi1q1bN8+fP7+uV69e8UceeaQrACxYsKBw1KhRoVNOOSVkPvYrr7yyc86cOf20tmOJ5mTHggULCgsLC8WKiorN27dv3/Tss89W9u7dW9S2mzFjRr15X8FgkALAyy+/nDd69Oj2xYsX5wHAuHHjItqYyZMnN2uf7+eff14BMPsV83zmzJnj2pt10aJFuyoqKjZv2bJlcyAQUE499dRigH2Xpk2bVjx16tTm3bt3b6ysrCyPRqPk6quv1m1eioqKxPvvv797yh+0C1IiboSQ/wD4DMBvAGwDcCyltORgDuzhfxudacvXrnp/yTLtVJ6bpqhlBtyFjG+rrFGpmKRA4BMTyj7b/5nysc3gFAmhYDfI6teNEk5V3GTd+sMMLYRILSob+3t2/3vbLGM1GxECxUGCYqKMUINhc+UT25DdbFQLZIFVtRZlBdA7N4A+gRD6xrajmFRhBNmJY18cxjoZmEKlMYVZeujCpBSDSAQ9HBkSCdK1ylR7WyqVuLVTU8VoNEFkkAjWnDeAEV4N5mb02nmbiaspR65I2Xd4FLcfGRMnTmzfsWNHYNu2bf4BAwYMveiii/oMHTq0bOfOnf6ePXsOr62tFQDg97//fdGgQYOGDho0aOjdd99dCADJtrnxxht77dmzJ1BSUlJ25ZVX9po2bVr/f/3rX7nacadOndpfU03csGrVqvTBgweXhcNh0trayhUXFw9du3ZtcPny5Vljx44dcsoppwwcOHDg0AsuuKCP9gB//fXXs0eNGlVSVlZWeuqppw5oaWnhAKBnz57Db7rppu5jxowZ8uyzz3aZPn16P6336urVq9OPPfbYIUOHDi2dOHHioN27d/sApohcddVVPYcPH17ar1+/Ye+9914mwIjfrFmzeg0ePLhs8ODBZffee29hsv2YcfLJJ7fX1dXpy5Md+7LLLut9zDHHlAwaNGjoxx9/7KgaevHFF3NGjBhRUlpaWjZhwoTBe/bsEWRZRt++fYfV1NQIACDLMvr06TNM+wx/KEyYMCFy88031zzxxBOdNsD/61//uufhhx/utm7duuDChQsLH3300Sr7mNGjR0d5nsfevXs7dV61tbW+nj176r+AR44cGUtLS0v6tW5paeHWrVuX+dxzz1W+8cYbh6X3eTAYpE899VRVTU2N/4svvkh76623sgKBgHLttdc2AIAgCHj66af3LFmyJF+7p0tLS8NZWVnyG2+8kX2gx0318bkBQBzAMAAjAAwjhHTYlNiDh0RIS9Amyo7algjWVLKQnkztlrnJEY6xh0J2mvvfiO/Vtk6UUuxpDCMmKkZ48BCCU2LgOA6SapehVZUSKBYvNw0amTMrjFHJXTzR/d8oBbFdnb+u3Iml5VY7RHPYNkvtNpAe9KO4axB5Qhy37rkSHwZuQR+ibrf6QSNUSnnIIOChIBSTgS3LAaogl4QgU6KOYTl87AQMPzgAgMiudzvMfzoSXG9ecBI/e6WpRs40Qhc32auY8uGCNHLUWYKIooj3338/e/jw4REAqKysDF566aUNW7Zs2Tx48GD9wq1evTr9xRdfzF+/fv2WdevWbVm0aFHBZ599lpZsm4ceeqhKUx6eeeaZqiuuuKL++eefzweAhoYGfv369ZnnnntuC2D0vtT+27RpU+CEE04IT5kypfm6667rec011/Q655xzGo499tgoAJSXl2c8+uije7Zt27apsrIysGjRoi61tbXCggULun/yyScVmzdv3jJ69OjwH//4xyJtPsFgUFm/fv22WbNm6Ww9FouRuXPn9lm2bNnOTZs2bZk5c+b+m266qae2XpIkUl5evuX+++/fc/fdd/dQz6tg9+7dgU2bNm2uqKjYfPnllzd0tB8NS5YsyZk8eXJzKscOh8Pc119/vfWxxx7bPWvWrP72fZ1yyint33zzzdYtW7ZsPvvssxvvvvvubjzP4+yzz25YuHBhHgAsW7Ysu7S0NNK9e3fnLzsVTz/9dJF23ZcsWaKTgBkzZgzQll955ZW93MaPHz9+cKL9jhs3Lrxz585govWJ0LdvX3H27Nl1J554YulNN91UW1RU5Pij9dFHH2VwHEe180p1TrNmzdr/+OOPdxs1alTJ3Llze5SXl7sYPVrxwgsv5J544oktI0aMiOXm5sqffvpp4tJ7FdoPFu0/jfQngyAIKC0tDW/cuDFYXl6eNnLkSIvPU15entKzZ8/4pk2b9DnPnz+/dsGCBQesuqVaVXo9ABBCMsGsO54D0A1AhxfPgwc39M3PSGncvW9v0V/LCoVCKfgUnda0Zuk5aX7X9W2qkvfauircsoQVSffr2uF3u9MQ4q2Q+aBOyDTFjVPilu4JGjQyZxYXY2LyQgtG2qzkZHNtK0q5xAQ5EypxCwQAIWgJbca1Pw3RVj0UGYcAGTx4KKhsCAFrmS1HCSqxVD20QgFFDQVDtOXcqYrb6G4+oFGbeILPkvBWexCAzdEyRt1Wk2/DptaE/kxdleMhJYzIHmkwN5kfP35827XXXrt/9+7dvu7du8dPPvnkkH38ypUrM3/1q181Z2dnKwBw2mmnNX388cdZ55xzTnOibew47bTT2q+77rq+1dXVwgsvvNDltNNOa/L5GGkeO3Zs+8cff7zDvs2f//zn2pEjR5YGAgHlueee052khw8fHiorK4sDwLnnntu4evXqzGAwqOzcuTM4bty4EgAQRZGMGTNGd4qeMWOGI7l0w4YNge3bt6dNmjRpMMBCVAUFBfoNc8455zQBwIQJE0I333yzHwA++uij7NmzZ9drcy8qKpLXrl0bTLaf+fPn97rzzjt7NTY2CqtWrdqSyrEvuOCCRgA49dRT29vb2zl73tZ3333nnzZtWq/6+npfPB7nevfuHQOAq666av/UqVOLf/e739U9++yzXS+55JKkvTZnz569z61H66JFi3b94he/cJhEJhpvx8GkFdx6661199xzT8+5c+daQoxak/iMjAx50aJFu7QG8KnOacKECZHvvvuufOnSpdkrVqzInjBhQumqVau2jh492vnLV8Wrr76ad+2119YBwPTp0xsXL16cN3HiRHfzTBXaD5aUTtYE7ZpR1jbRcQHt13TKlCntd955J1Ihhm5Itap0DoDjAYwBsBvAs2BVph48dApBH4eoqCDNl5rYm5dhkK72mARZoUhRrEM4zohSut99gzaV2K3b3agvS1lxo0oH3QoM+OItkPkgqFY8QBW9qpQ3mfBG07ohGNmL7IZvMWzNLfhPwRMAWBupTbWtGFTknr8q+jJZBwWXP7gikhA3EkGYBiD4BEAIWBQuzdIDYlgnUBJ4SODBQ8YlE/oBrUw5CyIO7ae1QgGeAyNZMRsniIcAwuHq4QRYpS1Ur3erqXPRqIsZKcsvtm4vpAHBXCO8mlEItFYBvcax98UnA9veYa/9xg8DTjl6WidoeUX25enp6a7MPtlDONE2bjj33HMbFi5cmLdkyZK8Z599trKj8XV1dXw4HOYkSSLhcJjTiKPdI5EQZtcyceLE1rfeeus7t31lZWU55kkpJcXFxZFvvvnG1eVAy3ESBAGyLBN1G8dDtaP93HPPPVUzZsxouvfeewsvueSS/ps2bdrS0TZu52jGnDlz+lx77bV7L7zwwpbly5dnaYpgcXGx2LVrV+nNN9/M+vrrrzOWLl26Cz8C1q5dm15cXJyQECUDz/OuPpipErRkyMnJUWbOnNk8c+bM5hkzZmDZsmU5iYjb3r17+S+//DK7oqIibc6cOZBlmRBC6FNPPVXFdSZPJwVIkoRt27aljxgxoqagoEBatmyZJSzb2NjINTQ0CCNGjIiuXLlSJ2q33XZb7b333ttdEIROM+VUzyANwF8AlFBKT6aU/kEtWPDgoVPQniOp2LgpCtWrPEu6ZSEcl9HQ7lSoEiGkEjNzWDYjwDvWm5vKC3xqX4lEHmxuEOItkPk0VJbMQmtuGSKZvfWen5wpVNqWwyIFBTXsqzW8ZaW+7qsN5me19XtOiQ8E7sUJUhLilo0wIvAzkiQEjSR/AAGivpaiJuLG7EAEKBhQkAmkMVK5H13QFGPXTQHA0gQJsOMDo28owEigEAB425za9gF/KTXeayph0VBg2lNAUE2nEgLAtCeN6tLWKuA3LwLD1C4K2T2BbiPYa1ObMR7y4QmVZhZKaKnyHbL/MgsThsUOFJMmTWp/5513ctva2rjW1lbunXfe6XLSSSclTe7PycmRQ6GQ5Yswe/bs/c8880wRAIwdO7bDh/oll1zS74477qg5++yzG+bMmaOH68rLyzO2bt3ql2UZ//73v/OOP/74thNPPDG0bt26zI0bNwYAVkG4YcOGpNGcESNGRBsbG4UPP/wwA2Dhy3Xr1iUN702ePLn16aefLhBFdj/v27ePT2U/PM9j/vz5dYqikCVLlmR3tM1LL73UBQDef//9zKysLNnewL6trY3v06ePCABaCFrDZZddVn/55Zf3nzp1aqMg/KDpbQCAr776Ku2BBx7occ0117i2nPyx8MEHH2TU19fzABCNRklFRUWwX79+8UTjFy9e3OWss85qqKmpKa+uri7fu3fvhl69esU/+OCDA1K4EiEWi5E5c+b06t69e3z8+PGRqVOntkWjUU6rRpUkCVdffXXvyy67rC4zM9PyR+iss85qbWlp4bds2dLpME+qodIHCCETAVwM4DlCSAGATEqp6y8kD/+7oJSi/23v4PrJg3DtZGfKgnbnpmLt8eAH2/DcZ5UQOIIRPXOwdW8bFry7FTVNEbxxTccGuK1qKNTcxik/w49QjClf+1rZ88f8Ayx1xS11IiBIIShCALH07tg1bC7bnPAglIK3WHiwY2vLqtRn50iyA8sCv8PmnXejR+4w5Ad5wJTTXycGwZ6MTjKZjLh1IW2QiB9Bnnf0BtW6HyDaAoRYt4M4BMiUA08U+DgCFDKytSL3XFTW+yDJYciUsOupVbt++hdg0p3sdTzEjsOZ/uwQAnz/hXViMROvSOsCDP01sP55RhQJZ61W5ThYfn9q/UyzDOsQjh6mUOkR4Lk2ceLE8AUXXNAwevToUgC4+OKL64877rjItm3b3PMHwPpXjhkzpn3QoEFDJ02a1PLMM89U9e7dWxo4cGD0jDPOsJyzluOmvZ83b15tKBTiBEGgs2fPbpQkCaNHjy558803sziOw6hRo9pvvPHGXlu3bk0bP35828UXX9zM8zyeeeaZyvPOO29APB4nAHDXXXdVjxgxIuGvtGAwSF9++eWdc+fO7dPW1sbLskyuuuqqfclI5fXXX19fUVERKCkpGSoIAp05c2b97bffXp/KfjiOw7x582oefPDBbtOnT29Ntk2XLl3kY445pqS9vZ3/29/+5nhG3nHHHTXnn3/+wKKiovjYsWND33//vf7lO//881vmzJnDz5o1y7WaMRXMmDFjQDAYVAAgLy9P0iomtXClNm7ZsmU7APYZlpaWlkUiES4/P1984IEHvj/zzDN/kMpdtzkNGTLEQcgqKiqCc+bM6QsAiqKQyZMnt8ycOTOhP9Nrr72Wf8stt9Sal5155plNixcvzpsyZUp7ou20HDft/UUXXbR//vz5DhI7Y8aMAX6/X4nH49zxxx/f+u677+4A2H2ydOnSHbNmzer7wAMPdG9sbBTOOOOMpvvvv3+v2/HmzZtXe9FFFxW7rUsGkko8mxByF5gFyBBK6WBCSA8Ar1FKU7ePPwwYO3YsXbdu3Y85BQ82xCUFg+cz+4nK+05zrB98x7uIywrOGdMLD3RgwDv8rvfRFpNAAJw/rg9eNDVdL//9L5EVTN7k/bbXN2D5hlr88cxhuO6VbwAAffPSsbsxjPwMP2KSgnXzJ+OmHUFIAAAgAElEQVQPb23WG7pPGdYNZ4/u5bq/ya8aRPSjszZAsedcJcCk10rRWDQBVcUX6sv6bXkawVAtviu7CqX//T0AoL77iSioXQmZD4CXY7hPPA9Py1NxLv8x/uz7OxoLfob/13wz+ufyeLV+mnEtlH4YzlXik9NXI56u53Tj8kXrMIn7L571P+g6r3qhO7oGFJDTHgK+W6nnrAHAH8WLcKfvX5bxxdFFeM73Z6STGNoufAcn1r8AfPh7PDHgaTy4ORsv/KIJc7/KwfAuIp5vvpRtNOE64Jd/YK//fRlQ+Skw4f+AD+azZbdVAX+yXe/JvwcKbEXrUpwVLBAOePtGoFV1Pzj/Zeu4z58Adn8KlJ4JdC0GVj+EO5SrcM7l8zCqT+qFZYSQ9ZRSS3eXb7/9tnLkyJFJ846OVrS1tXFlZWVl33zzzRa7gpQqli9fnvXQQw8VueXEHS0YN27ckAcffHCPW45ZKvjkk0/Sr7/++t7r16/f1vFoDz91rFixImPmzJkDXnnllZ3HH398p+6Jb7/9tuvIkSP7ua1LNVT6awBTAYQAgFJaA+AHMUH0cGQhUfWjBq0uNJXQlWagS+FUwmJix8+OqqYIuqT7ERDYbT6UVGJAPsvLyk7zQVIUSLZuCdrYjpGihEMpOCqD2pQvSjgQWEOloo8VhvFqwYKiKnD5GdoPcgWirCDN1pw9BiaedCZ8CwAZSiuI4GNkyKa46TluOggEnoMMHpm8iJ8PyNNtQrKC7Nza4oBM1VDpz/+PbeY3VZDGw0wRMxdM2O+DgZOdpA1gfUi1nEIhSRStt5rvllkAdOkHQC1OSLyFhw6wdOnSrMGDBw+94oor6g6UtHnoGLfffnu38847b+CCBQuqOx7t4UjAKaecEqqpqSnvLGnrCKkG0eOUUqoldhJCUisJ9PA/h2i8A+KmVx+mQtwMgmInbpEOqiwBoCUiIujjIHAED03OwfRPb0c1PQ2vTLoLm2tasacxDEVtLK/Bz3P4+btTAFB8cer7zokDkPkgUiVumvkutVd3Ep4VJ6jErbrfr9FY+DP0+P5NfYii/q7STHE5WYQoSsiwkcs4Vb/GLsSNVxu5t3QZhpymjZZ16UoI4ArVHDcbcSO2aAXHI10AJIVDkMgI8ETPictWiz9W7Q2w4gQCoEBVJ1Vyh+r1QPP3zNLDrQ+pfl0SrzLGJBnUexzLi/NnADEWEeGonDLP9uDEtGnT2qZNm1Z+sPs5/fTT204//fQfzDz3x8CaNWsOWClbsGDB3gULFlhCavPmzeu2bNmyPPOyM888szFR6O1Q4sc49pIlS7LvuOMOiwTfu3fv2IoVK3YermMeiUiVuL1KCHkGQC4h5AoAl4F1UPDgwYKoiVDJpuICO1IpTjC3rOJtxrhtUbsixIhabUsEJd2YctUaEZEV9IEQgl5BpmIV7f0YIyY8jF37Q5AUipVb67Chymi95OM5ZLSpxVym3p/m7gcURC8EIIqErKZN6FK/FvFAHmr7n2WZk+abZm8CT8EhEGvQj9WcPwayL5vtG5rSyI4dVBW23Mav8QgexMfB+ZZ9xcGIEGcjbjcIr+rErb5wIrKat4Kz9wflfe7Eza64EYLu6RRKO8f2SSmrQuV49Mhk83ypMh3pgsKIm7Y/Ldft75PYv12HWCo+HYyq5ht0iI5ImNZVQc2lO4TFCYqiKITjOI8GevhBcP/99+/9IUjaT+XY06dPb50+fXqn7TiONiiKQgAkfEqmWpzwICHkFACtAIYA+B2ldMWhmaKHownmUKkoK+BtSpNmKpvKg9Q8xK64tUScBXiXPb8W63c34d1rJ+KMxz+DpFCM68d+MAbDNZadairW3JetRMEcKiVUAiUqKTIRN3P1ZmHV+xj+5fX6eztx0xU3Yv2qaQpc991vQuF8oCqBMpvo8mqxQQ5nFDCcwq/HN0Fb2FglbsRke0HkOOYKS/X3H9Tn4ErCA3bipnmt2fL19OIEDbKIHhmA1M6r86Ks2pTw6J9jzDkscYzraqFX0RYhEPyWik9QCmR2A9rV54PddDcZik9Jvl69xjw9ZL1KN9bX15cVFBS0eOTNgwcPhwOKopD6+vocABsTjUm53lglaisAgBDCE0IupJS+cPDT9HA0Yb/JrsPeW1RRjM4HnVVAfDabjpaI8wH/zR5W8PaPT7/T1bqA6hc38vM5AKATI1+C1lZmhZCT45DVsJ7WhkohAmtVpZI3QbRFfkwqHQBd4bIrboopXKhwflDirP4MQMRvJ/ZD/jZr8VR+AuJmDpX64tYG7lUhwT3EGFJz7W3EzZnjBuT4ARma4qawllQcj0ybJ9/ndT7VzI0ADbsAs48aH7B2QPj0L4YqB1jHJoR673TpoHWkStwESIdEcZMk6fK9e/cu3Lt37zCknh/swYMHD52BAmCjJEmXJxqQlLgRQrIBXAOgJ4A3wYjbNQBuBvANAI+4ebDg6VWGZ6RkI25mCxClg1CpZIul2kOuLREXYpHmQ2MojqomQ6FKFKr1JTBhHJBvEJiytbeifMLjAEwhT86ndjtg52LvNUqobFHXDMXNXpzAW167EjcigvoETGl73bI83ebXGKMquTTZgQiilbjJhHOQR3Zi6nEdOW4ilPSu4EzdCDJ9rF8pD1kNlYoAJyBgm3pUJmohAQUqPwG+NlWn8jYXis8etb73d8LSqCMDZPWaclQ+JHYgY8aMqQMr0vLgwYOHHw0d/WpcDBYaLQdwOYAPAJwD4ExK6ZmHeW4ejkAM6GrkL9U2W1seXbl4vf7aroBQSnHfu1uxpbYVAPCHt6xpDnYC1hiyKm6KQvVlX+4yOiFwbOfmAwGUOhQ8Dfm8MeeiKqM4QSNgCudj1aASKyqw+rA5Kzu5BMTNPM4ntrqSkABE+FwicgFHVSkjbjmNGyHEW1C25lZktFVaxiiUQPu6P4bzjBUakXILldqKCIICIFIBAiRg32agpQogPHgbCXaQpE1GyBaCery+Ex3nBYDZeKSMDioZNMWNyFAUL7LpwYOHowMdEbcBlNJLKKXPADgfzMvtdEppChnEHv4XYTa7PecZw1iVUoqPtho+hnYD3ogo4+lVO3Hqo6yT2mvr91jW24lbc9iquP3p3S1wA8cR9N36N9MSClAFmUF3sdkvtbrvRyVgPpGtH7ThfvXfByzjHAqclhtnI26crQ+nmxoWgIgMEnEsD9qIWy5hocaydXdg3Idno0fl6xj25Q2WMQp4/RhrMdxYkVHA/rUpXQGIVqNcAAGeQAIPgYrAwpOA7e8zctRRJahkOgfdILfIfWz35N5+FnSouHGQiIAgxKOmV6kHDx48dETc9KcLpVQG8B2l9Kgu5/ZwcDAraVoTdwBY812jdZxNARFl4/2b31TrlaEa7MRtT2NYbyIPAJ9UuPuiSgpF34rn9PecIoFQGf27ujva+CX329tcVQoAGS0JPERtbaeCEZZ0r9iKNDhqI24uX8UybjcyqNP+x89ZVb1cGHNOb98NwGhUr4GFStVraCY8Q1UjX94P+AzyFoBqeGtCgGe9Ty1zIrbOBXAp+pRMc9FDsgnYHp/cVJkdIHUWFufSkImwxVrGgwcPHo5kdFScMJIQokkQBECa+p4AoJTS7MSbevhfhCRTDCA1OIn7Bv+QfwVFoeA4YiFmAGtGboZoyml7b9NeTBiYj2/2NGN8/zx0ywlCsKkr72zci7aYhMW/HQ8AiCfwFxElRc1JU4/L+UCoBIFz7/jjE0OuywXJtpxwCIRrHeOIuYKbKhi9Su0gYCM3diLoVjgwlqvAPqnRsTwARljnxq9BEWlCF9KOidjkOm99KpTohK13ely10gaQN9AYxPv1KtAgURW39HwgzLrvBASXFlokBcVNNBE37bonUsvsfnfuZ6Puo+ORIpeGTBJx5Ft68ODBw5GKpMSNUprKX1EPHnQolOJF/73oRpqwmfZFRPwlMgI+vbpTg73VmmQidlFRxurtTEG7YFwfZAQEVDc5Q4art+8HpRQkiSErhTUPjVdi4OQoeM7dfd/scxbO6K2/FmxVmgDB8ctPcO7ApOwEwoYFkmxLync0hE9AZLJD3zuW5bQzL8pGZONN+TjcKSx23dYMmfDQvs5Bs2JnvnSm0GgAcRA+HTjjMVZAEGmEnyMI2f9kcDw6VNza9xmvtRy3RJ+Z/bokRcfMTeTTkImIo8LZgwcPHo5UeCXtHg4pJEVBOpjC9ZL/Xuzfz/La7KFRe46bWXGLxGWUVzOipD3fhQT2HTFJNcK1Lc8MMIJB4SRJvmhTwmpTzlSZKfqN3paavYai5qplN7srXAQG8UsLG51r7H1Nqwb8xnX76v5nW95nqflrO5Xu+rJc9dia+hWwe665QCacfjETqk+m0GhBQAHhfYyYHX8DcPJdCPg4iA7FjQMIMG+MsWhKT9t8ImbV0CVcCwDB3I5z1jR0goNJfBqySMRxv3nw4MHDkQqPuHk4pJAVQCRGnlLTXqYY2UOl5dUtCMcNkhO3ETcNRH3QJ+ohqikpGoHTEFQVPrOyp6g2HWnh6oTEjTdVexKT+ibEWcZAc9exjm3MILKxjS9mEBaZtyb/i8F8/XV1v+n6a0mw5t5lUqYWzpcuwxmxexCjPnTdxwo4ZMrOMUic1ih2KJRA9LH2wjElgZBuUtyK0mRrVSnvw5BcVlVqAeEBEEzpa1zP649RX/tcrD007zU7SRvxG+DsZ4FgTofngsLSxPu3Qeb88EOC1EEPXQ8ePHg4UuARNw+HFIpCETeF0+ojjDjFZeuDszUi4YZXv9Xfm0OlITNxUzmAPwFx04ohYqYH8+nDu2Nkr1wAqt0Yz9Su9pxiACyBn3MJ1WUEeN2mQyE+S4UopzAVaV+v5G795qIDX6xZfy0LTpKxt9cUSEIGKnN/jqe3BiEqsFZgAsgA67cZokGU0wGoo7l6Zaum/i2WJiedE8D6nlaWXom6HpOxmzO3AjRdB3+WsTTW5qgqHVlAMKPM9jlwTMkTOOBK/i1M5z5BpmbsdsrdzonkDXAeF2AhVJsqmRDHXAhM/gPQbXiHQykR4IcIOSVjXw8ePHj46cMjbh4OKSSFQoSh1DSG2AMzLjlzl3bUteuvzaHS7ablGhIRNw3m/U8d1QNZqt0HpUAoqz9igTxUDbwQAJBm8zgDgJOGFOCu08t0sqbwPmS1ViCjpQKA0U6KJmuQDqvNhy9uEDfJl+kYu7ffNGw69k/4e2VXvFflx8PlfiypYOdRK/QEAKTL7FrcOJwl+MfggyCyZZo33Le0GFNjf0w6ry+bc3HOZ71QM+BsxODHFfzdkIedYyVLpacbr2OtrhWeXTNsy9QwtJ8HbvO9hIf8T4MnKgnP6QUHNKXNTpztxrzJwAlAwRCHabAbKOeDHxIUr6rUgwcPRwk84ubhkEKhVG96DgANYUY44qqi1i3bIAq86eGdqCpUz3EzmbyO7ctyzzhiVKeaQ6UcIXrBAgWFIIYQTe+JeLArZC5gyT3T4OM55GUEdMVNkFh1Zdma29g+qWakm5y4mcOrmiVHW85gyIK7/Qjl/QhLbK4bmnz4Qiljr32jABj2JLyaf1bM1ejbyiZvuA10IGYptyWclwKCiEwgyQpiMrCH7wNu2FlWctZzDDDmUuO9G0m1V32qhQfmFDLLH5XJv7eO14mb7U9PZ4hbJ0A5AT5IUBLcXx48ePBwpMEjbh50UEpx+T/XYqXJKLezkBSKOIyHcFM7CzEKrd/jVuElXPIzQ4XhObAqTEohuihygJHjZsagwkycOqwbCAguWvgVrv7XekeOm7YVBSBI7VD4AEAIKMejsOYj9NpurcTULc5sTdh98RYQOY7i8r8AcPqxAUBjwThIaijU3Iyek+NQiIDdQy4HTUJM4oo2W4K1tAS35z+GTWks21/LreMEFxJlIz+tsIZj/yWdjDC1qlLL9/ixuVlAgIN7Na7fRDBbq5zrObccNyA3kfhVUAJ0HWIaT6z/akjLS7ADE1Y/BOxa2fE4EygnwE9EyB5x8+DBw1ECj7h50BGTFHy4pQ6//efaA96HolCIpl6dzRFWYTq8/D7MFt5C8f4PrRv8MR945viElY5u3ILjCHhCoFCK8uoWvLOR2W4c0ycXc08utg6mAC+FdTsOzdOt5GtraDEvna0ntlwoygno9v1y04ScxI2TY6hRCwyseXExUM4Haic7NmiUIiIT9RACwmDKJIk268vskGxuPYqt4vNRaTrOjd+J13EyQur+nt/ByJ2fT1RZaiKY+YOc6+3nr55vUDA+KMeej7/R9MZFceMEIJCFDlG1Fvjq6Y7HmaApbnKnbEY8ePDg4acLj7h50BFWiwKEBH08U4Fsy3FrVVtTRXysWKB789f6OoWC5UjtLXfNgQOsKexatwOOEHAccRCEgQWZGNGTHUcXdhQZvBwFVQsU3Jq5z51UjOOKu7Lxtl6jQrwFQUto1ckkA9E6UFWJMyt2nByDwgmuXRHM8Kv9SGXK9i0Q6EqZsI8VcPAuxE225W3Z22bFIaDK1w9/DfzWMW9/oimZ88Z6j3Out5NQKeoY4iDbwWxgwlyg+BRWzMBGGeunPgGk5SaY0MGBcj4EIEGRveIEDx48HB3wiJsHHSG1hZSQwCojFfQOb8ZYulF/3xZlxC0ssAfz0JrX9HXmys6ImODB6qa4EfafHQPynXlkQcp80GTVsd+NuBUXZuo9Vu29RgOxBgzc9HjS+VDC6/u1hEqVOCgREpvNqrCTKJ6jCNlCnJyduJWega0KCztfUMzm3MUWjZXA4w9jYvC5fMt9iRQ3s8WGW5WnFioW0ti/3Uc5huS69YHtOwE49rcG8TOTzFSqSQ+0uEBV3LyWVx48eDha4BG3QwBFofjVo6vxTrmzBdKRBE1xS+Rxlgpuq51reS/JEmSFIkrSHGOpSTPL2r3CdX/mHDezJ5t9jgRAYXbA9J6tT1N90BS1U4I5bBlEDAIkS+GDprjFA+45V27q2Z5IADURtl9zK6selW/AH29ybSBvRsBGongOaLcTN1UJmxh7FOLP5gAjztPX/bIPxegCQLSRUgk8umcJcCvI9SX6iM05bm59Q7XrJwSA0x8GjrmIvVecFi5JkVJrKxPMuYedMdPlmB0I9YibBw8ejhJ4xO0QoC0mYXNtK240+ZIdiQiphrgHEyrlYHtAKgoUSkFlyTHW3IYos+YzAEBRlpWwuHEAAiAUsyp0WUEBQR8PXmxHZvMWjOzNjFyH5rM9yCrxMStuW4OX4qv8u+HnodtaaKHOyiGXJzzHWLDA+l5S9NwxXXGzkIvOEWEeQESxkibOz1SpKloA9JlgIT45fkb2RFvOmwgBPIGr4pagEQXgN9mWpHd1rtePS4Gs7oblh7n3aiq8SgvJFpQCvhQUN/P9ozjvpUSgvA88oVBM/Wo9ePDg4UiGR9wOAWJqmM+X8Gl4ZCCskqHGUNzRS9SOldvq0O/Wt7Gjri3pOEIVUApQ9cEucwE9FGsmbsEIKzAYXMSS1AcXZuLK4wcYBryReqwMTcPPOdbuqT1mfXi3RiUIPMHoVZfgZx+ciZ4ZBM9cNAbje7L4oZIgVJof2oGTlozAuBW/ZvNVlSPRn4NY0IW4gKCpq9HfiYLgVvEKvZhAswAxK2/UJkGt3ivg5V1GXNNel0EIIFLTNgNOhOBjRMfPUUcou2sagUCAuKNYgYOPZzlzduhea3ZoilvxKUZfUcvk1GPYk/0txDwF5qYVQSgdt+ti40z7l9RtQvXAmr8nJXJaNS8Xd/a69eDBg4cjET8acSOE8ISQrwkhy9X3/QkhXxFCthNCXiGEHB5jp8MALcToOwil6qeAkKkF1Z7GcNKx729iROvlNXuSjiNUYSFR3ZiW4s9nDECaj7cQt27tWwBAb0afm+HDsf3zdMuK7MYNAICrfcvRs0u6azhX4DjkqOMC4VrwHMGor24AAChacYJLhSevxJHdvEWdr9Y5gXcPyRFiyc/6pt9vsZn2QyNlhLNk/V0AjE4Locw+sH/NHtqYjpd3BXXTYWpT5CgIRMW0rOdYFKaz9zMGhh02HhkCINgUt38U3g4A8HEEPpeoZMJbleOB814ERl+ceD3gvDaymYClQNy0itXux3Q8FrCSs7j6Y2HN34Cd/wEqP028nfq585LT1NmDBw8ejkT8mEzjWgBbTO/vB/AwpXQQgCYAv/1RZnUAOFqIm7l3aFsseTiqWzbLWatutioZks2SgqqKm0bcCFXQJU1A/64ZFuLWRdwHgQMmDSnEsB7Z+EWxNRypEa6RuVH0y0+3bAuwzgdmaLYfwXCtuj0LPWqKm0LdqgyoUVVKOARiDc4hIJacNVH9CjXQbACAT2wFH2/ViVtr7tCESV+aaOXmhBIzC1q8H4XpBNtnAPN+buSgXTUc6JYmwy9wjLiZrn2Dr4jNh4NrjpubCqeDcIkNcTXiaydunQ2VBrOB37wIlE1LYTCsxG3PV8DOjwwCHWtNuBlVCx8E2VPcPHjwcHTgR2EahJBeAE4DsFB9TwBMAvBvdcg/AaT4F/3Hh0Z4DqYa86cAc96YnRjZoTVxN3c8oJQibmtCTqjMnvGKqL8nUCBwxHGMfD6CzKCA6yYPRkn3bMs6o2pTAiHEUSVo7z368xVTLe81HzftYf++4tIsniogisQUsKQFBaZjqSHCBhjzLax6Hz97Xz1+Eg+3t/YwMmm/1AqAppjpGGqRgI/nLD8O5o3l8MnZPDKDLJfNfO01jzcf5y4cHvCtqp+PXXEzN7pPsXiA4wAXmxNXmInhty8xtU37jPZudN8GQHoaI2690lLPi/PgwYOHnzJ+LInoEQC3wPAezQfQTKleOlYFoOePMbEDgWZlIRyBOW51rVGs390IwKq4mZu+u0EjSrwUBX6fA3zxFFZv329RfQAjVEpVxYSAgigSeI5AsZndZkqNrs3fASP0qBUP2OfnupkpD4uqpsBaY3beXkQBRio5JQaF8yFhQQEhIKb9EpWwSBDw/QDWC3XoujsQiNapx7UrkMbrxbsysKmB4PM6e/9Pgoao6auZpOuC1sNV4IAwNcaJlC3nOeCXfQ/hfcklynE7AOLWGbgUtxjEbUPCzXrkMOJ2fM8jWw334MGDBw0/+F8zQsjpAOoopevNi12Guv71J4TMIoSsI4Ssq6+vPyxz7CwSuf4fCbhw4VeY/tQXCMUkbKhq0ZfbzV3t0IhSuqSGqT65H+0xCSJsCgpVoFCAmB68mc3b0EOpxVnye5ahXdCWmLhpSf9qKNOu1rlWn6oqTSxYgFhGDwDA/h6TAADV1Fl4QKhq1sv5QQmH1i5DracCVb4ymfQ2BPvoryUXP7IG0YdpH2ZjYwOb4VNbrWP+vDHdsY0MYi1OcLPlsEHgWDGCvg/18vh4IJDsW65IrJVU43cdHgOAqXPCQYZKOwu3AoRULEV8acybTk6xCMKDBw8efuL4MX6GHgdgKiGkEsDLYCHSRwDkEqL3SuoFoMZtY0rp3yilYymlYwsKCtyG/OBQDhNxe+PrKsxatK7DsGWHqFoHbHvPddV3+5lB7dC73kdVk5EH1BQWcfk/12LCff9x3U5RpSNZI1pqLpsbcaOUQhKNB+eYTy7BXxt+i1uUf1iGZpFIwhCeP8ryzbSqz+MH2YiXm1GvSiZa8obrTd6bCsfjZN8ivK8c6xhPqAxeijLFjRDU9zjZsn7TsfeC8n5oPRv2F01Ea7pB3ETB2bZpW4gd98MqAoUCH1Rb1bMW0Uk+HGJnCg3YBWLdblElMzz2EYKAC7/R+XFrDWsltfqhDo8BIHGOm0VxOwyeaW7Ey3LMBMgvBv7fvUDPMR2P9eDBg4cjAD84caOU3kYp7UUp7QfgPAAfUUovBPAxgLPVYTMBLPuh53agOGhilQDXv/ItPti8D7vqD7IibuHJwEu/cX3QZacZak5ti0HcZi1ejw+31KGmOYr2qHM7UWUJum+ZoiAqyo7+mSxUCohix4pHNkIJFbdu37/N9qeSphG9rC2SOBfmphUo2E1zKQi+VMrwWeAXjrlyckRvU9XWpQwteSP09bIvUx3HyKMEHv9tNK5fe1Z/xxwiat5ZgKdojqcWspTthRMpEDeeY8RtW+lc7M8dqS8XeLgStwOG1lPUTqTM71P9OlAFCDe4788Ot/WpNKb34MGDh6MMP6XEj3kAbiCE7ADLeftHB+N/MlA64+R+ALB7lh0wRGdlnZki7Gt1Nynd384emlFTWyotx4zT0xIVxCTFkeOmUAWKTCFLiR/M72awOpRsEk7oui8GGFFL1IWgR66zMwPRHva2bbS2qH7Yzlfra6oqbgAQyehl3iP7vxq2K2/Pxsu7jNCnQpwhzZDCSJefo6iPpvZ104jbnsAgFubzO1t52eHj2HYtOSVYO+Bqyzq/C3GLKwSo/AxY/0+2IKV2BwCCzNgYWd1tOwwZr1M1yN38JrDsGuDbl4FXZwDNVYnHuhE3n/qZ5w1I7XgePHjwcBTgRyVulNKVlNLT1de7KKXjKKXFlNJzKKVHjNX54RDczE3XNbuRwwG7J1jAxTtCVBS8vaEWJXe+h363vo2WSFyv6tSS80GZ4qYpYvt6/hIA66Tw/OeV4JI8zJsJI2W/yGtxzEeHmgyvGdxyUhS/4r4EANw6ZQjG9XeqL4LEyISj+bp2aW2Em6NxcFIECufTt9EKEaJCDs78KA+f7+X1QgnRRtTc+Hs1mC1HkAfqIp1T3F7odhtw+iPWxu8JwBP1PqRAS9w4Xw7E9f4MSQT44nGgblNKc9JBCHD6o8DxN1mXN+wwXn//RWr7qlU7jWx5k/27L3GRga4Wm7s5aMUtiuwslvDgwYOHoxQ/JcXtiMXhCJWaKzwjh4y4OedpzynzuxA3Wab493rDaHf5t7V6qFRXQihT3DhQ1OcMR2s+CzHyUPDmhhqTMufER42MdJV2Sfzw1YgfJ0cBqqB4wwN40v8YxpMt6JLud/XQE0S1cMJE3GTFRGzsxLxa9TEAACAASURBVE2OM8WNCNC+GlrXg41pLEfqgypODw/ztuT4mO0+iAfy0MAz4lYV8WFPKHnMco4alZXU3XAcYX5nKUBQQ6UUFBHz7UKAkMulj8oHUWmaVQTk2Iq+zWputDm1/WhFHhrpSmKdot9nGaa8Vu3HgCIdnoIIDx48ePgJwiNuhwDmUOnDKypQbqrOPFCETGTNTOIONewCV1vUeSxRppbnYkN7zKg61R6elGJnfTt4ooAjRLfB8EHCrvoQBMiIw706soWyUCBJosppNiC8HAVRJAQjzFg3l7QxguOyfU4jU3TMitveCIdIAtLCyTE1VCroF0bmWTjOrzBiQmCEYGO282m1RfP2DPgNZLXS9Iv9aXj1u+TK2YxSdkxJ7ZrgZpybCDwxlDpzjhwhrJepGaf0FHFVmf1aH6RliBRjYV0ASKWhe7wd2F9hXZYo5SDeDlT/l73OMCluGvFrrcZhKYjw4MGDh58gPOJ2CKApbhTAo//ZjjOeSNKCJ0WETXltoYMgbhuqTOqH7cEoK1TPX0sGhVr7Y7ZGJV1xa2hpV3dN8e/1VazJPOEgC+whng3WOssHGS1cLtwQQhpiVEiqyhHF6LzAyxHdl+3M3lGMrngU6W3f6cUIGoZ88yc2N9Nt3iqaCYrNxFeOqaFSg+m055YAAGp8rPCAEKMgI0asRKwlzqGpq2Hsq7XZShXaJRbVj6kzjTh8uuKm5fBRVAYvQMaSi3BCdxl/PcH4IfDQ8TyO65eZaFcHBjlm5L+p4eykaNjpsjABefziSaBqDXudUWgsN/sANlWmMksPHjx4OOLhEbdDAC1CdihrFJojRiVnSzgF24MEmPrEZ6Z31gk2h+OOMK+bHYcoK4ibvCYkRdFz3OJx9pCmWg4aFBDCQVKJWw4JgUDBz/nNiHPuitMeWgARQsI8uPzaVUhvq9TfB8J7oT3kR6bVYWDF3zF65QxwSsdpka2mys66qDV0ycsxRgpNIbtIZh9sGP8QtuexClQCgjbV362O72bZvi1OsXvwpfp7mQ+4RvAen+g+T+3ay5ri1gkRjOeM+1BSgD8Iz+vrSKgOpw0w1EHO7Vt/sB69UowVC/A+9rojuH3WiSpLw43G60xTqNQ8viV5z1wPHjx4OFqQYr8ZD8mg+bjJCZibKLMWTwkT711QbfJUq25OQcE4AGjtqrplBzG4KBOfbN8PH88hJlmVKEmhECUFx5Kt6M/VYlhDdxSEKvAvTEUQ7OHJURmTufXwcxSUMxS3voF2nBT9BgDQU7JWDVbTfLTQTLQiAxJ4cNSdoB6z+grL+59/cIb+umfl6wDUrgfqg7w5bwRyG82J7sZ1bzMpbneLM8BxAkb2K0CP3ctAqAheVn3cTKiTM7Gj3a/uiaK+xyQ054/E3hqWv/ann4m47Usf2iUCcBxac8uQ3bwZNAFx+0Uv96+d1nhDOgDFTSCARAkUhUKiBAOJ2QbRet+5e+UdbKg0ymxLfBlAkgpiHW7ETUnwAyUtB9CE44Ap589sb+NzGhl78ODBw9EIj7gdAmiELZER76A73sWvhnfDkxembgJa18bImsARrKls7GB0gnnZ52Mjllrl6sTifJw0pBCfbN+PrKCAP/6/EtyyxCA+kqwgLit43P8EepBGYLe2ZiruNik7C/0PARRoBAEID0lIR5HSiDSX7mUz0x7HqqY8aISBKW7JlUWF8OCoe6GGL9aMYLiajeOtD/HKSBDzv8rAfWPbLcRtH/JwL3clFqd9DkALlRrELSIBT25Jw+p9BpEjhP1PDHaFrFqfjOjKGFabxAGgqCydhbS23YgHnd0ZAIBPQOC1xS2i2q6qE1yKhbKpHirdTnthItSKUVtrsc78gEgZUpx5vPkzUutSsOkN57JEOY7mogVzdwqzsudVlXrw4OF/BB5xOwTQCJKbn5vmffZO+d6U99ccjqNO9VQbVJiJ+vYY4pLiWvGZDDHJRnJs89OUNZ7nEPDxuPS4fsgJCsjLsGaz724IY/3uJnAB5/ntRRf0hq31mEoMYmlF6NNeA2C4Y7swyYBZ5YlDQFoCUqZBFtLBiW2u6zgq4diPzgcASDb15d36fOyK8qhoUtAqEgiEqVLaVBWVGHByDLwS03PcPqj2W0gbYNWltCKA3AD7l1VqUih8EKHcIQASWMUk4E0aUVvXwELKnSpOUMdKClPsAjCRJxshPuAG88mgSADnY8pXKqFSt5w0JcHnb67e9ZnC7ebzStU7zoMHDx6OcHg5bocAVFfcnOt2N6jJ+Z2QT3758CdY+CnrHZnm5yHJtFMmv21REVcuXmcJtwLA9/tbLe81xU0jCMcN7IphPZ0FBPOXbgQAtFOnyW2l0s2xTLPfEP05GE63oQ+pcxnD/jm7F5uTRHn3qlLTeZuLBpJBqwTVwKtMpTVO0SYSZPoUHFtI9WlQVWETJLXQQq2IjbnxCHXeMRl4Ra0S9am8QrF3PIBh9mvZBQE+Oxv4cKqE47uzAWk8dShsnVLctPw4yo4ZJIlJDTnohDYXaMTNn8EKFTqCazeIBPc4MStups+2fqvx2t6EPtaWmAh68ODBwxEMT3E7BLArbubH4oJ3tgAACrNSrzCsazMefH6eg6TQThU+/Ht9Fd7ftA9NtqKGXz71Nbbe1x9Ute64600WShNcs9UNaIcmLlKNnzjJFlWvgKIWI8zzvewYo5GHvAAjLiLcq0qJaVk0vQcCsYakcwWgF0boc+TYGUREgphMEOSpTuZkahA1XlJzCVXiGVec5xtUL9V3bYYK5FOHualrjvZVYPdHzywOgB+LpwB1YQXRmIyALantQBQ3mRIsrEjDkz6z4sau4eTeQPl+GYCbn9xBVtYoEsALAJ8JxFo7Ht9tBFC9zrYPF5a78k+GUS9gVK66HV+DLAGvq3mRZz/b8Vw8ePDg4QiCR9wOFp89iuI9cQBlhipmelavqmBhxPzM1NQiO3w8B1npnOKmmdGu+c6aG+cDUyDOfvoLrN/dpC/nU4ydBWHNXZrE/RcBuOWlseMrfGLfsgCnqCMp5o8MIWcXdVXcspq36K9zmspRMXIeutasRF79Vwn3rdiI205+IAAgqhCIClOnNDVLVIheRcrLqkKpEzdjH8fkS/i6QdArMs0UQyNYbsTNXXGzXu/CdA5I1+4PYyedIW4aeVy4nZ275bNSr+vCyRxiEnUPuVPK8sQStBTrEIrMFLdUq0rdwuJUZvlxZjXOTNoAYMhpQNFQYJ+t44NZXTMrft++AgyZ0vF8PHjw4OEIgRcqPVis+B0mbr0HgPHgdqNBbtyIUoqFq3ehqimccPcCTyApSqeImz9BOWImIthY3WwhbQBcuw6YweZOkQerkvKs/0H4XYhbenslAEPJMmOtMhgAcOWgFkzpHsL4QhljC2Rk+H2uxO2YVZda3oez+qOm//Sk85WEDCjqsV+XJ+I/LayvZkwhkCggEKp/HnGF6D1GOYkRNwUEYQkImQoZzh0oozCN6uFQM0nTbTzcQqUuH1uqOWZCJ4oItI/wq/2MLLsRNwAICKbPJH+gujALiIet1aD7t7P/UgVVFbdAJiNfHZnwuoUxt73DepZSxSCSdgh+YOrjzuXmClPza5f+vB48ePBwJMMjbgeDpt2Wt25VpUFV3ZBdnkHl1S245+0tuPalrxMewsdzao5b6tPyqQlPAiQIMB7aSwN34vTHP3OOd0mm8kECMelKXdCGNHtTdgCT+G8cy9LU6k57W4Z6moPz4nfi+tzHkJmejtlDZXRRCyFEfzZ8Yqv+sC6oeh+59WstprpNeaMAAJI/G3ICTziAFTG0Kiw0LVGDqEQkAlEh4DngRLV3fI5f0RU3rbcpwOGCldn4T62h/IzvxkEweaXNX280fuc4Ap5QV+/+3e08xuTF0Mvid5saIeuM4mYem44oJvCbjQUaSWqtAfZ8BWx4hREjwgNdBwPHzGBql5korbiT/ZfqDwZNcdOqSpOYKVvmBAB2ZbZtH7B0NvDmXOvyEeeyQgWzCa+Gyk+A1Q+x16lUtXrw4MHDEQqPuB0M9pZb3uo5bibCIqlP+vJqZxusmmamBtS2JvZpEzjWtl2UU0+01hS01YHrsCM4Q19eRJrxN99DjvFBwaaMUYrtwRm4R3gOACMr/ycsTfn4+m5sYbczY39EdoBDI81wjI0Hu8IXbwYvhnHc8pMw8vP/U011DQJQ19sIeW069k9oyh/telxZSEcYKnEz3eJhmYOkhkovLWW5b7tDPqzZzwiaprhVx5z5iHnpHHhC4PYp8ISoLaec6xpjBL0zKbJM0b9ktO1Wk2NMZ3zcRBPn+i3/jnWlVn359g3Apw8zK47aDUZolBcSN2qveD+1CSgyC5P6MliotCPFzRwq5XhYrkq0CYi2AOH9xrJgLnDqn9lrc79SDS17gKq1rD2Wudr0cFifePDgwcOPCI+4HQQicesve9mlOMEc4vxsh9U2QyN1yTojCKoaFhfdlY9IXNarWvVt1ESs7sTp//ZLfr1jWVaaNdWRU1sWXSj8BwAQEDhcJryXcI52SAKTlxSbKtaMTHQJACHJedvFA3ng5SjSQnt0xY6jskX1E/1GYrriS4fkz3I9viykI6oTN1MXBJkzQqUcp4c2l3zPKhW1HLdXavId+xQ4oipuTiLAc8TSucAMhQJ+nuDvJ7PtynKTK1FXDDP2n+lPnXTURyi0/DjHVhGXpu/xdka2CMd80hSRqVz23LEdKzpW3ShlRIwTACGgksAOfmiYw+KcYLX8iLoUN1DFqCj1JSn0UZTUDIA9ePDg4QiFR9wOAtSmgjn9bq0hzp31If3119834fnPKgGwhvKiGkvdaFPmfCoJi0oyXlu3B+t3G2SsJSKi9Hfv4cEPtjmO2xlk+K3EzRe3PugLspI3R2/krQpIdb9fAwBkwWrLEYeAnADLHbPPMR5kZKn/5icTHsfe+5MS99oayvkQVfuISqYKyrDEoSnG6WFFLUIcV5vFC6pHnEydXwtCYFHVfJwxf54jlibv+nwpq7DlCUWvTILKSzksmyok9eMzF4p06UQ9iyhK+DIwB7cIL0O01xz9958uW5iKEbROEYoEbH5TDWOq8+AEdFhxqoU9eT8bT+WOyZ4iGxWiHG8lbq62MIpVPZtyn/t+pWjiDgwePHjwcBTAI24HAcUSDqJ6jpv2fLF3LojGDaL36yc/xzpTkcD+9pjlXw2CGi+LiQpu/vcGTH/qC32dFmp94+tqyzZMyXN/cFZRp5u/vThhyNes2EJWiVFevAY1tCvCad1xafxmy9j9RRPxbu/r9fe7Sq9Cc+F4AEBrntV4VwKP3AAQkjlHsUVr3ggAQFG1e2iuLXuwk7jZWlPpywnnSty+bAiiLsphT4gt0z4eUSVuRdUrHNtoIICe40Ypq0YtSpPxxzHM+40nTuKuvTfztI4KQczISc6XrccSo+hGmnC18Cbi9vkHsp1ESpZUMsRbOxMQArRUQb9/qOJ+K+0tBypUFVYjWrxPJW5KCiqdbBBGTmDzMK9zjLdVvP7sKvf9imFPcfPgwcNRDY+4HQSoSRngQB1ETbK9b48nDpNt28vUnnDc+tDSQqWOLggAWtVG9Gk+64NaVih4l1T5zUpfbFH6Opbb7UAKVQIT8TOS96Z8DXqQ/QAIPlaOwWvSL/Sxoj8XxNT4uzVvuJ7sH0srwq6SWaY9E4AC34cEfFxjJV2JSJixXnDkK+0KJZKkCGJEC5U6SVhjnC2TbMRNg+LytTCralo+2am9JFw8gvXOFFxCpZo6x3Uyz+rWsQQEFBm+1LcbV2gc3BwexqBfMmXLTqQU0ZrjpoEQIKoqrsFcNe9NVefMFZof3wusf541gNcKETTFDUitOEEbS1JR3ChSKuoQI0B76l1KPHjw4OFIg0fcDgLUVBnHQzGMajUDWtvDMhRzPpCO48pxq/Civs5O3PwqqYraDMEq9rXhN3/7EgAQtBE3SaEQXNLoRfCWKlMN9sdhS95IAIBsax2lFRvwRDEt45HGm8/TujdqqxisVZ1Pntia4QiX7iq50vI+mlakv27PGWxZt6edw6q6BI3FCYGkWnzEaHJCCDBlUTEpPu6KG9HJmebvFjTxnYgEVIetIUqNyPGkc6Hr2cMJtl1MkJ/R8dw1nNzL+Ex+xZs87jQFzC6bacUIHGfNKSOcUaQgBI1ty18D/n2pMVYjWvsrjK4FvClXLZXiBI3Qcry1MGKbSz4l7yTurhAjQFut6Xy84gQPHjwcXfCI20FAMRE3zqRw+YgErP4LpLA1X60t6iRNL/j/hNnCcggtrMVVxKbKaaHS1qg1b2f5tzX663SH4qa4EjcJvOtyzqa4cQoL1/plW7WrRtxgJW7pgokU2B6U9jy0TBMXiYnWh3tr12Os56G2rmrNHYr6npMt6yKykZtmByUcqEq+Yi5j+mZar0F1RLA0r5fBoYvfOjdCWDUqI27sHIOCca5hiaCizQfZRFhkPVTaefLgF7jONYM33YvjObUV1MQbVCLmEjpXJJU88bZOB8TYlxAw8tV2f86Wad5uaWoBR6jeCG2aFbeOeoea7UA4AYgb+Z9o2eMcn9PHqsoBwKgLgXFWsg85bvVx27XSswfx4MHDUQWPuB0EqOkh3TuLA0AxkuzAMagA/vMHBF+faRnvRtw05O5bA4AVKpihEbdZi6zVoPmZhpKV5ncqbrwLQUsTCHyELS8wbW+nB5p3WlqkBhfxK0xr2EjrvikCSe6ilriVMJg5TEe8RPIx25CIkI2rvszBZ3uN85QpsZDlDUp/6zzVog434vb0L5KTigye4u0zFKyaDkzopuCkbjFwhFWOytSw3gi4dI4KRY1ro1WgCj+E6ONm5TH01yrZSZCnpqg5bubcMUIMIiYEDMVNC2Vrvnq89l405bgdBHHrCG6trqY9CZx6v3WZLFqJGwBsebvj/Xvw4MHDEQKPuB0I2uuBNX8HNf2S/5l/B6Zxn2FZ4He4gPsAAEBsykHYJcctQlmeVlYzM0yNilbCZTfH9UECKj+1ECCzG/53+0OIxGW9vZUZlBiK26g+RjN5u7LDmc7rHt9zpu014maQBAIFWT6K63AjlmSc7zjmizusodK8YHIWs62PsY9IOnPJrY36UBPm8cDGDFA1/hiSCHIIU2kekc7C1Pg9lnlqXRvcVLluWcmJgo+nKMgQ0Debw4unCnjmlICe46YAiMua4ubc1uzaoilunfFjO2C4JfQLAdXqwyVUShW1v6jPRvpsipuikj4tD04jRVqYm1J34uZGJM1QRKBLPyA9HxjpvG8cyO3jvtzO/sUwsOtj27E6IJEePHjwcATB61V6IHj5AqBqDYSyC/VF94TuBtRc+Z8R5oVlDxNGbKSMg6L3+vRFWYWpJFMmemhhNttT/2bhFeD5t5F5zLOA6lVG1YcypRQnPbgSAHA8Z+3qsFoehjwfhaB2PzCH7+zPPk5xDy1xqs2CpfCBUvAcMPO4YlBa7NjmQ3EYXqUn4EulFADw+3EU7+0m6ryd2F1wIvZ+twk+SOirKm7mvDyJUvhA8JfyNNxGWEVnNe0Kq27I6Qn6wzJaYe7URUDh6yB0WRNPsxQUaPYdmo9bTGVkaS4dJzRSB5hDpUkPd2jgllPG+dRqzUTETWTETbYZ1lpy3GS2vaa4aX1ItTFUttqBaASvIx83KQYEuwA372T7+viexGPT8oCTbk++Pw07PnQu8/LcPHjwcBTBU9xc8G55LfY0Ju4fiv0V7N9Ik+vqPMIqRKktBGR/tg4kNeDUxHW/yPLhREUBb3rQ2EnGYFLFljfvchw3ZipgWOy3+lxdIs4DITz8quJmoTl2xS0BcUsPV+OyQVHk+gwipTWSJ4Q4cuUAQKQcbpGuxOvKL3BG7xjy0wjmss5VjkJHSoHb1mVgpngrLhDn6yE8yzj1dY5fwWPSr/GiNAlvyhOsOyIEMZVFT+veYD03Amds2IYMXnHtJ8oTYEebD2FJU9yc1DOmOImbC7879HAjSrxfTfynLiaDmuLmtylSJsWNDxh2ILyNuGnkXduPNj6VUClVWN6ZP42RKnvumh19jwO6OKuhXSG5dSHxiJsHDx6OHnjEzQVXvfBfnPLwqsQDVLWByM7enWYoxF5lSNEUiqPfrSznppQwVaydBuFTzV8lmVrsOXy2BClFfQjJsvPBGFdNfAeQGse6E7q2ITNgVJUmEyE4OQ6a4NaY2jeOPt1Z0/amrmPRXHBswv3saOV0kgMAlw7l4OM5vVJWUijaRYPgxBWgIWY+rjFOg0biBufIqEcX3C5drpO0hX0fxKZRd+FvW4PYE2OFDX4a04kiwG54t1N/XJqmv75yQKNrYUC5ygH/to0pnUGX5DVTipurj9thg1u3AUEjborTnoMqrBqUF6yKW1uNQQJ9pqpSrcJYVIsItA9CMSlugjnHLUmoVAvFCwmqgu3oiNjduA3oobY/C9UnH+vBgwcPRzg84mbDxf9gVgpRMcmDRyNuUnLiltawEXcKi/F2l79gJv8+KIBNNcYDtoAwv6w9tABFke3AnjWQZEUnbvcK/8C0DVfr4zMCPPwCezC2xUyVneozVKvSHE6catz1wyLICvBI59gDvDD7/7d33mF2VfX+ftfep06fJJPeeyUJRBJEegcVUKogeEUQf6CAWMArKPYOgu1a4aoXCygiIIJUAekJJQmQhCQkIX16O2Xv9ftjrd1OmUxCkslk1vs885xzdll77T0nWZ/51iRVyRjHjrOpbloWOVa4WdweAsY3jX8fq2ZezrrJ55FP1JQ97jPPRjqr+/F6cf2ta80JLnismu+8pIRQ4SOXWmKFt3tFV7wuBYcPD6yDjbKKjvQI7lufYElOx0Qla/j0fIvPHeiNGYjWGxYGwiuc6FCdLp2t2qm1z3pd9iMVMqXdoGoOk4kINx0TuKcMPq0bYJ1KavFcja+649W1sYLCtp6FC2Dm6Xpyui2VnYRDQ83cm98KCtjaun0VEpL6d9mp1asfw+aWiXHrwVWa01axZHHP2pLsoMYf1cPhQ3/s4Xzz35zBYNh/MP+jhXhzazv/XrFtxwd6FoYSFrdWGW3zdFHsH8zqep4b4rchpWTp28olOlOs4br47wFolDXYMg+/Oo58Po9tCeaOruW82EMM2fo0Pz17NpcePpEpDdU4Wsycv/k7gCQVt0jnW+Cuy8h1KatdC8ULosRCWjGGxrv50okTede4wfzgrLnc3HYVCx88jQlLb9EHuljSKXLzRhA2bYNm4xa0tNoRXj1ZT7ht6bJxETyjm7zn3KjCadUZqWu6guvkHE+4wah0ni8cHBTh7chbdOkYs3+4B/NJcS1yxqlAYB0LN4K/cGZwPTsUA2alS2QwAunChgSh+nUTanWhZEfQko1eq7DA8W5hw4tw79XwxA+gaY2/ORdT/Vu7YzU6OUELt7y2qnkCzHOH23EYHu1wQVbFDvoxbuHit42r1eeIxU0LN+963vZybH0tON7jnNvLt7GK9aKFRLo++nnK8aEPxlVqMBj2H4xwC3HPyxt3fBD41gQn21W0q4vyi4zjwootalE80FL1sB50DiIbyhE5esPPsIXg4sMm+tuStsuC8YNIxKxIP8z/jv0eS8BX374YlvwO8e/vAZCiRK9GYeHYaWw3w/j6JImYhSUEFZ3KrTpp6S0kOzb4GaX5eOkG7r2lVMN1T7B5Zec8t2hMx/kVWtzWyOEAvOgEz8KrluJIFa8WSqilyxF0+R5BwavWdERaZc+O0FpWIkp2MgiXOIlV1BXth2KXZzrkKq3Qv8LnGxNc+Hg1L2y1guSEnSzAC8Dj34XHvt3D/u8E70ON4StS6vuXidcq96ZXgNcTagn9IDwhZ2vhO+v0YDzvDxIvq5RQ5qibizaRd8MWt3jvLG5ebOiwkGCcfnL5NlaiF/9N2QVWueO+AlNP8gbY8fkGg8HQTzDCLURhi6qyaGvC2u0dRbvucg4te5qUkryOQ2vXlrmv5z8UOeaYxtuxLBGJQRP6epVJm6N51t9+cew+juNZ6l3VeP73LyprYZpiS6BE4MRSWE4WoRfaitaVkWNqGl/1i++2DJ5PV8Wosvfi8XKjzbqO4q+RU+JR1mhNm9CHN2bVG6/zQqHF7Y3ETH4z4jr+4Bzlb+vQFjXHVR0J4qFLZ118ixsoYed9mhLSYqXi+yxtcbvXOZh41aDiA4CCcnkRC5xXGuSNViUg/rPpHca4bXgB3l68456fAE1BBvFUbXiqrhusbrTQVaozdSMWN4AzgrIv5PT3J57WWaMysKC5OsvUE2uFWaW9EW7eXEaXj4+MsCtN4+MVcOat3gA7f77BYDDsoxjhFqKwBVPOKfEfvuv6i9IB1urIrmtyH2OFHF12fEdKXxzGhJfdKVRtthC2CNpmAdg6IHz84GIX6GCC7gxVQsUOzbDeAqCjagKdlaPpqJ6AFDaunULgYufVeO++/+TIWPFMo29xc0WMzaNPKHsvoGK+rn+xkm+/lCraV0q4VWrF5omttpwX86YOzhY87o68xbbUeMIWk7Vtth5f1VUbVQmXzlLPMueKiHBb1R73RVq0WG6xcvNi3J51Z5BMFt8PBILTIxnyJqf1ey+eLeOI3VQOpBfCLeSyF51KvMeqh6oNvqtUiyXPVeonCGg1HVazXmZmwju2K0hukI6aki/cQiLOClncyrlKW9bBS7fr8XuZnLArnQ8sWyVX+FZDg8Fg2D8wwi1EYW/RVVvbiw/a9HLZ8x2ski2lPKRUWaOAf5wrbL+bAai2VIUWt7lPXcaI1Xf4DefDhPtgzrOUBe2SmMpafWvqBbwx779ZOetKsGwcWwmSeLaFRFdx9l082+qXAlFN3Xv+enTpjNH1nTEyDmzpCuaXL7FWevXQPJHTqmPBGrM2L2y1i1ylv1hZ7K5tzQfxY5ZQpUyuOThOVVySdQXtuegz8rJDw8ItfMR0baFaJlW5iRVyFFYZK9e4gjyMcFapZ31bqrQajQAAIABJREFU1a57pLqBW3tXWl759Mbi1roheD9qgbKyeUkIlq2ES06Xt6nQrao8IWeVcO17wm3IFPXasiHIPPUsbk5IyPnWvPSOe5WuChXH3VHHhJHzIVkTcnnuAlZixzXlDAaDoR8xcIWb6xZZBQoNbNfc+UpxtwOvhlupIaVVZD2Lji/J6wXtW/Ffqo0iLPYE263B2uIWUNv0CrOe+wIJWewyioVE3xixJZId6VoJEAKprSquXqTtfAeJbiXcmgYf6B8/bP0/GPf6rwDVZUH04KLKOHDRE4GwumFxBZc8WY3rRrM+PUakHWI6u69Ce+eac8HX78alKZ7eonbMGxRcNywAj7ZeRGrB4EglWr3acUlbxci1hYTbxVODGMSwmzMsiu84RXDniXn+7BzBWfIbbEhPK5uEeNPh0XtKlbC4ecjQ3Eu1xuqRtk2hgXoh3FrWB+9rRsAXt8ABZ6rPnqvUK+NRMVgJJt/iViJjM98FCKgZqT53NkGrLjEjXeU6Dce4OaH4Od9VWubfQfiPgR2V+Rg+Bz6/FmZ/sOfjSl5Hj23HdtzFwWAwGPoRA7dzws3zIFkNn3jS31ToKl2yrpm7Fm/gQwtDxT97KCzqYJVsNeWfGnKV+ueEhVuiklgujyVEyTpitd0byEpbBeXrcypR1hGJYJTYzgmDNoE2rrhWInK+lylqORlsx4tlm0v99hcBqGleRo1uvSWFTWf1eAC2NyykZfC8iJhszkbnt6xZlynpztMtEpHYs0OG5vjcgS7o9lNeIH9LaIycK3hKC7cLpuRZ8ox63+pVsRBr+HXie7zQeAhMvBBHRnuApmxB1hX+8QCnTw51PwjrhdCzrYoLDhqRYMUFLnlnHPGY8AUm0lVNyiccDlaM2qQg7LqMhcapiT5qXAR5fWhiZ+qBOHm458rISDvFtJOD7gWgkxMclQ0KKvvSskPCrURmcLZDCSxdXBk3FyQUZNvhtbuDY6UTFOVNVAWWvfAfRd0tKubMjgeCCnq26M4+Aw69YtdKeVz8sCoRAuqaPWW4GgwGQz9jr1vchBBjhBCPCCGWCyGWCiGu0NsHCSEeFEKs0K/1OxrrHdG8Fja/Cn/+iG/VKHSVAqxvKsgc1YvAs+60omNdLJ7RrZ1K4UpJLNfBUIKOC7ZlUaHFVz5WgXTzRRY3jwRZEsJhSXKBvy0t1UJ5F0cCEG9eE5xQsOiFhVuya7O6ZrwWV9fJyscqQ8faZCpG8NIhN7N+8nm0DplPy5D5/v5Ci5rH95bV8PEnq/nEk14NN8knKh5hfmVwz55wW9MRWHtyruDAwUoUHzUu2O4Jwi/MUaVOpmdeYurirzM5vypSHy0ZU2OEC/5WJ0PCLaQXSnku47ZFOmEHog1g7X/g2Z/D4t+VvNcwtiVYOCz47Mog2cIXsdvegAe+GOo+UIJ8wfdtZxJS0/UwrqCLhGfVev0+fUydtrhpq2apUhvdLUr8xbWoc3JR8bP0r8H7TFsZi1vIIvfXj8NTt8AjX4fVocLWogeL23uuhMHFLdR6Rao+MKtahb1YDQaDoX/TF67SPHC1lHIGsAi4TAgxE7gGeEhKOQV4SH/ec3jWhKV/hVf+DBS7SqG4HdS2NrWwtsiqomMdLJbK8Yzv/r+Sl3Sl5JubL+HZ1GWhc2weFSq77rGuiSTJUZuysWRxQHZSKoG3zhrF13MqGzXhqPmszqnYpcFWkKxQ2P3A6+RguVkqW1fgihjdFcN4+ZCbaB4014+BA13AFZB2AmkXmJMoTiTweKXZi/ESHGc9z5rUeRy+6VZ44bbgPkqs1y6CrAt1CYd0wmZanVIsy1piHDO8mwMb1HGVspOKjnVc7twWCfpP2ZB1AyvXXSdmGFETiJJob9ZeWsC8WK/W3pWJCc/HkSLqKt34Mjx4PWxfCW8vCQ7MdcHt5wSxX7nCEjO9FB3n3QmXPtWLSaaUYPISGuyQcDv3T+q1u1kJHk+4ubnycWJNa9RzEpYa2yuW6wm9DvUHAhueh02vqLE9eopxKyzvsTOEzy1q6WUwGAz9m70u3KSUG6WUL+r3bcByYBRwKuCt7rcBp5UeYTdRHTKP6PidsMVt6lAlzJwC12YmqwTVZllc68vZweOULjQ4W4rO+WPsVC5M3cRruaEkyVKTskh1B8kDUruUkq4SEl1unN87x6rbEMri1oiKNztmUKh/qihnccuS6N5OPl6tiugKm3y8GiuUnbiiq5rnt5VfWHO98D4dZ70QfAhZkkaUKZifc1WRXiEEH5pm6W2CwWlBXEZ7UKbJRCxuKR3j5khIWpIpg+NR69nOsPYp6NgWCIBeWmzCwi3jCHL6qxO3gEe/EdoZak+ls0C9Px6Kem32JsYNVDxa7cji7U5BnKKX+eklJ8RDGbTjtbXOddQxXpurfA9ZnUIosen1RfUsfN4z69Z/SJQSaT2JsxJ/LPSasDC3471/hgaDwdAP6NPkBCHEeGA+8AwwTEq5EZS4A4bu0YuH/wqPqcVLSoklYMbwao6crkw8mXxUoQi9IL0thxQPqR2clbHSC30pV6yDRW3KZk1uEBmZICEcLDdPtkVZKtZPOJN1k84FICWV+OkmTrfuz1mjA9oapRJu72m9xx9bFjhcA+HWTSzfgWsnkdoK58ZSxPNBFu13V4/na0sqiuL+PLLujq1WrYTKPSQCtVYZFxwwuMSYjiBuqVmPDiWUJixJzIlaohIyE8moTWlXqVffTQCsf16JsJ3BzcNTNyvrmO/2C36fD54u+NJB3fz95CwVBYXdwsKtNW/54jZZ2NM0XN7Ce76e2CiyuPVSdJQTOoWCySuS67WuCse4hVtL2SGLW7mevPEK9bzyGT2uXdyr1Ms+LVXSoyfLZ09u1HIMP6B4mxUvnyhhMBgM/ZA+S04QQlQBdwJXSilbe+u+EkJcAlwCMHbs2F2fgJOH2jGqrpR2RzlSUpGIcdlRk32RlS2oayG1C2izLA7B8yxuX5vfCq9E97VQXVIESSzqkpJVrRYZHbwfI8fPHlrG0Ulw7LTfWiqdV9aLdjfpuzKPtpXbrY0SNbEKLG5eLFsi28TQDQ/SWTkGqRfI7vSIyLEdKDHruhJbm7ae3hIjbsFBQ/JFpTtK4d1PKV7eXuJ4R4k0y4LBIUNQ0gaRaYscW0V3pGabyipVrlLfEqc7STB2EQiLAxsks2u7oURLMB8v/qyrMWjNFHITTqkTTKkrXX8srM9achaLt6t/XoX13yIWrLCFrWmtcqX6iPLWolStKpXRsk59Lifc7IJ/4lZMNYP37ikWOi+c5WmFYtxKWdyEBQ3TlfvTyajrC7tY7JZzsQ6bVXp79UjV6H5X+K/71O+saniwLZYIEiYMBoNhP6BPLG5CiDhKtP1eSvkXvXmzEGKE3j8C2FLqXCnlz6WUC6SUCxoaGnZ9Em4+CMz+941qkwyMAHFbPZpsQeDbg8tUvNN2imuMHT+sjfeNbGVEwbq+JT0JF4FbprZVbVzSlg+E241bLiYplIvLIeaLq4bOVQC8SbFLLE+xhUIWiGHPujZx2Y8BSHVu9G84kx4WObZDRovQuhK+9XIFX11Swcb2wOJ22axia8yUmjxx8lwWU9mHEqtXcUZZV7kVLQSp0O0kbBHpDgBQRRfHjAxEQcqGNR0x/rkh6dd3C25cPfe/vNfm+kN30F81nDiw4gF9fgnxtPyeopZUYYtbZ97iyS1KFMULfzVhMeNZ2Dq3w/2fD4rTqgPL10OTLgyaFHwu53aMNGgXSpyFy4eEz4uU6ohpa5wobXG76EGYdLSKfytlcfOEW6nfu7DgjFtLz/eSR+HUH0PVLhjck9WqG0Mkq9ZklRoMhv2LvsgqFcCvgOVSyh+Edt0NXKjfXwj8bY9OxHV8FykdW8B1kFIiBFS2r+GkO6czU6wp6p6wfrtyJzbKmsIRWTS4k4/OkCRDK/hB3T+lrWIsKTJ+ckEhcUsFs2e1cKuVLSR1v9GsSPgxbrPfVsHjb8hiS2NORtXB1uFHFLmbXL2o2o4uIRJa1J2CshCdnsVNa5btmUAIvdmc95MTDh9V/BVa2JDnLPvRYKz6qb1aPDPaVWpZIpLAkLSBTEvkWEtI0rGQcItF94mweyzk6ow9/m144Lryk/jPj3qe5IYX4J6rYMnvVEuqbGDNscv8aypsleUnHKx+PCiz4e/S855/vnotjHnzcPLlRVeYHR2TaS+934opIRZLBvGJVVrcn/pTVWPNi49rWR+yuHkFePOw5oniGDtQ/+6qhxdvBxV7Ov/8wNr3TrETJqvUYDDsV/SFxe1Q4MPA0UKIJfrnZOBbwHFCiBXAcfrznkPmo+6l7hZcV1l7Rr+lNOOJ9nNkC3o32XrRbaRYuIGNEKrrQavuRdpINW4sRZKsX7ojzAWjNvotnzIyWGQ94dbiBMINYJOsp12mEAWxT3lirHUDK0WpJvFOLOoidEIZhU4sMBO21U7zrX+esakrVGbDkZDTbsoiNyAgpUtNLBBOCVtA45uRY4aHrJJX6yojK9pi1CbUBcNCLGnLiEDy8GL+1DHBdlcCXaHsRelCrhteuxc2vgTbV0QFUVhUbllWfENhnvwhtIWyTEMCMVPGqJgqrOMmgfYt8PRP4JmfFZ+QqIKh2pWYLdG9A5QwCn9/y4UazP9w6Bgrelx6EAyaWHoMK6bKycSSgRVyzlnwuTVwwFlqu/f96dgK3W1Ri9vLf1Ai2CtDEqZwHnsSO2YsbgaDYb+iL7JKn5BSCinlAVLKefrnPinldinlMVLKKfq1cU9c/1/LNvPNfyzXrtLQwpfrxtEWt4pO1UJoE0PIFKRP+sJNFgujcC7AKdlvcGzmOwxKuFixJBaSZKb4lo4cbfl1vnKhkMM6oRbs7U46Yjk7LfMV3uqwsQW01Ez1t7dQyQeyN6hx4tVsH35Y0bWcWCVZK+QCDQnCsMXtI/lr/ZuReA3gg9M6Xcu3uKXjgg9OgkMawpYVgQzVeYtvW66EUttmf9vd7wvHpwXv13XYehvR/SUETE0+EGepiHATJO+7Itjwj2uUiFj82+gAUiqr0B/Pg399WZW2KEVYZBQF2Qf7OrRwO6A+z0yxhqtjfwJkCeG2g4QDy1YxbNB74VY2Fq4GDtUFfS0ralX7xFMwcl7p8wZNUK9h4WYnoKI+cEWG3aDdTeo5FSZDdBS3VlPf570l3BJGuBkMhv2KAdc54fLbX6Q75/L5tIMVr1JWh65GyHXiSokQgrQWbllp86/lW/jxIyu57ChVDNRrKZUt9ehCLpl1UrmVfntwI4lGJZbq3KhwWz7/OpxkrW9xS4sglujr8V8DsD2XRIpggWxGlSmxBCyfcQWLnlE14d6Wg8mQ4IWFNxMnjxsvlawgaLXrGeIqi1E469S1U2wZeQw3rh3PC9sDQbC82WJeQ1BMFqAtZ5HWYiZlw/cPt9jUEWfRn4JLlXROtb7tl2FpCHnCwiLtlDFZIEHShho6+EH8J2TyHyxpcUvLDv/9oFTQ1aDo2u2b1E+Yp38G654OPm99TRWILcfqx6FuHEpwhEVS8FzatXYdmpbc2PlVqkUXP82/H0sU9sOS5YP2QQmbtC43k+0o3u86ag69rXXmF9m1IvMllixv+aodo49JhYRbwfWao3GH6hIF91pKNFl70+JmepUaDIb9iwHXq7QqGQMklszzfGOSrmm6XNwzP2NI9zoEqtk6wMxatRLf87IWOlL6FrcvzSq2JMTyxeIiYQtcHUs3VkTzLVxbqRfP4lZN8fmdMuEnJwB+GZCsKxDAusnn0ZwYTkZvx46VFm2alZni+nMe6yecye3OMZFtG9qLLW4vNKZY16Fry+l1ujIeLXA7r6HEwhwStl4W8dhKxx8D4IgxShwkbZgq1nGsvZhT3vgiZKNZpQBpN3CVXjgDRle63JW4jqfsS8reo09YtPmTKlOCItOq3Jr3f764v+aL/6vcnkCnFm7DK/C7YVTTSayo56vbc9yVZauMUSgpWH1Ll52A8cWW1SJ8y5zsvWDy7jMs3KwC4RbubDDn7Oh5HqXuU1il4+32BF7LKxPnZjAY9hMGlHDb0trNtvYslraYPLYlzXeW6MXouV9w2ZpPqnVNL25HjlALZLVWFnlXYgm1AIypFqyXQ3jEmcuDc29i9bSP0TisoN0QIBB+c/evxG+L7PPKc3jC7WV3IoVkRSwS4/aZGdEg/e3DD+ON+UGwfWGnh0K2hZIqmgdH3WThcD6/RppeiGs715LWYuS11gT/3KDEQFrXwKiMB+fMHuRw4rhS84guni9/CO44OWpx8wL8Y5YgLXoo/Eo0xq02KfjsApt51ipqxS6WfwiLjrpQAkhrD+Up1jwOf/8UAFv1dMZUSf9Z1IhO4q/oThpTTlCvy+9Wjdt7mofftaDEM/CEYCwBH/4rXPlqz1mYXg09N0+vXZSe5SyWDHVZKBBui/5fECM3eGL0PI9Srl4n1/t5vFOsuLK4GeFmMBj2EwaUcLv0d6qSfxwlyBxstmWDxajWbcISwnchDtn+PHMrmyI13WxcHCySNrwnczP/lfs8MTtGS8MCnHjp+mDhJIAIwutlqcZ/Vs5gdvcvaRK1/iFZEhHrRDhDUeh5JuI2H5rYxdljmnfYzqlNKmvcQ9ahbBofbU4RFm5eL9KcI0i3reH9a77G8tRH+Uryd767OCak32jdEoJVH7FZfI7kA9MrscINQc/6X3/GYWqSFkOr4hHhFm5OX0G0DIUnYLtQzzMRztLtamZYx2s93vsO8YSbsCFVxjJZrqyJdKnQX6UpdYFI+N7MNxFrHlcfwgkRj3yt/DyEHXQt2L4SNi+N7ndCFjc7DnVjerakVQwJ5i4EnPJ9mHRM6T6lHp51LeIqLagVZ9kwxOvZq39x5dpY/b9nVA9RgFzHXrS46Rg3E+dmMBj2EwaUcNvWrqwXV81Ubrc8FvUi6oIT4C+CNc1Lud35tN/2KqOFm8SiKhaonKI6XQUDunaqzL6CJuRAOxW8llAZhTlp4xRY3OJ2RLn5nDUxx7nTev51ZpzA1RqL2dFyIC6054oX/1RuO6NW3+l/vkDcx5WxO9QYQhatv/Vpm0SsMJZKW4+evAma3yq6Rli4hXuKpgqEm6szX5u1sI2UV7n/Gha9ekPR2Jz/F1XUtTcIWzVqH3tIUCqmtzhZbj9RcP2BGcZWBd+NA+rz+P/MSom+E74Fs8+IbrPswEq25gl4+KtRi5E3TryXc6wMd/kQ8K6PwXl3RLpZFBF2lXq15mKJHo7Xv7dEhRLq006O7o9XwDHaMjzmkJ7H2p3YnsXNtL0yGAz7BwNKuA2rSTJxSCWXvvlJQDVSv8t5j7+/m2SRB6eCDHnXZdU/f8KTN38ECxdXiMhxPT1EQVAv7U13OA/ZhxbshaEptSgfPayDK2a0MbxKWS0yxHEQCL3otNVO06JIn72T3qbGjPCTKrIisLZUtK7ib69s5mNPFGfKHtPyV6paV0S2zRequn86pm2TW19XjdJDWaORyfluvzy8/o+ia1Rq/VhPa9TippM1fOGaUMLNK8WScEPCLdy8PEyismfLUphUne7TaSurUDkSVcXbHv0WY1PdfHSmpKF7jb9Z5LsCV+OcM4vPs2yK2lqF+4R6hC1G3nixXtY6S4e6fHjPckd9XD1RH08F8yt136Vacs08Fc75P5h1erAtWR24c1OlSunsIUyMm8Fg2M8YUMKtsSNLOuRrlEArlSzqvgWA9bExWEIgCtwqeVcy6T/X8r7MvVTTpToB9DZGR0B3xQjutY7kgtw1DK4IrFyeS3Z8tcvX5rdx7sQsR42SCC00MsSR0qKrcjTrJp3L+oln+m5V6PmXl3PhjtUJukJGnn9uSPiz9pMZgKkvf5evtH2p5Dhru8pbdU4dl1XFhv+lzy0V8A87FE5VMTjRepbFqUupagrqqJ1kPQtAPqEsbJYWbs2yClcKEm6ZHpphUnW9b1i+dbmyzlgxKHR7V4SsVmMWljj3NVj5MDz8dWqf+GqwfdXDwfs5ZxSfZ8WDvqEejW/6ItXnyZuC47yiuekSDV9LEX7+vVX7XsmPsOWxx6K4Bd9GIWCkLtA35XhVRmTaKXD09XDkF3o3h92B5yo1ws1gMOwnDCjhNntkLaPrg8XHy6DcxGC21MxGSNUm3pLRLMBvtgYLTYNoBiwkgpq4Wgx6WhKUxS3GzfGPsl4O5Zn695We22BJQ6USlXmiFjeEYPuII8hUjo7EuEXiyAq4a22C361Kcc9a9Sv+/itp7lqb9LNivRZZdVuf62H20CnLi653DbOww5ab8CIfXigjwq3YQlMZhyOsl9T7rYvVxu4WDrdVw1dXx5sJ3WXgFXc87aSJu2W6Cnh8/N8wZGrgllt4Kbzr4p7PyWeUmDrtp8G2gy+JBv/XjoZZHyw+145B46rotnCx3lIC0rLh2AIXbyxdbE3b8AIsUy3E/BIhVb1s+Ra57s4mJ4TmUUq4jdcW6+phxfsK3ZOWBYdfDSPm9G4OuwMrZpITDAbDfsWAEm7fPuMADpscWE46STG7VlltHGxsHIQAURCLNM8JOsZXkPF7gN60qINrZjWRjpV/jIXLZM5K8tK7b2H5/OtxyyQt5IWyyrlYfsspj2TI4iaEoG7rc9Q0FnS0BzZ2qjk5jrIe/nuzGjOt48Y8l2nD2w8XnRumm2KxkdB15cYVerzCgeme1XLkgdFA/zcfLRqvKgEpnUFqxfQYrRv8/UHChW52n59CG2lioXIgRRx6JQybrWuGabVrJ+CEbxQfO+EIGH+4nndeiana0cH+k78b7ahgxWDy0cXj9BRwf/zXistpgHLljZwHp/wAavQ1D764tCvTs8J5wi3sAu2JXbG4+ckJoXNLlZk55HIlkGd9oIfB9lIGaSlMcoLBYNjPGFDCDWDGGlWS41+OcuNcMEUJBgcby7O4uTmaBs+nvWZyUaFdFXelXKWDkpJFI2zsUJPKny/u4ifPlyhHISUnWc8QdzNIK06mcmTZhb7bUgtkmoyf3elRHVfCbWyFsgqOf/1Xqml8gXUjr8/7w1u1bO8OxqgRatFvJ42U+G7hjXJQybnEKF7wKujmkKFZJg8qEHVOSPB6C+UpPwiKufqT0y7ObSvAyVHdtYGDxBsAvpvYD4gHclO1lfKEr/N362iecOewSQ6iOrstGLMw/qpySCB+PLFiJ8sHxY+cG7y3Yiq2a8IR8O4ri4+1YkG7pzCFVh3PAjnrA/DuT5YWY57YfddFcNBH9L2U6MoBwfelU9937ajSxxUSaY3VUyZNiXlFXKWlizoz4oBi1y7gW1f3VrHdUtgJNY9SZVUMBoOhHzLghNtBr6u+9k+6swGIaQtWHgtLW9wsmQdhk49VkiBqfRuZyioXZan6shJ+0nEVP+/+dNG+Be7L/DTxQxY23b3DObYJJULqaCcnLW5dkaQ1qy5YFYfr57Zz6dRoNqxVEO8Vjm37ybLA0rPCVVadO1tncfpDNUhdZ6uSbuaLFXwj9ktqaecE61li5P2eqWHWymF8bEaeVGE6baSxuxZuFYOLBYuThY5t8OB1cN9nSD72NcZaqqCx73oNCTd5+Gfhk4thzlncUn0leWKstieQaF0DKx/SYxbMc/CU0Af9y4rp5zApWmQYYUUtMp5oufBuOPZ69f70n0ePryghdAuFmyeYeoqxC9eOO+zT8L6bAwFXhL6P9i0q2L+ilzFu4evvKCnBPyecnKDZ5cbvfSjcvMzZUoWMDQaDoR8y4ISbx6OuKj7r1SHLE1OuUkC4OVxhk08UZ78NcTbjxtKUWox+s6J8PNjx1asBlTm5I553p9MlE3wy90mWNCW5a22Sm18NxNeBDS4zh8SwQ5mPoqCtT0s23IopeP8j5zROyXyDpXI8AE5WCaQa0clfk1/iQ7GHeSH1Cf4ncROHWMtIFAg3OfYQjq3fzGFjS1hYwi5mr6ent/BPPi7Y190aJDS0b0aEMkJ9+2ZOLbSPzPkuFelKVeA1liChrZu/tHWlfi8hItydYP4FMPnY0KT1s/HitT78F7hmHbznKvVZiGhxWTtkZfWE1dyzg6xQYZUueFsY0+U/jx5KUYQtYJYNB10I1Xrsk78H8z4MZ/8+eh/5bh0H18tyIL3Nqg1TyuJWrrZdOeQ+YHHzhVsPWcIGg8HQjxhYwk1KXCxWDDqK1XIEEBS/fa0lplylXoybsMjHA+H2ldyHAbCdDJn0UL/rQZh71gWWjYMGZfn4xO1+J4OpNdEuDAD1m/9Dum1N0TgvdjawIP9r7nMXBUaWAoPSqFV/ZM4zVwcbdDBcum0NVr4rItza8qFm8ti+aLNwqRFdRe5Yzz1aSwdJEb2wqBlJKtdKQneQ4K3/BDu3r1KWjXy3yrK04oEAOP8OeO9N6n2mtTiTUhPfopIUPIvbUUedgBVyRSdjSui02PXIYXOC+CXpBi7Z+vFR8eXquYbrlqVqgjguYcFhnwn2lbNkeXOuHBLNMvWQjhpzzEKYdz7M1gkM+R6yX+0yBWtBxbqd9iOYeIS+j3zwatm9d3uWKwDdE57Y86x1098LNcN3fhxg37C4lejgYDAYDP2QgSXc8l2qDlvIAuHlFXQ4MRzXIR23sNwsUsTIJgN3WDuB5aE7PbxkfJodWp9eaEwwvd5C6MxPv8SIFnJ2voNxK25j0tJbisZpzgqGpNTxuqMUeRm9XsPGR6InSQfhZJn20reY9OpNtOaC49/uCkRmXSJw5x1ar7I0/+CUCLQHfpS4pdhVmqxVwqtbt97aHAraX/8s3PlRePDLQbX/sCuwUmdB9mD9sBtXKKHTsU3FVKWi8V5JXejNtoRy3bl5WPY3tXPSUXDpE7Dw49FBPUtVoasv7EJM1QRtrsr1//QSFmrHKFelx9CZ6vWNfyrLX904OO3HSkBCsRs3TG/Elye8dKJJINx6m2iwC//MPcH9jqxl+0DRWy/20Qg3g8GwnzCwhFuXcsmlci3MEGuBQBg5WIwUjVyLfEETAAAboUlEQVQpf48lHZ5ormdLaoJ/anj5ysdLB4/bBWvcm23BBksXTfUEnJe5Gst3aIuRZNxrv6Rhw7/IupC0o4veyvYEL24rv8hbbo6KDtWVoLJ9LV1O8YL79xM7eLruOo6zngdgirUJgBeZXnbcE+zngw+jD1YCx83D3ZcpV1ipzMbmNerVzUWFiSd2GlcXnfJq5aLgQ3erCsBP1xeJLa8AsW0J5cZzcvDKn/ReAcPnQLIgUcFvyl5gefLco55L72MPwSWPweSCGDiPE7+lYt2mHBe13n34r+rVTxrQAm+mbik28ajg2AvvhQ/9Kfjck8WtcJ6eO9jJg4jt2bZR3h837+Qa+5KrNNdDBrLBYDD0IwaUcEv+7GAAxjX9h38krwWk367Kq2t2YuufAXilvYaPPh+UhFjsTvbfu2VihgrLqr3WGlh0bKdLv6rYLREKZK9qXYGQDvXbnmfU6jtw83mSXoy+Gwz6+5WB5SwXj8bfCelQ3bQ8uFeiWXTfOqiN2ekWUq2r+UXiB4yscBik4+3eTo7nL6nT6YnvcoGKDQsLtUybWhCtHqxG4X2eoFp6Z9FhsweHvoq5Lh3HlSwSWys2K8uJlCA8i5uX7VhOcHnWTrtgnr5w07+LqqGqNEe5mLBEpYp1S9dFxUhh8oGX/DBkMly3HRZ8JNg34T0w9YTgs+iFcBMiKGsBIYvbTvzzPfHbKmaut4yc511cv74D61lfCre6MTDnLBgxd8fHGgwGQz9gQAm3/KFXs2ZYsGheZP/Dt5J5ws2jkyStBFaVbhI4Xn01UaIeF5APJRVauHQ6gjvXJGjPQWWrKsya6toE0o0kE8SyLYhQRma120xKTycbGtMr+AvFyQhC5iOZpePE5sj+U2dUIZygYO2jx6yj0lYWnFYnwZ8GfZzv5M4ueV+354/ib+nTlcUsLMRkHjq2qubhqdqS50YtbgXJHod9BiYcqd6n61VVfVDtppy8jpGLfkU3NCsB3NyZVQLLzamYtGGzVRxWKUYdpF4Ly2xYBRa3XSV871OOh7Ghzgp2LJr4UEhPojdMLBW0unLzypW5M4Jo0aUqZq63VOoECe8au/SMvHP6ULjVj4cP/gKmHt93czAYDIbdyIASbs7Bl7Jp0AL/81HWYpI2jK/MEy8o+6E6BgQLTk7GELrrgFumvMN4ud5//0LyUp7cmua3K1P88y0LO68sRcJ1sNxcEHcFWE42IsTqZTMJWyKQEYtbwoamjGBNuxUReqBcpSKUWTlHrGYYjQD8YFGnysbMBcItkW0lrRMP2vIxKhIxbnVClqCQheK/8xdR4bVs8CrlA2Q6oH2zil0rrNXmTywkTAprraXr4Lw/wXFfhaOvg4apavtDN6hxS4iak+eEAuRjKSVivKSAciLo/TfDObcXt6ry3JS7WlV/wUWqYXv4umf9tmehVkhvEwfqxyuRDEqs9sbF+k7wv+PvQLgNP0C91k/cLVMyGAwGwwATbqBrtGmec6djCbhxUQczKqPBy11EF9TPTd2It4i5ltpX3bSMeU9cSrLjbQDmpBv94+tFMF5nTvqN4oXMg5QRV6nlZiP9Uce764hbqpfpus5ggXal4PoXK7jy6SqE67B96CFsHPs+Pa6LFSrH8f3Ez3gmdTnfW9jJqdMqVUxYPtQiqquRiTnVLL4lH6ciYZNBCQ6ZqI70k3SxSHs+5ZHz4VBdRqO7WSUaJKth1mkUMfvMAldpgcUrllZWs0M/BcNmRC1ymdaS9c/OXzgOAEdKVWrEyenG8D18leNpmH5yceybZw3cVeH23h8E7sePPqDi3+K9LNHhUfhMyjFsphKzrqMtbjshDneGy5+H8+4IFS/2nusuCLepJ6hkkSM+s+NjDQaDwdArBpxws0PuxLlVSmgJIZiUjmY6dhBdgKcOrWDbSBVkPnrV7TSsu5/6raoJev3WZwBoSEWtYB55Gbg2hetw+bP1vN4Yahbv5iIWtANYQaLgNxO3JI6ELV0WIEE6ZBOD2D7iCD1uHuFm/XZZHmeM61SiDaLC7dmfc3DnY4ByA1cmbRxsPp+7mPwpNxW5Pk+YFbJ0HaDrmTW/pcaMp5Xb06s3BqrrwKkFGbOJgsbthdX2qwvKTVjFVqUKXU4l70jVIqq7VWUM9tblGOadiBJ/DP1sxy5U8W87S6GYLMeQaSqTt6tJu5H3kMVtyBSVfOHxThMghs/pvTg1GAwGww4ZcMLt8W3BIjK3Jqimvm3McciQa7RJRhcb107xz5oz2dqwiGS2iZFr7/bFWMPbjwIg3dKWmxcaU0EnAzfPW51x/vxmsPB2ZPLUNC31P49lEwkrKiZSNjhSMKHawcbFQiLtmF9PTsW45XnbKSiSuuX14H3LekqRJUZlIsa5B49h86SziB3wQRh1oL9/1Q1HcfHhIXdXzUj1mmlVwi1RqQTMjPfC8V9X++x4cfmNwpiswgKyhcKthMsxpcuBxCwBw2cDUln9elvTLHJ9bVV1eyjXsafpbXFcT0hn2vasxa0Qr61WZS8b2hsMBoNhjzLghNudG4PCqYlMk/++o3YqL737R/7n7TIaSL+qPcl1i6vY0Kwsdh01k3z3pu1miHdtwSpIGPBY3xX3i9raOICkOhZY2FY35xmzMrBWxciTjEnmh9bKpK0sd+054cfjSSuB1JaXRzYlaOzM00yBBefpH/tlUGiPJix4SCyqUjG++YED+MWFC1RT95CgsG2beKgIrh/kn+tSHRLCPSw9EdRTmyf/RguEW6oWDr4k+FxijHGDKpkxoppPHDkpWgR3VyxQ3rzzfdnHspeB+96zanxTlR3Zldpsu8LM0+C0/4Ejr9k71zMYDAZDjww44WaHmqZXt74RjW+ybJqGqOSFJpQ48Zqvb88oi06r4wW0y4h7c9YL11PZsTZyLS+ZAVSWqUeCPGkrmMfx3ff7710ESXKMdjdz0+C/4rnxEjZ0O4L1nbbfP9Wx4jRVTlLz3LSZTe0O3ZQQTNu01S2fKWupqdIuyIhAe/enYOLRxdYsO6asad26fVfYBVo9Qr+OLHkdrngZ0rqwcdh163FUEFtXSoylEzb3feowPnHk5GiHg11x6Xmu2p46G+wpvKSE3maGekL6uV+o171Vl0wImHdOUJvOYDAYDH3KHk5N2/eIEbWK2flOnHhgpXplwkf53PoLyepA/WMy32N+VQujO5TFI5NzwAYpHXK5qIvtaGtJ5HOSHN06ycHGpVvGSYkccfLE86V7lnbIFElyXNx6C1VbNjKcw9nEYGoTkuVNak7DhLIUZknwkbu3szyZYJhoZJBoY50MzHSZkQtJvv0MdOkuB05GxRt1BUkUT7szgGgrLp/jv6riqUplMCaqgizHylDfzgPOViJq/OEl74/6cXD27+DPF5bORA1b78qIEyGEKuNSPUxdS7q7FuMW14LT6QOL2xUvwfrnypdRKaTQOnnQR3f/nAwGg8GwzzOgLG55V2JpC1a3rcVaKJSsOStY2RZnE8qSUx2XdJJiq6hnbbsSBl4LqA2dNm0tgQACikqKxH2RKLGF9DNV51qr+A7Fra4A2klTY2eptNRYh9Vt5ZsHtTEkGUx2rqVqwn159XRAsJ0aFlrLmW6tY6UcFVz/1B+qN21v6weQUbFKp/4Yxr4bgDscJbA6sqXdvGXLTiSroXWDej9ofLBdCDjgrJ77Wo4/FD79WlBfLXK9kMVwR43Bk9XBGLviKvUsdr0VT7uTmhEw8/29Lx1SKNxmnbr752QwGAyGfZ4BZXHryOR9i9ub+SHMFO1+PTVXwkceDxISfndslic3J7j31c0skmtZnD+QRxJXMcFScWI5x2WYiAqLmoLPnpCztZu0iwT1wP8lvlF2ju0yTa1oRsSU5ek7M99CTJ3BIa9dSyrZwmPOXNpRQf8vdyqX42ixjdFCtVvaIIO4L6tKW8LeuB8OvFAJt3Q9zD9ftZ166ykWTWogXzGS988t49osR7IG8m8qobUrVenLCUIh4JJH4edHqi4DO2LMQmW52pU6Y0Mmw/tuhoZpO39uXzL5uN4nNRgMBoNhv2JACbc/v7jRj3FrkykQsLLZZcQQSHVtJkmKoaKJ9bKBhrTFZw4UfH7FVZCH55zZvmgDqLFzJHTz8E0MYQiNDBPNket5wi3mX7MCRNRKV8g62cAUdwMI1VpKvHgrLL2T8U4bCDg79iigarq1UcG8MbWwNTj/KXcWT5z0AO+p2VrcniqfCSw3R3we6sdzxrSTOKMyFOTfW1I6eaNuHAyZuvPn98TI+XD1670rI5HSWbS7WovtoAt37by9TT7kNv7gL41wMxgMhgHKgBJuK7Z2EtPWL9UZAb7ySj0jKiT3uV/ida1p1rpDGbThGOzUIf6575KvRsayZZ4cMSDDZ+PX8NtccZHRuMiDDBIT7nEWMc26o+z83pP5IZfbumF5uHRHpq3o2DbSSCyG1aR84XZ65gbelCOpHTUNRhd0Cbj3KuV6HK1di7EEHPjhsnPZIV6x3Mohe0ZEFJYGKYfn5uyLOLW+orDMisFgMBgGDAMqxi2bdxmRVJmM9dUqMD1BniNy/44cN87aQvWy2+HB68uOZeGSJsNP8u/n322l3Yzn2/9iktjgi8WTp1aRl9FHfmn2Sv/9etnANnoXb9UeU25SAarYLbBYTgagJh2Km/rEf9SrFy82+8xejb9DPOHW18VVPeHWF5mhe5OpJ6leox+511jbDAaDYQAzoIRbd94lKZTbcs4Y5Ub8W/I6jrFfKnNCc8nNbaKKetlMUuTpkMpM97gzp+i4S2P38FDys1Si3FwVCUtb6QIOnh11M96SPx3pld9omF72XhztIqyrTMC5t8PHHuI7p89mwpAKkrHQr3XojOD9mbfBtJPKjrlT1KvWU2Taez5uT+MJx/1duNkx1V5rfC/i/gwGg8Gw3zKghFsm75ISOmEgo8pxDBdNLGApGytncFjmRqZ13xqcUNiiSfOIWEgaJRQ26Tpvn89dUvJYgKdTnwRgTG2Ch0ZdyvpQAsFHjw0yK6cMrSRDgtzQ2WpDzSi4+LHIWHlbucmGT5rLNSdN41NHT1HzHL2AsxaO54GrjlDuU49wnbBJRxe3mdpV5p2nXnclMWF34t2Ps58LN4PBYDAYGGAxbpmcQ9JywAXGLoI1gYu0MrOFdXJY9IRshyoZ0bkdgPxR1/GrVx3yG1+FGLTKCp5KHwkdLp0Uu69aZQU1ImirZVkx3nvJV1nw1cN43tEuy2QVjH4X2AluPX0hr21sJfasDrhP1cKoeTDtZFj1MN2Xv0zMssDtIpGs5tJw8oEmUkDX44qX4O2XygrRXaJuDPz3FpCl+7PuNRK6rMv+bnEzGAwGg4EBaHFLaosbw+bA1W/4+17IBJXhz8l+MThJizaA2NiFzD3pY6yWqjuAZdvcd9WR6rCCpvQA7aRYNyrkmrSVC1QiOCHzLV6YfLnK/PzYv+C8OxhVl+aYGcOwPIHl1Rk793a4+g1SdcOI1TRA3dhoxuiOqB+v6n7tSpHanognd68Y3BW86xuLm8FgMBgGAPuccBNCnCiEeF0IsVIIsVsbJHbnXRJCl42wY6ryvuaK3GX++6fdmbijFgQnTjgCrt0AYw9hSFWCZ1wVe5YcMoH6qjTHzhhKjhjPjolWs8/IONsmnh66OWXgdKXkdTmW9bP/XyA8wi5ML7YtLIrSfVAktj9Qp2PtZp7Wt/MwGAwGg2EvsE+5SoUQNvBj4DhgPfCcEOJuKeWy3TF+Ju+S8nqEFlTaby1ozp498/9I3aQTB+KVyqUJjKxLs04O45z4Tdx6xhHEgS+cPIPpw2uYethxcOMfIacyOJfKCYxKhMbVtbhcXSs2Xq5R+JHXKjepESM7JlEB1zcFze0NBoPBYNiP2aeEG3AwsFJK+SaAEOIPwKnAbhFut6W+z8iWxeqDJ9zedzNy+yqeOvho7nnpbb7xj9fU7qoGmHI8rHgAphzrj1GRiPHAlYfRmXNIDVXuyokNVXzmBF19XxeC/deoy/jMqgX8raYumICrROP04dU8s7qRVLyM6zKWgPdcWXqfoRjLAsuUyDAYDAbD/s++JtxGAetCn9cDC8scu3NIycRhddCkkwW8GLGDLkQAI4GZIwN3pBDAeX9WrZQKqvJPHV5T/jrvvxnuv4ZjPnART6fHUB1zYeWZymp3xOcA+OE58/n7Sxs4cGxd+XEMBoPBYDAYCtjXhJsosS3ShFIIcQlwCcDYsWN3YmQBZ/8e/nY5bHsdBk0sOmRojbLaVCZtLK+MhhAgdiKo/4CzYNbpCCtGnTfGB38ZOWR4bYqLD5/U+zENBoPBYDAY2PeE23pgTOjzaODt8AFSyp8DPwdYsGDBznUWFwJO+7FyWZbIsJw6rJqHrz6CXN7FtkppyF5ix3d8jMFgMBgMBsNOsq8Jt+eAKUKICcAG4BzgQ7v9Kj2UxZjYUFV2n8FgMBgMBkNfsk8JNyllXghxOfBPwAZ+LaVc2sfTMhgMBoPBYNgn2KeEG4CU8j7gvr6eh8FgMBgMBsO+xj5XgNdgMBgMBoPBUBoj3AwGg8FgMBj6CUa4GQwGg8FgMPQTjHAzGAwGg8Fg6CcY4WYwGAwGg8HQTzDCzWAwGAwGg6GfYISbwWAwGAwGQz/BCDeDwWAwGAyGfoKQcufafe5LCCG2Amt38rQhwLY9MJ13ipnXzmHmtXOYee0c46SUDX09CYPBYCikXwu3XUEI8byUckFfz6MQM6+dw8xr5zDzMhgMhv0D4yo1GAwGg8Fg6CcY4WYwGAwGg8HQTxiIwu3nfT2BMph57RxmXjuHmZfBYDDsBwy4GDeDwWAwGAyG/spAtLgZDAaDwWAw9EsGjHATQpwohHhdCLFSCHFNH1z/10KILUKIV0PbviyE2CCEWKJ/Tg7tu1bP9XUhxAl7aE4pIcSzQoiXhBBLhRA36O0ThBDPCCFWCCH+KIRI6O1J/Xml3j9+T8wrND9bCLFYCHGP/nyrEGJ16HnN09uFEOJmPa+XhRAH7uF51Qkh7hBCvCaEWC6EOEQIMUgI8aB+Zg8KIer35tyEENNCz2WJEKJVCHFlX3/H9HWuEEK8qr9jV+ptffq8DAaDob8yIISbEMIGfgycBMwEzhVCzNzL07gVOLHE9hullPP0z30Aem7nALP0OT/R97C7yQBHSynnAvOAE4UQi4Bv63lNAZqAi/TxFwFNUsrJwI36uD3JFcDygm2fDT2vJXrbScAU/XMJ8NM9PK8fAvdLKacDc/UcrwEe0s/sIf15r81NSvm691yAg4BO4K96d599x4QQs4GLgYNRz+q9Qogp9PHzMhgMhv7KgBBuqEVjpZTyTSllFvgDcOrenICU8nGgsZeHnwr8QUqZkVKuBlai7mF3z0lKKdv1x7j+kcDRwB16+23AaaF53abf3wEcI4QQu3teAEKI0cApwC97cfipwP/q+3kaqBNCjNhD86oBDgd+BSClzEopm4k+m8JntlfmFuIYYJWUsqfi1HvlOwbMAJ6WUnZKKfPAY8Dp7FvPy2AwGPoNA0W4jQLWhT6v19v2BS7XLqFfe+4i9uJ8tTtyCbAFeBBYBTTrRbbw2v689P4WYPCemBdwE/A5wC3Y/nX9vG4UQiQL51VizrubicBW4DfajftLIUQlMExKuRFAvw7tg7l5nAPcHvrcl9+xV4HDhRCDhRAVwMnAGPat52UwGAz9hoEi3EpZhfaFdNqfApNQbsqNwPf19r02Xymlo91ro1EWlxk9XHuvzEsI8V5gi5TyhYJd1wLTgXcBg4DP7815aWLAgcBPpZTzgQ4CN18p9up3T8cjvh/4s97Up98xKeVylEv9QeB+4CUg38Mp++q/VYPBYNgnGCjCbT3qr3yP0cDbfTQXHynlZi2cXOAXBK6qvT5f7e57FFiEck/FSlzbn5feX0vv3b87w6HA+4UQa1Bu7aOFEL+TUm7ULrQM8Bv65nmtB9ZLKZ/Rn+9ACbnNnktPv27pg7mBihF7UUq5GfaN75iU8ldSygOllIejvi8r2Heel8FgMPQrBopwew6YorMlEyhX0t19PCcKYndOR7mVQM3tHJ3FOQEVqP3sHrh+gxCiTr9PA8eiAu0fAc7Qh10I/C00rwv1+zOAh+UeKAQopbxWSjlaSjke9bt6WEp5fmihF6iYqPDzukBnJC4CWjw33B6Y2yZgnRBimt50DLCM6LMpfGZ7ZW6acwm5Sfv6O6bnMFS/jgU+oOe3rzwvg8Fg6FfEdnxI/0dKmRdCXA78E7CBX0spl+7NOQghbgeOBIYIIdYDXwKOFKqkhQTWAB/X810qhPgTShDkgcuklM4emNYI4DadTWgBf5JS3iOEWAb8QQjxNWAxOhBfv/5WCLESZTk5Zw/MqSd+L4RoQLnTlgCX6u33oWKnVqKyKf9rD8/jk3ouCeBNfT0L+JMQ4iLgLeDMvT03HUN2HPp7pPlOH3/HAO4UQgwGcvo6TUKIb9HHz8tgMBj6I6ZzgsFgMBgMBkM/YaC4Sg0Gg8FgMBj6PUa4GQwGg8FgMPQTjHAzGAwGg8Fg6CcY4WYwGAwGg8HQTzDCzWAwGAwGg6GfYISbYZ9ECOEIIZaEfnrqToAQ4lIhxAW74bprhBBD3uk4BoPBYDDsCUw5EMM+iRCiXUpZ1QfXXQMskFJu29vXNhgMBoNhRxiLm6FfoS1i3xZCPKt/JuvtXxZCfEa//5QQYplurP4HvW2QEOIuve1pIcQBevtgIcQDumH8/xDqlSmEOF9fY4kQ4n+EELb+uVUI8aoQ4hUhxFV98BgMBoPBMEAxws2wr5IucJWeHdrXKqU8GPgRcFOJc68B5kspDyDornADsFhv+wLwv3r7l4AndMP4u4GxAEKIGcDZwKFSynmAA5yHatY+Sko5W0o5B9Uz1WAwGAyGvcKAaHll6Jd0acFUittDrzeW2P8yqiXVXcBdett7gA8CSCkf1pa2WuBwVP9MpJT3CiGa9PHHAAcBz6nWqKRRjdD/DkwUQtwC3As8sOu3aDAYDAbDzmEsbob+iCzz3uMU4Mco4fWCECJGyAVa4txSYwjgNinlPP0zTUr5ZSllEzAXeBS4DPjlLt6DwWAwGAw7jRFuhv7I2aHX/4R3CCEsYIyU8hHgc0AdUAU8jnJ1IoQ4EtgmpWwt2H4SUK+Hegg4QwgxVO8bJIQYpzNOLSnlncB1wIF76iYNBoPBYCjEuEoN+yppIcSS0Of7pZReSZCkEOIZ1B8e5xacZwO/025QAdwopWwWQnwZ+I0Q4mWgE7hQH38DcLsQ4kXgMeAtACnlMiHEF4EHtBjMoSxsXXoc74+ea3ffLRsMBoPB0DOmHIihX2HKdRgMBoNhIGNcpQaDwWAwGAz9BGNxMxgMBoPBYOgnGIubwWAwGAwGQz/BCDeDwWAwGAyGfoIRbgaDwWAwGAz9BCPcDAaDwWAwGPoJRrgZDAaDwWAw9BOMcDMYDAaDwWDoJ/x/eZCXcxAmV5oAAAAASUVORK5CYII=\n", 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" ] @@ -286,18 +945,68 @@ "per_group_interp.add_interpretation(\n", " GroupAgentInterpretation.from_pickle('data/lunarlander_dqn', 'dqn_PriorityExperienceReplay_FEED_TYPE_STATE')\n", ")\n", - "per_group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" + "per_group_interp.plot_reward_bounds(per_episode=True, 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"nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/docs_src/rl.agents.dqnfixedtarget.ipynb b/docs_src/rl.agents.dqnfixedtarget.ipynb index c8141be..86e4b48 100644 --- a/docs_src/rl.agents.dqnfixedtarget.ipynb +++ b/docs_src/rl.agents.dqnfixedtarget.ipynb @@ -2,39 +2,28 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "current_dir=/home/josiah/anaconda3/envs/master37/lib/python3.7/site-packages/pybullet_envs/bullet\n", - "pygame 1.9.6\n", - "Hello from the pygame community. https://www.pygame.org/contribute.html\n" - ] - } - ], + "outputs": [], "source": [ - "from fast_rl.core.basic_train import AgentLearner\n", - "from fast_rl.agents.dqn import create_dqn_model, dqn_learner, DQNLearner\n", + "from fast_rl.agents.dqn import create_dqn_model, dqn_learner\n", "from fast_rl.agents.dqn_models import *\n", - "from fast_rl.core.train import AgentInterpretation, GroupAgentInterpretation\n", + "from fast_rl.agents.dqn import *\n", + "from fast_rl.core.agent_core import ExperienceReplay, PriorityExperienceReplay, GreedyEpsilon\n", "from fast_rl.core.data_block import MDPDataBunch\n", - "from fast_rl.core.agent_core import ExperienceReplay, GreedyEpsilon\n", - "from fastai.basic_data import DatasetType\n", - "from fast_rl.agents.dqn_models import *\n", - "from fast_rl.core.metrics import *\n", - "from fastai.gen_doc.nbdoc import *" + "from fast_rl.core.metrics import RewardMetric, EpsilonMetric\n", + "from fastai.gen_doc.nbdoc import show_doc\n", + "from fast_rl.core.train import GroupAgentInterpretation, AgentInterpretation\n", + "from fastai.basic_data import DatasetType" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": { "pycharm": { "is_executing": false @@ -51,12 +40,12 @@ "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", "\n", "Basic DQN Module. Args:\n", - " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", - " ao: Number of actions to output.\n", - " layers: Number of layers where is determined per element.\n", - " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", - " to the head on top of existing linear layers.\n", - " nc: Number of channels that will be expected by the convolutional blocks. " + " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", + " ao: Number of actions to output.\n", + " layers: Number of layers where is determined per element.\n", + " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", + " to the head on top of existing linear layers.\n", + " nc: Number of channels that will be expected by the convolutional blocks. " ], "text/plain": [ "" @@ -72,7 +61,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": { "pycharm": { "is_executing": false @@ -104,7 +93,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "metadata": { "pycharm": { "is_executing": false @@ -138,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "metadata": { "pycharm": { "is_executing": false @@ -148,24 +137,78 @@ { "data": { "text/html": [ - "\n", - "
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\n", + "image/png": 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\n", 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" ] @@ -216,7 +259,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 10, "metadata": { "pycharm": { "is_executing": false @@ -225,7 +268,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -244,12 +287,12 @@ " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" + "group_interp.plot_reward_bounds(per_episode=True, show_average=True, hide_edges=True,smooth_groups=10)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": { "pycharm": { "is_executing": false @@ -288,161 +331,161 @@ " \n", " 0\n", " (DQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 27.895787\n", - " 48.7\n", - " 8.0\n", + " 235.886444\n", + " 499.0\n", + " 10.8\n", " reward\n", " \n", " \n", " 1\n", " (DQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 27.521729\n", - " 46.8\n", - " 10.9\n", + " 209.443111\n", + " 446.1\n", + " 10.0\n", " reward\n", " \n", " \n", " 2\n", " (DQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 29.128825\n", - " 44.0\n", - " 16.9\n", + " 272.512667\n", + " 495.9\n", + " 11.5\n", " reward\n", " \n", " \n", " 3\n", " (DQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 26.520843\n", - " 52.3\n", - " 10.7\n", + " 246.301111\n", + " 431.1\n", + " 10.1\n", " reward\n", " \n", " \n", " 4\n", " (DQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 27.778936\n", - " 49.2\n", - " 13.2\n", + " 200.820667\n", + " 493.3\n", + " 14.0\n", " reward\n", " \n", " \n", " 5\n", " (DQN, PriorityExperienceReplay_FEED_TYPE_STATE...\n", - " 25.197561\n", - " 36.8\n", - " 12.0\n", + " 139.946889\n", + " 486.1\n", + " 13.9\n", " reward\n", " \n", " \n", " 6\n", " (DQN, PriorityExperienceReplay_FEED_TYPE_STATE...\n", - " 22.827716\n", - " 38.0\n", - " 9.1\n", + " 171.786000\n", + " 497.3\n", + " 12.0\n", " reward\n", " \n", " \n", " 7\n", " (DQN, PriorityExperienceReplay_FEED_TYPE_STATE...\n", - " 24.578271\n", - " 51.9\n", - " 13.7\n", + " 128.038444\n", + " 452.6\n", + " 12.5\n", " reward\n", " \n", " \n", " 8\n", " (DQN, PriorityExperienceReplay_FEED_TYPE_STATE...\n", - " 22.751663\n", - " 36.8\n", - " 8.8\n", + " 71.668667\n", + " 198.4\n", + " 12.2\n", " reward\n", " \n", " \n", " 9\n", " (DQN, PriorityExperienceReplay_FEED_TYPE_STATE...\n", - " 26.039690\n", - " 46.8\n", - " 9.3\n", + " 105.985778\n", + " 337.0\n", + " 8.5\n", " reward\n", " \n", " \n", " 10\n", - " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", - " 148.154989\n", - " 499.0\n", - " 10.6\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 29.125333\n", + " 81.6\n", + " 7.2\n", " reward\n", " \n", " \n", " 11\n", - " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", - " 141.317738\n", - " 285.8\n", - " 14.1\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 52.764745\n", + " 166.8\n", + " 9.6\n", " reward\n", " \n", " \n", " 12\n", - " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", - " 229.873836\n", - " 496.0\n", - " 9.8\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.286918\n", + " 47.8\n", + " 5.9\n", " reward\n", " \n", " \n", " 13\n", - " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", - " 149.444346\n", - " 483.9\n", - " 13.5\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.516186\n", + " 119.8\n", + " 8.3\n", " reward\n", " \n", " \n", " 14\n", - " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", - " 137.559645\n", - " 499.0\n", - " 10.4\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.339468\n", + " 218.5\n", + " 8.4\n", " reward\n", " \n", " \n", " 15\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 29.125333\n", - " 81.6\n", - " 7.2\n", + " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", + " 148.154989\n", + " 499.0\n", + " 10.6\n", " reward\n", " \n", " \n", " 16\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 52.764745\n", - " 166.8\n", - " 9.6\n", + " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", + " 141.317738\n", + " 285.8\n", + " 14.1\n", " reward\n", " \n", " \n", " 17\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.286918\n", - " 47.8\n", - " 5.9\n", + " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", + " 229.873836\n", + " 496.0\n", + " 9.8\n", " reward\n", " \n", " \n", " 18\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.516186\n", - " 119.8\n", - " 8.3\n", + " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", + " 149.444346\n", + " 483.9\n", + " 13.5\n", " reward\n", " \n", " \n", " 19\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.339468\n", - " 218.5\n", - " 8.4\n", + " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", + " 137.559645\n", + " 499.0\n", + " 10.4\n", " reward\n", " \n", " \n", @@ -451,51 +494,51 @@ ], "text/plain": [ " name average max \\\n", - "0 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 27.895787 48.7 \n", - "1 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 27.521729 46.8 \n", - "2 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 29.128825 44.0 \n", - "3 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 26.520843 52.3 \n", - "4 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 27.778936 49.2 \n", - "5 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 25.197561 36.8 \n", - "6 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 22.827716 38.0 \n", - "7 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 24.578271 51.9 \n", - "8 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 22.751663 36.8 \n", - "9 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 26.039690 46.8 \n", - "10 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 148.154989 499.0 \n", - "11 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 141.317738 285.8 \n", - "12 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 229.873836 496.0 \n", - "13 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 149.444346 483.9 \n", - "14 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 137.559645 499.0 \n", - "15 (DQN Fixed Targeting, PriorityExperienceReplay... 29.125333 81.6 \n", - "16 (DQN Fixed Targeting, PriorityExperienceReplay... 52.764745 166.8 \n", - "17 (DQN Fixed Targeting, PriorityExperienceReplay... 16.286918 47.8 \n", - "18 (DQN Fixed Targeting, PriorityExperienceReplay... 16.516186 119.8 \n", - "19 (DQN Fixed Targeting, PriorityExperienceReplay... 16.339468 218.5 \n", + "0 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 235.886444 499.0 \n", + "1 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 209.443111 446.1 \n", + "2 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 272.512667 495.9 \n", + "3 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 246.301111 431.1 \n", + "4 (DQN, ExperienceReplay_FEED_TYPE_STATE, reward) 200.820667 493.3 \n", + "5 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 139.946889 486.1 \n", + "6 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 171.786000 497.3 \n", + "7 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 128.038444 452.6 \n", + "8 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 71.668667 198.4 \n", + "9 (DQN, PriorityExperienceReplay_FEED_TYPE_STATE... 105.985778 337.0 \n", + "10 (DQN Fixed Targeting, PriorityExperienceReplay... 29.125333 81.6 \n", + "11 (DQN Fixed Targeting, PriorityExperienceReplay... 52.764745 166.8 \n", + "12 (DQN Fixed Targeting, PriorityExperienceReplay... 16.286918 47.8 \n", + "13 (DQN Fixed Targeting, PriorityExperienceReplay... 16.516186 119.8 \n", + "14 (DQN Fixed Targeting, PriorityExperienceReplay... 16.339468 218.5 \n", + "15 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 148.154989 499.0 \n", + "16 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 141.317738 285.8 \n", + "17 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 229.873836 496.0 \n", + "18 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 149.444346 483.9 \n", + "19 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 137.559645 499.0 \n", "\n", " min type \n", - "0 8.0 reward \n", - "1 10.9 reward \n", - "2 16.9 reward \n", - "3 10.7 reward \n", - "4 13.2 reward \n", - "5 12.0 reward \n", - "6 9.1 reward \n", - "7 13.7 reward \n", - "8 8.8 reward \n", - "9 9.3 reward \n", - "10 10.6 reward \n", - "11 14.1 reward \n", - "12 9.8 reward \n", - "13 13.5 reward \n", - "14 10.4 reward \n", - "15 7.2 reward \n", - "16 9.6 reward \n", - "17 5.9 reward \n", - "18 8.3 reward \n", - "19 8.4 reward " + "0 10.8 reward \n", + "1 10.0 reward \n", + "2 11.5 reward \n", + "3 10.1 reward \n", + "4 14.0 reward \n", + "5 13.9 reward \n", + "6 12.0 reward \n", + "7 12.5 reward \n", + "8 12.2 reward \n", + "9 8.5 reward \n", + "10 7.2 reward \n", + "11 9.6 reward \n", + "12 5.9 reward \n", + "13 8.3 reward \n", + "14 8.4 reward \n", + "15 10.6 reward \n", + "16 14.1 reward \n", + "17 9.8 reward \n", + "18 13.5 reward \n", + "19 10.4 reward " ] }, - "execution_count": 7, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -506,7 +549,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 13, "metadata": { "pycharm": { "is_executing": true @@ -515,7 +558,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -535,13 +578,6 @@ " group_interp.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", "group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -560,7 +596,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/environment.yaml b/environment.yaml index 54be5b0..33c034f 100644 --- a/environment.yaml +++ b/environment.yaml @@ -4,12 +4,13 @@ channels: - pytorch - fastai dependencies: - - python=3.7 + - python=3.6 - pip - cuda100 - fastprogress - fastai=1.0.58 - jupyter + - notebook - setuptools - pip: - pytest @@ -22,5 +23,7 @@ dependencies: - requests - sklearn - cython + - gym[box2d, atari] - easydict - - matplotlib \ No newline at end of file + - matplotlib + - jupyter_console \ No newline at end of file diff --git a/fast_rl/agents/dqn.py b/fast_rl/agents/dqn.py index b5857c7..04a5afa 100644 --- a/fast_rl/agents/dqn.py +++ b/fast_rl/agents/dqn.py @@ -21,7 +21,7 @@ def predict(self, element, **kwargs): if element.shape[0] == 1: self.model.eval() pred = self.model(element) if training: self.model.train() - return self.exploration_method.perturb(torch.argmax(pred, axis=1), self.data.action.action_space) + return self.exploration_method.perturb(torch.argmax(pred, 1), self.data.action.action_space) def interpret_q(self, item): with torch.no_grad(): diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index 52b7ebe..419a675 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -205,15 +205,15 @@ def update(self, item, **kwargs): self.tree.add(np.abs(maximal_priority)+self.epsilon, item) -class HindsightExperienceReplay(Experience): - def __init__(self, memory_size): - """ - - References: - [1] Andrychowicz, Marcin, et al. "Hindsight experience replay." - Advances in Neural Information Processing Systems. 2017. - - Args: - memory_size: - """ - super().__init__(memory_size) +# class HindsightExperienceReplay(Experience): +# def __init__(self, memory_size): +# """ +# +# References: +# [1] Andrychowicz, Marcin, et al. "Hindsight experience replay." +# Advances in Neural Information Processing Systems. 2017. +# +# Args: +# memory_size: +# """ +# super().__init__(memory_size) From 8e5a7d05c3a272f296a4cae534ee970b6b9b8b39 Mon Sep 17 00:00:00 2001 From: Josiah Laivins Date: Sun, 2 Feb 2020 12:01:46 -0500 Subject: [PATCH 02/29] Added: - fixed target lunar lander --- ... dqn_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 30411 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 15336 bytes 2 files changed, 0 insertions(+), 0 deletions(-) create mode 100644 docs_src/data/lunarlander_fixed target dqn/fixed target dqn_ExperienceReplay_FEED_TYPE_STATE.pickle create mode 100644 docs_src/data/lunarlander_fixed target dqn/fixed target dqn_PriorityExperienceReplay_FEED_TYPE_STATE.pickle diff --git a/docs_src/data/lunarlander_fixed target dqn/fixed target dqn_ExperienceReplay_FEED_TYPE_STATE.pickle b/docs_src/data/lunarlander_fixed target dqn/fixed target dqn_ExperienceReplay_FEED_TYPE_STATE.pickle new file mode 100644 index 0000000000000000000000000000000000000000..26563904b7eeb6c31a16f93b82ae4f3115acc8e0 GIT binary patch literal 30411 zcma)lX)snga#$4bP|z}A}LeRM5R(msuPv5G#X1IWyq8eDT#6$DkV`! zC^AJMLYjH}&i~DIy?f4!&gVMUT5GR8t-bdC?tPzaA_oP5LjU~}EA8gI(cjU}OKZ(~ zKUXb(KW7i0_*nUQe(M8#XRUSh@t^PG@9O94=j!k5@3Gz|J}zEudwgiTYOLtm|A}mj zw~tqK7m5}8PhqZytCtIi1Uh>Kxc(;+E9Vp7?Yrs!3h@r`^7nA|^K;%5A1k_XjkA}t z-(RKJe*cO5{kMz%CSTY8{TE?3-FOQji#`$Y*72$qePjC=#amihn*aIx&wqa`g#6=I z&lX89nRz3A*Iya;A?|XsMMlNQ2mmVY7&Z&w%HHV>7L<`X7j=)6 zJU}R65RIm!U&thvu7fEA5mvv?!v|Yatg5N2lPs2YhPqDx`!jXv-AL#E9OYmzZg6mb;H(OL){6v@(8Oll(17= zb7`jR8E=F>4}3KN%MCN{D}X-QcDx8#qhsVo*T7w9D!0%8-6&lpj;#EOWURtz%^wIg zZ;GJLw+}a>Zd%YNWJ?~Zp_9c?;V8V-;{y8Z<+1~N|H%Ob)UD{#i$15y{y^R9KKsz} z`ay1grs(8kk40F}rbaWgEc7GF2rR2vxufnE93pD1T@aIn#vD}XV)+p@tZvn#L83VAbuIpE# z?roiO2t`AE(T%5>WoRm=ApzNadOMI^mUsdqe{25*0%%yzsCy`!t#BQ^at;`aY{jr_ ztnZhmTPQqZ;!gCr&MyMJN*ri}y7v?7QP=1GEG+1XEiKkBJ6!Cj>7H9!;wuhG{Xv>oAn&ovsWUqVM7*D29@XY2id|2C8)b6v=S}_U#YK~n7!m||=%;!~}MD}NH2%4IpPd&IVF9oZ=Zj2bh(eY&2R&$^+G`mz} z1QwLE&Q1WV@&0r))v<3Oy3sRI23zCfwp}=KDh|Ct=#Z|ArY=aWM%^oV2T?ezUKzbA z6`>W!rtvMB8lJiug|+7wB7CzV1AT6~G!I$vvPy)roVBoV%;yY2cK7q0=<~xR%h0lF zt}6;#)j zA3PUEUD;wv)YEz>{W$q29V=LTE*asxi@(s+@#DeB?vw0;^{wmvf?iD>nS)+Ua-pda zW+IQ44ZbR)<@Sb1WPc7W!N#d_X++DNQk^J#Hn$H7*BQ)5;m?!rVgEK2(P(dzq-0FC zCmt=^3Y(#+@(H#Ge@&!toh^R?Yb2tx9Zj|7XCvzq{0iCR0W|pU_8pA{ea{+%u+rZP z>)X2Q5}Nu~Z~zNhd1n@~^)U;uHNLm56u^l65hjJYQM+lS>$%?t-4J{@jlwbq>an1A zox>3(rifudYOhjIch#qOv|RFWFeX$oGjAaKYoI2=)8Q%zLp2l;c3H+CtiHDs%eB5e z9-VyFritu=jpI<)PV^nJ8r}5>=bx)WVL6kLXgMQoFS4Q6HIUs|orj&`ebpV=YOfDi zkW|DgG!-Lu2w5Y2+Dl4IqiyLqP1;N9=zT&{X%9@WT-^{=gz|dU2$gd;qwdNeTAm(7 zP;5WDWDyEWxbn|YowqmnCODS-@nX3QzNb~ML4O-6HNsT zq12_xbT+aH(t~l9CA#Y(tCK5(mWNdLK~}7glF!O63Q)@T4x(j!&kXGScP6wi8(v6Z z#Jtu8%Z-fjKo~Jz2;DdzGZ)$L&MFMo`rG@XaQSQ{Y{^&JvB;YBrz0BKSHIEnu@$-q zx0ZcC7#$eavP0Nc-v2^ zeop&fWXCPvht=;Bk&f(8-2#NohwKmz5~s6*%wZPj^Tdf1`6rswVtwKW4Wvl36tsNu zK`Fv-6F(v>-bX1!_3A(@_p$eL6c$x0LfCCb$1GQd(2Aq5IR;Jn4C%xk)I2m4O{p4? 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×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", "\n", "Basic DQN Module. Args:\n", - " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", - " ao: Number of actions to output.\n", - " layers: Number of layers where is determined per element.\n", - " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", - " to the head on top of existing linear layers.\n", - " nc: Number of channels that will be expected by the convolutional blocks. " + " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", + " ao: Number of actions to output.\n", + " layers: Number of layers where is determined per element.\n", + " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", + " to the head on top of existing linear layers.\n", + " nc: Number of channels that will be expected by the convolutional blocks. " ], "text/plain": [ "" @@ -57,12 +67,12 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -81,17 +91,17 @@ " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" + "group_interp.plot_reward_bounds(per_episode=True, show_average=True, hide_edges=True,smooth_groups=10)" ] }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -109,13 +119,13 @@ " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp_2.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp_2.plot_reward_bounds(per_episode=True, smooth_groups=10)\n", + "group_interp_2.plot_reward_bounds(per_episode=True,show_average=True, hide_edges=True, smooth_groups=10)\n", "group_interp.add_interpretation(group_interp_2)" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -149,82 +159,82 @@ " \n", " \n", " 0\n", - " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 188.234590\n", - " 499.0\n", - " 9.1\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 57.051663\n", + " 202.3\n", + " 10.5\n", " reward\n", " \n", " \n", " 1\n", - " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 220.743902\n", - " 499.0\n", - " 12.4\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 75.768736\n", + " 198.0\n", + " 10.3\n", " reward\n", " \n", " \n", " 2\n", - " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 186.998891\n", - " 499.0\n", - " 9.5\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 56.496674\n", + " 166.4\n", + " 9.1\n", " reward\n", " \n", " \n", " 3\n", - " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 152.903104\n", - " 499.0\n", - " 7.1\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 11.074058\n", + " 26.8\n", + " 5.8\n", " reward\n", " \n", " \n", " 4\n", - " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", - " 147.719512\n", - " 499.0\n", - " 9.2\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 36.042572\n", + " 275.0\n", + " 9.5\n", " reward\n", " \n", " \n", " 5\n", - " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", - " 57.051663\n", - " 202.3\n", - " 10.5\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 188.234590\n", + " 499.0\n", + " 9.1\n", " reward\n", " \n", " \n", " 6\n", - " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", - " 75.768736\n", - " 198.0\n", - " 10.3\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 220.743902\n", + " 499.0\n", + " 12.4\n", " reward\n", " \n", " \n", " 7\n", - " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", - " 56.496674\n", - " 166.4\n", - " 9.1\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 186.998891\n", + " 499.0\n", + " 9.5\n", " reward\n", " \n", " \n", " 8\n", - " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", - " 11.074058\n", - " 26.8\n", - " 5.8\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 152.903104\n", + " 499.0\n", + " 7.1\n", " reward\n", " \n", " \n", " 9\n", - " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", - " 36.042572\n", - " 275.0\n", - " 9.5\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 147.719512\n", + " 499.0\n", + " 9.2\n", " reward\n", " \n", " \n", @@ -309,82 +319,82 @@ " \n", " \n", " 20\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 37.997111\n", - " 137.1\n", - " 11.7\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 258.565333\n", + " 499.0\n", + " 13.9\n", " reward\n", " \n", " \n", " 21\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 32.311973\n", - " 82.8\n", - " 9.1\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 269.299778\n", + " 499.0\n", + " 16.0\n", " reward\n", " \n", " \n", " 22\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 27.884035\n", - " 131.6\n", - " 5.9\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 154.370067\n", + " 499.0\n", + " 10.5\n", " reward\n", " \n", " \n", " 23\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 48.784701\n", - " 254.5\n", - " 9.5\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 141.921508\n", + " 252.6\n", + " 10.2\n", " reward\n", " \n", " \n", " 24\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 55.326164\n", - " 243.4\n", - " 9.7\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 168.225721\n", + " 499.0\n", + " 12.8\n", " reward\n", " \n", " \n", " 25\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 258.565333\n", - " 499.0\n", - " 13.9\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 37.997111\n", + " 137.1\n", + " 11.7\n", " reward\n", " \n", " \n", " 26\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 269.299778\n", - " 499.0\n", - " 16.0\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 32.311973\n", + " 82.8\n", + " 9.1\n", " reward\n", " \n", " \n", " 27\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 154.370067\n", - " 499.0\n", - " 10.5\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 27.884035\n", + " 131.6\n", + " 5.9\n", " reward\n", " \n", " \n", " 28\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 141.921508\n", - " 252.6\n", - " 10.2\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 48.784701\n", + " 254.5\n", + " 9.5\n", " reward\n", " \n", " \n", " 29\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 168.225721\n", - " 499.0\n", - " 12.8\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 55.326164\n", + " 243.4\n", + " 9.7\n", " reward\n", " \n", " \n", @@ -473,16 +483,16 @@ ], "text/plain": [ " name average max \\\n", - "0 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 188.234590 499.0 \n", - "1 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 220.743902 499.0 \n", - "2 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 186.998891 499.0 \n", - "3 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 152.903104 499.0 \n", - "4 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 147.719512 499.0 \n", - "5 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 57.051663 202.3 \n", - "6 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 75.768736 198.0 \n", - "7 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 56.496674 166.4 \n", - "8 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 11.074058 26.8 \n", - "9 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 36.042572 275.0 \n", + "0 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 57.051663 202.3 \n", + "1 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 75.768736 198.0 \n", + "2 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 56.496674 166.4 \n", + "3 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 11.074058 26.8 \n", + "4 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 36.042572 275.0 \n", + "5 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 188.234590 499.0 \n", + "6 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 220.743902 499.0 \n", + "7 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 186.998891 499.0 \n", + "8 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 152.903104 499.0 \n", + "9 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 147.719512 499.0 \n", "10 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 55.912860 397.6 \n", "11 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 41.026608 164.8 \n", "12 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 39.898004 154.5 \n", @@ -493,16 +503,16 @@ "17 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 196.119734 499.0 \n", "18 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 223.166962 499.0 \n", "19 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 162.472949 316.9 \n", - "20 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", - "21 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", - "22 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", - "23 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", - "24 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", - "25 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", - "26 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", - "27 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", - "28 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", - "29 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", + "20 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", + "21 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", + "22 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", + "23 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", + "24 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", + "25 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", + "26 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", + "27 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", + "28 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", + "29 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", "30 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 55.912860 397.6 \n", "31 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 41.026608 164.8 \n", "32 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 39.898004 154.5 \n", @@ -515,16 +525,16 @@ "39 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 162.472949 316.9 \n", "\n", " min type \n", - "0 9.1 reward \n", - "1 12.4 reward \n", - "2 9.5 reward \n", - "3 7.1 reward \n", - "4 9.2 reward \n", - "5 10.5 reward \n", - "6 10.3 reward \n", - "7 9.1 reward \n", - "8 5.8 reward \n", - "9 9.5 reward \n", + "0 10.5 reward \n", + "1 10.3 reward \n", + "2 9.1 reward \n", + "3 5.8 reward \n", + "4 9.5 reward \n", + "5 9.1 reward \n", + "6 12.4 reward \n", + "7 9.5 reward \n", + "8 7.1 reward \n", + "9 9.2 reward \n", "10 9.3 reward \n", "11 9.6 reward \n", "12 9.9 reward \n", @@ -535,16 +545,16 @@ "17 10.1 reward \n", "18 10.8 reward \n", "19 10.9 reward \n", - "20 11.7 reward \n", - "21 9.1 reward \n", - "22 5.9 reward \n", - "23 9.5 reward \n", - "24 9.7 reward \n", - "25 13.9 reward \n", - "26 16.0 reward \n", - "27 10.5 reward \n", - "28 10.2 reward \n", - "29 12.8 reward \n", + "20 13.9 reward \n", + "21 16.0 reward \n", + "22 10.5 reward \n", + "23 10.2 reward \n", + "24 12.8 reward \n", + "25 11.7 reward \n", + "26 9.1 reward \n", + "27 5.9 reward \n", + "28 9.5 reward \n", + "29 9.7 reward \n", "30 9.3 reward \n", "31 9.6 reward \n", "32 9.9 reward \n", @@ -557,7 +567,7 @@ "39 10.9 reward " ] }, - "execution_count": 8, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -568,12 +578,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -591,16 +601,9 @@ " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp_2.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp_2.plot_reward_bounds(per_episode=True, smooth_groups=20)\n", + "group_interp_2.plot_reward_bounds(per_episode=True,show_average=True, hide_edges=True, smooth_groups=20)\n", "group_interp.add_interpretation(group_interp_2)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { @@ -619,7 +622,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/docs_src/rl.agents.ddpg.ipynb b/docs_src/rl.agents.ddpg.ipynb index 003bbc6..6f66441 100644 --- a/docs_src/rl.agents.ddpg.ipynb +++ b/docs_src/rl.agents.ddpg.ipynb @@ -13,9 +13,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Can't import one of these: No module named 'pybulletgym.envs.mujoco.envs'\n", - "pygame 1.9.6\n", - "Hello from the pygame community. https://www.pygame.org/contribute.html\n" + "Can't import one of these: No module named 'pybullet'\n", + "Can't import one of these: No module named 'gym_maze'\n", + "Can't import one of these: No module named 'gym_minigrid'\n" ] } ], @@ -45,7 +45,7 @@ "text/markdown": [ "

__init__[test]

\n", "\n", - "> __init__(**`ni`**:`int`, **`ao`**:`int`, **`layers`**:`Collection`\\[`int`\\], **`discount`**:`float`=***`0.99`***, **`n_conv_blocks`**:`Collection`\\[`int`\\]=***`0`***, **`nc`**=***`3`***, **`opt`**=***`None`***, **`emb_szs`**:`ListSizes`=***`None`***, **`loss_func`**=***`None`***, **`w`**=***`-1`***, **`h`**=***`-1`***, **`ks`**=***`None`***, **`stride`**=***`None`***, **`grad_clip`**=***`5`***, **`tau`**=***`0.001`***, **`lr`**=***`0.001`***, **`actor_lr`**=***`0.0001`***, **\\*\\*`kwargs`**)\n", + "> __init__(**`ni`**:`int`, **`ao`**:`int`, **`layers`**:`Collection`\\[`int`\\], **`discount`**:`float`=***`0.99`***, **`n_conv_blocks`**:`Collection`\\[`int`\\]=***`0`***, **`nc`**=***`3`***, **`opt`**=***`None`***, **`emb_szs`**:`ListSizes`=***`None`***, **`loss_func`**=***`None`***, **`w`**=***`-1`***, **`h`**=***`-1`***, **`ks`**=***`None`***, **`stride`**=***`None`***, **`grad_clip`**=***`5`***, **`tau`**=***`0.001`***, **`lr`**=***`0.001`***, **`actor_lr`**=***`0.0001`***, **`batch_norm`**=***`False`***, **\\*\\*`kwargs`**)\n", "\n", "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", "\n", @@ -89,7 +89,7 @@ "memory = ExperienceReplay(memory_size=1000000, reduce_ram=True)\n", "model = create_ddpg_model(data=data, base_arch=DDPGModule)\n", "learner = ddpg_learner(data=data, model=model, memory=memory, exploration_method=exploration_method)\n", - "learner.fit(450)" + "learner.fit(4)" ] }, { @@ -237,7 +237,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/docs_src/rl.agents.doubledqn.ipynb b/docs_src/rl.agents.doubledqn.ipynb index 7cd5b53..4c99ffa 100644 --- a/docs_src/rl.agents.doubledqn.ipynb +++ b/docs_src/rl.agents.doubledqn.ipynb @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -46,12 +46,12 @@ "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", "\n", "Basic DQN Module. Args:\n", - " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", - " ao: Number of actions to output.\n", - " layers: Number of layers where is determined per element.\n", - " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", - " to the head on top of existing linear layers.\n", - " nc: Number of channels that will be expected by the convolutional blocks. " + " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", + " ao: Number of actions to output.\n", + " layers: Number of layers where is determined per element.\n", + " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", + " to the head on top of existing linear layers.\n", + " nc: Number of channels that will be expected by the convolutional blocks. " ], "text/plain": [ "" @@ -349,12 +349,12 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -366,13 +366,13 @@ } ], "source": [ - "model_dirs = ['data/lunarlander_ddqn', 'data/lunarlander_dqn fixed targeting']\n", + "model_dirs = ['data/lunarlander_ddqn', 'data/lunarlander_fixed target dqn']\n", "group_interp = GroupAgentInterpretation()\n", "for model_dir in model_dirs:\n", " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" + "group_interp.plot_reward_bounds(per_episode=True, show_average=True, hide_edges=True,smooth_groups=30)" ] } ], diff --git a/docs_src/rl.agents.dqnfixedtarget.ipynb b/docs_src/rl.agents.dqnfixedtarget.ipynb index 86e4b48..88775f8 100644 --- a/docs_src/rl.agents.dqnfixedtarget.ipynb +++ b/docs_src/rl.agents.dqnfixedtarget.ipynb @@ -549,7 +549,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 19, "metadata": { "pycharm": { "is_executing": true @@ -558,7 +558,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -570,13 +570,13 @@ } ], "source": [ - "model_dirs = ['data/lunarlander_dqn', 'data/lunarlander_dqn fixed targeting']\n", + "model_dirs = ['data/lunarlander_dqn', 'data/lunarlander_fixed target dqn']\n", "group_interp = GroupAgentInterpretation()\n", "for model_dir in model_dirs:\n", " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp.plot_reward_bounds(per_episode=True, smooth_groups=10)" + "group_interp.plot_reward_bounds(per_episode=True, show_average=True, hide_edges=True,smooth_groups=30)" ] } ], diff --git a/docs_src/rl.agents.duelingdqn.ipynb b/docs_src/rl.agents.duelingdqn.ipynb index 52d442e..9c37653 100644 --- a/docs_src/rl.agents.duelingdqn.ipynb +++ b/docs_src/rl.agents.duelingdqn.ipynb @@ -13,9 +13,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Can't import one of these: No module named 'pybulletgym.envs.mujoco.envs'\n", - "pygame 1.9.6\n", - "Hello from the pygame community. https://www.pygame.org/contribute.html\n" + "Can't import one of these: No module named 'pybullet'\n", + "Can't import one of these: No module named 'gym_maze'\n", + "Can't import one of these: No module named 'gym_minigrid'\n" ] } ], @@ -46,12 +46,12 @@ "
×

No tests found for __init__. To contribute a test please refer to this guide and this discussion.

\n", "\n", "Basic DQN Module. Args:\n", - " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", - " ao: Number of actions to output.\n", - " layers: Number of layers where is determined per element.\n", - " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", - " to the head on top of existing linear layers.\n", - " nc: Number of channels that will be expected by the convolutional blocks. " + " ni: Number of inputs. Expecting a flat state `[1 x ni]`\n", + " ao: Number of actions to output.\n", + " layers: Number of layers where is determined per element.\n", + " n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added\n", + " to the head on top of existing linear layers.\n", + " nc: Number of channels that will be expected by the convolutional blocks. " ], "text/plain": [ "" @@ -99,12 +99,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 4, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -128,12 +128,12 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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" ] @@ -191,86 +191,46 @@ " \n", " \n", " 0\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 37.997111\n", - " 137.1\n", - " 11.7\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 29.125333\n", + " 81.6\n", + " 7.2\n", " reward\n", " \n", " \n", " 1\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 32.311973\n", - " 82.8\n", - " 9.1\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 52.764745\n", + " 166.8\n", + " 9.6\n", " reward\n", " \n", " \n", " 2\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 27.884035\n", - " 131.6\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.286918\n", + " 47.8\n", " 5.9\n", " reward\n", " \n", " \n", " 3\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 48.784701\n", - " 254.5\n", - " 9.5\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.516186\n", + " 119.8\n", + " 8.3\n", " reward\n", " \n", " \n", " 4\n", - " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", - " 55.326164\n", - " 243.4\n", - " 9.7\n", + " (DQN Fixed Targeting, PriorityExperienceReplay...\n", + " 16.339468\n", + " 218.5\n", + " 8.4\n", " reward\n", " \n", " \n", " 5\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 258.565333\n", - " 499.0\n", - " 13.9\n", - " reward\n", - " \n", - " \n", - " 6\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 269.299778\n", - " 499.0\n", - " 16.0\n", - " reward\n", - " \n", - " \n", - " 7\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 154.370067\n", - " 499.0\n", - " 10.5\n", - " reward\n", - " \n", - " \n", - " 8\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 141.921508\n", - " 252.6\n", - " 10.2\n", - " reward\n", - " \n", - " \n", - " 9\n", - " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", - " 168.225721\n", - " 499.0\n", - " 12.8\n", - " reward\n", - " \n", - " \n", - " 10\n", " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", " 148.154989\n", " 499.0\n", @@ -278,7 +238,7 @@ " reward\n", " \n", " \n", - " 11\n", + " 6\n", " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", " 141.317738\n", " 285.8\n", @@ -286,7 +246,7 @@ " reward\n", " \n", " \n", - " 12\n", + " 7\n", " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", " 229.873836\n", " 496.0\n", @@ -294,7 +254,7 @@ " reward\n", " \n", " \n", - " 13\n", + " 8\n", " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", " 149.444346\n", " 483.9\n", @@ -302,7 +262,7 @@ " reward\n", " \n", " \n", - " 14\n", + " 9\n", " (DQN Fixed Targeting, ExperienceReplay_FEED_TY...\n", " 137.559645\n", " 499.0\n", @@ -310,47 +270,47 @@ " reward\n", " \n", " \n", - " 15\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 29.125333\n", - " 81.6\n", - " 7.2\n", + " 10\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 258.565333\n", + " 499.0\n", + " 13.9\n", " reward\n", " \n", " \n", - " 16\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 52.764745\n", - " 166.8\n", - " 9.6\n", + " 11\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 269.299778\n", + " 499.0\n", + " 16.0\n", " reward\n", " \n", " \n", - " 17\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.286918\n", - " 47.8\n", - " 5.9\n", + " 12\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 154.370067\n", + " 499.0\n", + " 10.5\n", " reward\n", " \n", " \n", - " 18\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.516186\n", - " 119.8\n", - " 8.3\n", + " 13\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 141.921508\n", + " 252.6\n", + " 10.2\n", " reward\n", " \n", " \n", - " 19\n", - " (DQN Fixed Targeting, PriorityExperienceReplay...\n", - " 16.339468\n", - " 218.5\n", - " 8.4\n", + " 14\n", + " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", + " 168.225721\n", + " 499.0\n", + " 12.8\n", " reward\n", " \n", " \n", - " 20\n", + " 15\n", " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", " 37.997111\n", " 137.1\n", @@ -358,7 +318,7 @@ " reward\n", " \n", " \n", - " 21\n", + " 16\n", " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", " 32.311973\n", " 82.8\n", @@ -366,7 +326,7 @@ " reward\n", " \n", " \n", - " 22\n", + " 17\n", " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", " 27.884035\n", " 131.6\n", @@ -374,7 +334,7 @@ " reward\n", " \n", " \n", - " 23\n", + " 18\n", " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", " 48.784701\n", " 254.5\n", @@ -382,7 +342,7 @@ " reward\n", " \n", " \n", - " 24\n", + " 19\n", " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", " 55.326164\n", " 243.4\n", @@ -390,7 +350,7 @@ " reward\n", " \n", " \n", - " 25\n", + " 20\n", " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", " 258.565333\n", " 499.0\n", @@ -398,7 +358,7 @@ " reward\n", " \n", " \n", - " 26\n", + " 21\n", " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", " 269.299778\n", " 499.0\n", @@ -406,7 +366,7 @@ " reward\n", " \n", " \n", - " 27\n", + " 22\n", " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", " 154.370067\n", " 499.0\n", @@ -414,7 +374,7 @@ " reward\n", " \n", " \n", - " 28\n", + " 23\n", " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", " 141.921508\n", " 252.6\n", @@ -422,81 +382,221 @@ " reward\n", " \n", " \n", - " 29\n", + " 24\n", " (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE...\n", " 168.225721\n", " 499.0\n", " 12.8\n", " reward\n", " \n", + " \n", + " 25\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 37.997111\n", + " 137.1\n", + " 11.7\n", + " reward\n", + " \n", + " \n", + " 26\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 32.311973\n", + " 82.8\n", + " 9.1\n", + " reward\n", + " \n", + " \n", + " 27\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 27.884035\n", + " 131.6\n", + " 5.9\n", + " reward\n", + " \n", + " \n", + " 28\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 48.784701\n", + " 254.5\n", + " 9.5\n", + " reward\n", + " \n", + " \n", + " 29\n", + " (Dueling DQN, PriorityExperienceReplay_FEED_TY...\n", + " 55.326164\n", + " 243.4\n", + " 9.7\n", + " reward\n", + " \n", + " \n", + " 30\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 57.051663\n", + " 202.3\n", + " 10.5\n", + " reward\n", + " \n", + " \n", + " 31\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 75.768736\n", + " 198.0\n", + " 10.3\n", + " reward\n", + " \n", + " \n", + " 32\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 56.496674\n", + " 166.4\n", + " 9.1\n", + " reward\n", + " \n", + " \n", + " 33\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 11.074058\n", + " 26.8\n", + " 5.8\n", + " reward\n", + " \n", + " \n", + " 34\n", + " (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT...\n", + " 36.042572\n", + " 275.0\n", + " 9.5\n", + " reward\n", + " \n", + " \n", + " 35\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 188.234590\n", + " 499.0\n", + " 9.1\n", + " reward\n", + " \n", + " \n", + " 36\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 220.743902\n", + " 499.0\n", + " 12.4\n", + " reward\n", + " \n", + " \n", + " 37\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 186.998891\n", + " 499.0\n", + " 9.5\n", + " reward\n", + " \n", + " \n", + " 38\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 152.903104\n", + " 499.0\n", + " 7.1\n", + " reward\n", + " \n", + " \n", + " 39\n", + " (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward)\n", + " 147.719512\n", + " 499.0\n", + " 9.2\n", + " reward\n", + " \n", " \n", "\n", "" ], "text/plain": [ " name average max \\\n", - "0 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", - "1 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", - "2 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", - "3 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", - "4 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", - "5 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", - "6 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", - "7 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", - "8 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", - "9 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", - "10 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 148.154989 499.0 \n", - "11 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 141.317738 285.8 \n", - "12 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 229.873836 496.0 \n", - "13 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 149.444346 483.9 \n", - "14 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 137.559645 499.0 \n", - "15 (DQN Fixed Targeting, PriorityExperienceReplay... 29.125333 81.6 \n", - "16 (DQN Fixed Targeting, PriorityExperienceReplay... 52.764745 166.8 \n", - "17 (DQN Fixed Targeting, PriorityExperienceReplay... 16.286918 47.8 \n", - "18 (DQN Fixed Targeting, PriorityExperienceReplay... 16.516186 119.8 \n", - "19 (DQN Fixed Targeting, PriorityExperienceReplay... 16.339468 218.5 \n", - "20 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", - "21 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", - "22 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", - "23 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", - "24 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", - "25 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", - "26 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", - "27 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", - "28 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", - "29 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", + "0 (DQN Fixed Targeting, PriorityExperienceReplay... 29.125333 81.6 \n", + "1 (DQN Fixed Targeting, PriorityExperienceReplay... 52.764745 166.8 \n", + "2 (DQN Fixed Targeting, PriorityExperienceReplay... 16.286918 47.8 \n", + "3 (DQN Fixed Targeting, PriorityExperienceReplay... 16.516186 119.8 \n", + "4 (DQN Fixed Targeting, PriorityExperienceReplay... 16.339468 218.5 \n", + "5 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 148.154989 499.0 \n", + "6 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 141.317738 285.8 \n", + "7 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 229.873836 496.0 \n", + "8 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 149.444346 483.9 \n", + "9 (DQN Fixed Targeting, ExperienceReplay_FEED_TY... 137.559645 499.0 \n", + "10 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", + "11 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", + "12 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", + "13 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", + "14 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", + "15 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", + "16 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", + "17 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", + "18 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", + "19 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", + "20 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", + "21 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", + "22 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", + "23 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", + "24 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", + "25 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", + "26 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", + "27 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", + "28 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", + "29 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", + "30 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 57.051663 202.3 \n", + "31 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 75.768736 198.0 \n", + "32 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 56.496674 166.4 \n", + "33 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 11.074058 26.8 \n", + "34 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 36.042572 275.0 \n", + "35 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 188.234590 499.0 \n", + "36 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 220.743902 499.0 \n", + "37 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 186.998891 499.0 \n", + "38 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 152.903104 499.0 \n", + "39 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 147.719512 499.0 \n", "\n", " min type \n", - "0 11.7 reward \n", - "1 9.1 reward \n", + "0 7.2 reward \n", + "1 9.6 reward \n", "2 5.9 reward \n", - "3 9.5 reward \n", - "4 9.7 reward \n", - "5 13.9 reward \n", - "6 16.0 reward \n", - "7 10.5 reward \n", - "8 10.2 reward \n", - "9 12.8 reward \n", - "10 10.6 reward \n", - "11 14.1 reward \n", - "12 9.8 reward \n", - "13 13.5 reward \n", - "14 10.4 reward \n", - "15 7.2 reward \n", - "16 9.6 reward \n", + "3 8.3 reward \n", + "4 8.4 reward \n", + "5 10.6 reward \n", + "6 14.1 reward \n", + "7 9.8 reward \n", + "8 13.5 reward \n", + "9 10.4 reward \n", + "10 13.9 reward \n", + "11 16.0 reward \n", + "12 10.5 reward \n", + "13 10.2 reward \n", + "14 12.8 reward \n", + "15 11.7 reward \n", + "16 9.1 reward \n", "17 5.9 reward \n", - "18 8.3 reward \n", - "19 8.4 reward \n", - "20 11.7 reward \n", - "21 9.1 reward \n", - "22 5.9 reward \n", - "23 9.5 reward \n", - "24 9.7 reward \n", - "25 13.9 reward \n", - "26 16.0 reward \n", - "27 10.5 reward \n", - "28 10.2 reward \n", - "29 12.8 reward " + "18 9.5 reward \n", + "19 9.7 reward \n", + "20 13.9 reward \n", + "21 16.0 reward \n", + "22 10.5 reward \n", + "23 10.2 reward \n", + "24 12.8 reward \n", + "25 11.7 reward \n", + "26 9.1 reward \n", + "27 5.9 reward \n", + "28 9.5 reward \n", + "29 9.7 reward \n", + "30 10.5 reward \n", + "31 10.3 reward \n", + "32 9.1 reward \n", + "33 5.8 reward \n", + "34 9.5 reward \n", + "35 9.1 reward \n", + "36 12.4 reward \n", + "37 9.5 reward \n", + "38 7.1 reward \n", + "39 9.2 reward " ] }, "execution_count": 6, @@ -510,12 +610,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -533,7 +633,7 @@ " for file in os.listdir(model_dir):\n", " file = file.replace('.pickle', '')\n", " group_interp_2.add_interpretation(GroupAgentInterpretation.from_pickle(model_dir, file))\n", - "group_interp_2.plot_reward_bounds(per_episode=True, smooth_groups=20)\n", + "group_interp_2.plot_reward_bounds(per_episode=True, show_average=True, hide_edges=True,smooth_groups=20)\n", "group_interp.add_interpretation(group_interp_2)" ] } @@ -554,7 +654,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/docs_src/rl.core.train.interpretation.ipynb b/docs_src/rl.core.train.interpretation.ipynb index 17518a5..35a2148 100644 --- a/docs_src/rl.core.train.interpretation.ipynb +++ b/docs_src/rl.core.train.interpretation.ipynb @@ -13,9 +13,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Can't import one of these: No module named 'pybulletgym.envs.mujoco.envs'\n", - "pygame 1.9.6\n", - "Hello from the pygame community. https://www.pygame.org/contribute.html\n" + "Can't import one of these: No module named 'pybullet'\n", + "Can't import one of these: No module named 'gym_maze'\n", + "Can't import one of these: No module named 'gym_minigrid'\n" ] } ], @@ -24,8 +24,7 @@ "from fast_rl.agents.dqn_models import FixedTargetDQNModule\n", "from fast_rl.core.agent_core import *\n", "from fast_rl.core.data_block import *\n", - "from fast_rl.core.train import *\n", - "import logging" + "from fast_rl.core.train import *" ] }, { @@ -52,63 +51,63 @@ " \n", " \n", " 0\n", - " 1.024499\n", + " 1.095179\n", " #na#\n", - " 00:04\n", + " 00:00\n", " \n", " \n", " 1\n", - " 0.992940\n", + " 1.026340\n", " #na#\n", - " 00:02\n", + " 00:00\n", " \n", " \n", " 2\n", - " 0.994167\n", + " 1.007764\n", " #na#\n", - " 00:01\n", + " 00:00\n", " \n", " \n", " 3\n", - " 0.978045\n", + " 1.001356\n", " #na#\n", - " 00:04\n", + " 00:00\n", " \n", " \n", " 4\n", - " 0.965340\n", + " 0.996845\n", " #na#\n", - " 00:05\n", + " 00:00\n", " \n", " \n", " 5\n", - " 0.961320\n", + " 0.993165\n", " #na#\n", - " 00:02\n", + " 00:00\n", " \n", " \n", " 6\n", - " 0.955802\n", + " 0.988180\n", " #na#\n", - " 00:04\n", + " 00:00\n", " \n", " \n", " 7\n", - " 0.953765\n", + " 0.986040\n", " #na#\n", - " 00:01\n", + " 00:00\n", " \n", " \n", " 8\n", - " 0.948629\n", + " 0.982307\n", " #na#\n", - " 00:02\n", + " 00:00\n", " \n", " \n", " 9\n", - " 0.932925\n", + " 0.976414\n", " #na#\n", - " 00:08\n", + " 00:00\n", " \n", " \n", "" @@ -119,2170 +118,77 @@ }, "metadata": {}, "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: [18.0, False]}\n", - "{0: [18.0, False], 1: [24.0, False]}\n", - "{0: [18.0, False], 1: [24.0, False], 2: [13.0, False]}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:fast_rl.core.data_block:Removing episodes: [2]. {0: [18.0, False], 1: [24.0, False], 2: [13.0, False], 3: [38.0, False]}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: [18.0, False], 1: [24.0, False], 2: [13.0, False], 3: [38.0, False]}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:fast_rl.core.data_block:Removing episodes: [4]. {0: [18.0, False], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, False]}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: [18.0, False], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, False]}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:fast_rl.core.data_block:Removing episodes: [0]. {0: [18.0, False], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, True], 5: [18.0, False]}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: [18.0, False], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, True], 5: [18.0, False]}\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "DEBUG:fast_rl.core.data_block:Presently there are 4 full episodes, and 2 \n", - "episodes to remove. (1)\n", - "DEBUG:fast_rl.core.data_block:Removing episodes: [5]. {0: [18.0, True], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, True], 5: [18.0, False], 6: [29.0, False]}\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "{0: [18.0, True], 1: [24.0, False], 2: [13.0, True], 3: [38.0, False], 4: [36.0, True], 5: [18.0, False], 6: [29.0, False]}\n" - ] - }, + } + ], + "source": [ + "data = MDPDataBunch.from_env('CartPole-v0', render='rgb_array', bs=32, add_valid=False, \n", + " memory_management_strategy='k_partitions_top', k=3)\n", + "model = create_dqn_model(data, FixedTargetDQNModule, opt=torch.optim.RMSprop)\n", + "memory = ExperienceReplay(10000)\n", + "exploration_method = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001)\n", + "learner = dqn_learner(data=data, model=model, memory=memory, exploration_method=exploration_method)\n", + "learner.fit(10)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "pycharm": { + "is_executing": true, + "name": "#%%\n" + } + }, + "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - 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" [255., 255., 255.],\n", - " ...,\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.]],\n", - " \n", - " [[255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " ...,\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.],\n", - " [255., 255., 255.]]]], dtype=float32), episode=9)]" + "" ] }, - "execution_count": 3, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "interp = AgentInterpretation(learner, ds_type=DatasetType.Train)\n", - "[g.write() for g in interp.generate_gif()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "ename": "EpisodeNotAvailable", - "evalue": "Episode 80 not found in [1, 3, 9]. \nNote that due to the\nmemory manager, memory that is not related to the agent's training will be\ndeallocated. One of the first things deallocated are the rendered images\nassociated with each step since images typically take up large amounts of\nmemory. This then means there are fewer episodes that you can get full\ngifs of. If this is not acceptable, make sure to change the memory management\nstrategy in the MDPDataBunch. ", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mEpisodeNotAvailable\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0minterp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate_gif\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m80\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", - "\u001b[0;32m~/PycharmProjects/fast-reinforcement-learning/fast_rl/core/train.py\u001b[0m in \u001b[0;36mgenerate_gif\u001b[0;34m(self, episode)\u001b[0m\n\u001b[1;32m 180\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mepisode\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mlist\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0many\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0me\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfull_episodes\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0me\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mepisode\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 181\u001b[0m \u001b[0mprefix\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Some Episodes'\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mepisode\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mlist\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;34m'Episode'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 182\u001b[0;31m raise EpisodeNotAvailable(f'{prefix} {episode} not found in {full_episodes}. \\nNote that due to the\\n'\n\u001b[0m\u001b[1;32m 183\u001b[0m \u001b[0;34mf'memory manager, memory that is not related to the agent\\'s training will be\\n'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 184\u001b[0m \u001b[0;34mf'deallocated. One of the first things deallocated are the rendered images\\n'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mEpisodeNotAvailable\u001b[0m: Episode 80 not found in [1, 3, 9]. \nNote that due to the\nmemory manager, memory that is not related to the agent's training will be\ndeallocated. One of the first things deallocated are the rendered images\nassociated with each step since images typically take up large amounts of\nmemory. This then means there are fewer episodes that you can get full\ngifs of. If this is not acceptable, make sure to change the memory management\nstrategy in the MDPDataBunch. " - ] - } - ], - "source": [ - "interp.generate_gif(80)" + "interp.generate_gif(2).plot()" ] } ], @@ -2302,7 +208,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.5" + "version": "3.6.7" }, "pycharm": { "stem_cell": { diff --git a/environment.yaml b/environment.yaml index 33c034f..fb5d411 100644 --- a/environment.yaml +++ b/environment.yaml @@ -26,4 +26,5 @@ dependencies: - gym[box2d, atari] - easydict - matplotlib - - jupyter_console \ No newline at end of file + - jupyter_console + - moviepy \ No newline at end of file diff --git a/fast_rl/core/layers.py b/fast_rl/core/layers.py index cef0527..3009f25 100644 --- a/fast_rl/core/layers.py +++ b/fast_rl/core/layers.py @@ -86,4 +86,4 @@ def forward(self, args): if not self.exclude_cat: return self.tabular_model(*args) else: - return self.tabular_model(0, torch.cat(args, axis=1)) + return self.tabular_model(0, torch.cat(args, 1)) From f28ae7f03b878d8b2f904007835294e5c59ee11d Mon Sep 17 00:00:00 2001 From: Josiah Laivins Date: Sun, 2 Feb 2020 17:47:20 -0500 Subject: [PATCH 04/29] Added: - fixed target lunar lander --- ...ddpg_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34395 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34435 bytes ...ddpg_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 75654 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 75694 bytes ...ddqn_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34396 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34436 bytes ...ddqn_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34395 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34435 bytes ... dqn_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34402 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34442 bytes ... dqn_ExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34407 bytes ...orityExperienceReplay_FEED_TYPE_STATE.pickle | Bin 0 -> 34447 bytes 12 files 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" time\n", + " \n", + " \n", + " \n", + " \n", + " 0\n", + " 1.475903\n", + " 0.743393\n", + " 00:03\n", + " \n", + " \n", + " 1\n", + " 0.296961\n", + " 0.179079\n", + " 00:03\n", + " \n", + " \n", + " 2\n", + " 0.162334\n", + " 0.137115\n", + " 00:03\n", + " \n", + " \n", + " 3\n", + " 0.149649\n", + " 0.131717\n", + " 00:03\n", + " \n", + " \n", + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "data = MDPDataBunch.from_env('Pendulum-v0', render='human', bs=64)\n", + "data = MDPDataBunch.from_env('Pendulum-v0',render='rgb_array',bs=64,res_wrap=partial(ResolutionWrapper,w_step=4,h_step=4))\n", "exploration_method = OrnsteinUhlenbeck(size=data.action.taken_action.shape, epsilon_start=1, \n", " epsilon_end=0.1, decay=0.001)\n", "memory = ExperienceReplay(memory_size=1000000, reduce_ram=True)\n", @@ -94,10 +146,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 5, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [], @@ -114,16 +166,16 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 10, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -141,43 +193,12 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": { - "pycharm": { - "is_executing": false - } - }, - "outputs": [ - { - "data": { - "image/png": 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\n", 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\n", 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\n", 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" ] @@ -189,22 +210,18 @@ } ], "source": [ - "model_dirs = ['data/mountaincarcontinuous_ddpg']\n", + "model_dirs = ['data/ant_ddpg']\n", "show_config_group(model_dirs)" ] }, { "cell_type": "code", - "execution_count": 7, - "metadata": { - "pycharm": { - "is_executing": false - } - }, + "execution_count": 17, + "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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6fQAYCaCX/jMVwCsRbhsRBcmYACECz1quPou5OlX1IjojjmM4R0QUuogFdCLSHMBlAN4EAKVUuVLqNIAxABbpuy0CMFa/PQbAYqX5AUBLEekUqfYRUfCM2M0mfjJ01cy0GbszQ0dEFLpIZuh6AMgHsFBENonIAhFpBqCDUuooAOi/2+v7JwI4bDr+iL6NiOqYkaGz2zyzXB0+faxOZ+DAzFyrjmPoiIjCJ5IBXRSAQQBeUUpdAOAsPN2rVsRiW6U/9SIyVUSyRCQrPz8/PC0lIr+MOnR2f7NcgwjMzBMp3AFdmNpIRNSYRTKgOwLgiFLqR/3+B9ACvGNGV6r++7hp/66m47sAyPU9qVLqdaVUplIqs127dhFrPBF5mGe5Ghm6mpQtcXpl6PTfXCqCiChkEQvolFJ5AA6LSG990wgAOwGsAjBJ3zYJwEr99ioAE/XZrhcBKDS6ZomobhmBmN2mBXUA4HD4BnSBJ0U42OVKRBQRka5Ddz+ApSISDWA/gDuhBZHLRORuAIcAjNf3/QTAtQD2AijR9yWi84DDqw6dXm7Ep7PUEUyGzmnV5cqIjogoVBEN6JRSmwFkWjw0wmJfBeC+SLaHiGrG5dXlqmfoajCG7ufjRe7b7rIljOeIiELGpb+IKCCHqctV3Gu5uqBM0ZhvXTort7+53n2bZUuIiMKHAR0RBeSeFGGzuTN0Tpf3JIdgJkWUVjjdtznLlYgofBjQEVFAnlmunvpCLqV8JjlU75xc+ouIKHwY0BFRQEZAF2UT2GyeDJ05oNtw4GS1zuk+lPEcEVHIGNARUUBGQWBt6S+Ny6W8Zq2u2lKpbKRfLFtCRBQ+DOiIKCB3HTq7Z5arSwEVptpzQ7q3rtY53bNcmaIjIgoZAzoiCsjhNC/9pW1zKpfXRIjElnHVOqdyj6ELTxuJiBozBnREFJCnyxVeGTpHNWe5mhm7K/a5EhGFjAEdEQXkdLn0YM7mqUPncsFhqj1X/YCOGToionBhQEdEAbmUnpkLa4aOkyKIiMKFAR0RBeRSCno8Z1opQnkFccGs5WpmHMtJEUREoWNAR0QBKQUItAkR5pUiHE5zhi7w0l8xUZ4/Oe6AjvEcEVHIGNARUUAul3Jn5swZOvMqD8Ek6Eakt3ffdrgzdEREFCoGdET1VM7pUsz/IrtWZom6FPQuV1MdOpd3QBfMGDqrtV85y5WIKHRRdd0AIqqZB9/dhA0HTuGCpFa4Mq194ANCoI2h0wI581quVgGaP1b7c5YrEVHomKEjqqfKHdqYtfyicxG/llIKNmhZOvdarpW6XGuYoQtvU4mIGiUGdET1lBFYVXd2aU1oXa7eGTqnyzu7FlSGzrSLp2wJQzoiolAxoCOqp6JsnrFskeZSSitZAs8sV1WDLldzWz0rRYSzpUREjRMDOqJ6yl7LGTr4zHJ1upRPgBa4HQ6L0ibM0BERhY4BHVE9FWXT/vet7goNNaNl6LxWioB3l2swzbAqVcdwjogodAzoiOopI0NXGwGdy6WNoTOKC2vbFJzVLVtikY1jho6IKHQM6IjqKXeXq7OWxtAJvFeKUNXvcrUa78d4jogodBEN6ETkgIhsE5HNIpKlb2stImtE5Gf9dyt9u4jISyKyV0S2isigSLaNqL7zjKELvORWqFzKM7vVyNApn8LCwUzOsNqD8RwRUehqI0P3K6XUQKVUpn5/NoCvlFK9AHyl3weAkQB66T9TAbxSC20jqreiTPXgIk2ZCgu7x9D5znINZgydZZdreNpIRNSY1UWX6xgAi/TbiwCMNW1frDQ/AGgpIp3qoH1E9YK7wK9TobjMgS2HT0fsWkbZEsA8yxXVztBZBXTBdNUSEZF/kQ7oFIAvRGSjiEzVt3VQSh0FAP23sWZRIoDDpmOP6NuIyILdNJbttjd+wJj/+w5nyxwRuZZnLVdTHToo78LCQQRmjN2IiCIj0mu5XqKUyhWR9gDWiMhuP/uKxbZKf/71wHAqACQlJYWnlUT1mEspbDlSCADIKyxFz/YJEbmG1UoRzjBMimCGjogodBHN0CmlcvXfxwF8BGAIgGNGV6r++7i++xEAXU2HdwGQa3HO15VSmUqpzHbt2kWy+UTnNaPrc/F/D5q2WX0vCp0yJkWIXr5EtEDMVc2yJVa7MJwjIgpdxAI6EWkmIgnGbQC/BrAdwCoAk/TdJgFYqd9eBWCiPtv1IgCFRtcsEVVmhG7nKjyzXCOV7TLKlpivbQ7oRILrTuWkCCKiyIhkl2sHAB/pGYMoAP9USn0mIhsALBORuwEcAjBe3/8TANcC2AugBMCdEWwbUYMU0YBO/w/QxtG5XFq3K6DNuA0uQ8fCwkREkRCxgE4ptR/AAIvtJwCMsNiuANwXqfYQNTRW3auRio2MSRGea+sZOj2Is4sEFUwqBdjEu+uV4RwRUei4UgRRAxKpDJ3Sy5Z4SpeIV5er3RZcQOdSyj1L1nNuZumIiELFgI6onrKcFh7RDJ24L2rTM3ROU0DnDGLBCpdCpYCOiIhCx4COqAFxBDGOrSZ8s28CgVKeMiTVy9B5b1NKcWIEEVGIGNAR1VcWia7aGkNnE61MiRE/BhvQKaXcK1y4t4WzoUREjRQDOqIGpHbH0Hlqz9mDnuXqHRga52ZQR0QUGgZ0RA1IpDJ0ylj6S4yyJcbSX9oFo2xiWTTYl+WkCHBSBBFRqBjQEdVTYtHnGtnCwp7riV6HzjPL1RZUUKYsJkUwliMiCh0DOqIGJLKFhT3cs1yrWVjYqENnEH0bYzoiotAEFdCJSE8RidFvXyEiM0SkZWSbRkT+WFX/OFPqiMi13GVL3Ne2qkMXzHkU7KaIziYCjqAjIgpdsCtFLAeQKSIpAN6Etu7qP6Et1UVEdcAqGffToVO4KqND2K/lclXO0JnLlkRVo2xJE5vne6SxBmx96HbduHFj+6ioqAUA+oK9G0RU+1wAtjscjsmDBw8+7vtgsAGdSynlEJEbALyglPqbiGwKazOJqFqsMludWsRG5lqVlv4Sr8LCUXYbnC4Fp8s7A+fLt7CwzSb1IpgDgKioqAUdO3ZMb9eu3SmbzVZPWk1EDYXL5ZL8/PyMvLy8BQBG+z4e7LfMChH5HYBJAFbr25qEqY1EFMDZMgeOF53z2mYVCEVqDQZtUoTnvrsOnc9arhUBlotQPoWFjdmy9aTbtW+7du3OMJgjorpgs9lUu3btCqH1ElR+PMjz3AngYgDPKKV+EZHuAP4RpjYSUQCj/vYfDHnmK3cABSCoSQjhok2K8ERi0XYbyp0uPeMG2GzBdZu6FLwKC9tE6k2XKwAbgzkiqkv63yDL2C2oLlel1E4AM0z3fwHwl7C0jogC2l9wFgBwsqQcbeNjAFjPaHXW0koRsU3sKKtwwamXM7FJdZb+8g7oIjUzl4ioMfEb0InINvipKKCU6h/2FhFRlRymLk2rOMil/Hd51lSlDF2UDYWlFXA6tS5UmwQ3y9W3bElxmTYrN7/oHLq2bhbuZkfUB1mHW+YXlwc7DjmgdvHRjpsyu54O1/mIqHEJ1OV6PYBRAD7Tf27Tfz4B8EFkm0ZEvlZuznXftspsRW4tV98xdJ5JETYR2G2iLeEV4PpWK0UAwEc/5YS5xZGXX1we1bllbEW4foIJDu12++C0tLQM4+exxx7rGMnnuHTp0haRvobhpZdeatOqVasBaWlpGd27d+/z5z//uX1Nz5WdnR3dq1evPuFq2+rVqxMSEhIGGq/7sGHDUgHgoYce6ty+ffv+5vekoKDA7rt/WlpaxooVKxIAz3uYkpLSp3fv3hlPPfVUB6fTaXnd5cuXNzeOb9q06QXJycl909LSMi6//PKUxMTEfocOHXL/m5kwYULSY4891tG4dnp6ekaPHj36zJw5s5PVczC3ycqsWbM6pqSk9ElNTc1IS0vL+Prrr5tdffXVPdPS0jKSkpL6ms+1Zs2aZgCQm5sbFRUVNei5555ra5ynf//+aWlpaRmdOnXqZ7y/aWlpGdnZ2dGJiYn9jPOnpaVl3HHHHV1922F+jbt169b317/+dc+NGze6Z38NGTKkd3Jyct/U1NSM7t2795k4cWJSQUGB3XjceL179erVZ+TIkT2KiopsAHD48OGoUaNGde/SpUu/Pn36pA8cODBt8eLF9bocm98/IEqpgwAgIpcopS4xPTRbRL4D8HQkG0dE3orOeerMWQV0kRpW5/LJrBllS5x6OROt0LD1zFvv8yivMXTu7WFub0MVExPj2r17987auFZFRQVuu+22QgCFtXE9ABg1atSpxYsXH8rLy7Onp6f3ve22206lpKRU1Nb1/cnMzCz+5ptv9vpunzZt2rGnn376WLD7m9/DnJycqPHjx/coLCy0P//887m++44bN+7MuHHjdgJa4DJv3rzDl112WQkA/PWvf213//33d125cuUv//nPf5quX78+/s0339y1Zs2aeOPaZ86csfXr1y9j7Nixhf7a5OvLL79s9vnnn7fctm3bzri4OHX06NGosrIyWbNmzT5ACw7nz5/fwfdcixcvbjVgwICz77//fptHHnmkAAC2bt26G9AC9qysrGaLFy8+ZD5m7dq1ezp16uS3gKb5NX7jjTda/eY3v+m9devWHZ07d3bo191/2WWXlZw7d07uv//+xJEjR6Zs2LAh2/f1Hj16dPf58+e3+9Of/nRs1KhRKbfeeuuJjz/++BcA2LNnT/T7779frwO6YCdFNBOR4cYdERkGoH71jxA1AObltayCt0iNR1M+Xa7mDF11xtD5drkaYpvYK2+koJw4ccKenJzcd8uWLTEAMGrUqO7z589vCwBNmza9YMqUKV0yMjLSL7744tTc3NwoANixY0fMpZde2qtPnz7pgwcP7r1p06ZYABg3blzy5MmTuwwdOjT197//fZeXXnqpzcSJE5MALfvym9/8pmffvn3T+/btm/7FF180A7QMyvjx45OHDBnSu0uXLv3mzJnjzqy9/PLLbVJTUzN69+6dMXbs2O7+zmPWsWNHZ1JSUtnhw4ebBLr22LFju1900UWp3bp162s8b7Ps7OzowYMH987IyEjPyMhIN7JJY8eO7f6Pf/zD/QE+evTo7kuXLm0RnnclOImJiY4FCxYcWLhwYXuXq3pfa2bOnJl/8ODBmI8//jjh/vvvT3rxxRcPxcTEeP1P2Lx5c1e/fv1KsrOzY6pz7pycnCatW7d2xMXFKQDo1KmTIzk5OWBg/f7777eeN2/e4by8vCa//PJLRCphTJky5dSll15a+Oabb7b2fSw2Nla98sorR3Jzc6P/+9//xvk+Pnz48OK9e/fGfPzxxwlNmjRRjz76aL7xWGpqavnjjz9eqbZbfRJsQHcXgP8TkQMi8guAv+vbiKiO1OaC9r6TIozZqS6XPobOFtxs1aq6XKPtkSq40rCUlZXZzF1mb7zxRqs2bdo4n3/++UOTJk3q/vrrr7c6ffp01MyZMwsAoLS01DZo0KCSnTt37rrkkkuKZs+e3RkAJk+e3O3vf//7oR07dux67rnnjtx7771JxjX27dsX+9133+154403jpivfc8993R96KGHjm3fvn3XRx99tG/atGnJxmN79+6NXbt27Z4NGzbsmjdvXueysjLJysqKnTdvXqe1a9fuyc7O3vnaa68dCnQew88//xxdVlZmGzp0aGmgY3bt2hX35Zdf/vzDDz/sfu655zofOHDAK5Do3LmzY926dXt27ty567333tv/hz/8IQkApkyZkv/222+3AbSgeOPGjfE333xzldnIrKyseON1nzVrlrsb+tVXX+1gbB86dGiq1f5paWkZO3bssAyqMjIyyl0uF3Jycqo1HtNut+Pvf//7wQkTJvTs0aPHuZEjRxb77pOXl2fftGlTs4EDB5ZWp01jx449k5ubG52cnNx3woQJSf/617/iA7Vn7969TQoKCpr86le/Khk9evSpRYsWVQq4rFx++eWpRnuC7Wa/4IILSnbv3m1ZdDMqKgrp6ekl27dv93q8oqICn3/+efN+/fqVbtu2La5///4lwVyrPgn4D0hEbABSlFIDRKQ5AFFK1VoKnog8zFk5qwxdgDJwNaZ81nIVYy1Xd4YuuOygb2Fhg9U2qqyqLtcbbrjhzLJly1o9+oLG0+sAACAASURBVOij3TZu3LjD2G6z2TB58uSTAHDXXXeduPHGG1MKCwttmzZtih8/fnxPY7/y8nL3G3DjjTeeioqq/NHw3XffNf/555/dWY/i4mL7qVOnbADw61//+nRcXJyKi4tztG7duuLIkSNRn3/+efNRo0adMrrTOnTo4Ax0no8//rhVSkpKwoEDB2Lnz59/oGnTpirQMSNHjjwdHx+v4uPjHRdffPGZdevWNRsyZIj7w7q8vFzuvvvubjt37oyz2Ww4ePBgDABcd911xQ8++GC3nJycqKVLl7a67rrrTjVpUnVSKVxdrlZq+uVs2LBhpb169SqdPn26V2YpKysrPj09PcNms6kHHnggLzMz89zq1aubBNumFi1auLZv377zs88+S/jqq68SJk2a1PNPf/rTkRkzZpyo6phFixa1Hj169CkAuP3220/efffdyU899VSl18VXMF2uvgK9XubHjS9BADB06NCiBx54oGDevHntzPvffvvtSevXr49v0qSJ2r59+67qtOV8EjCgU0q5RGQ6gGVKqTO10CaiSs5VONkt58N6DF2kZrl6r+VaKUOnd7n6+zNr/JG16nJl4ZLQOJ1O7NmzJzYmJsZVUFAQ1bNnT8vuMRGB0+lEQkKCo6qxePHx8Zb/iJRSyMrK2hUfH1/p7TJ39dntdjgcDlFasF9pX3/nMcbQffnll83GjRvX64YbbihMSkpy+DtGfL4M+N5/5plnOrRv375i+fLlv7hcLsTFxQ02Hrv55ptPLFiwoPXy5ctbv/XWWwesnnek7dy5M9putyMxMbFGCzHbbDbY7d5/G6sTTFYlKioK119/fdH1119f1L9//9IlS5a08RfQLV++vHVBQUGTDz/8sDUAHD9+vMm2bdti+vXrVxZKO6xs3ry56eDBgy0zbA6HA9nZ2U379++fC1h/CerXr1/pypUrWxn3lyxZcujo0aNRmZmZ6eFua20Ktst1jYg8LCJdRaS18RPRlhHpvt59DGl//Aw/7q/yb0mjYTWGrnlsVKVt4VZplqtN22YEetp9/9+cjYfMkyKuSNW+KLdsWv8WnmkXH+3IPX2uSbh+2sVH1+gDHQCefvrpDqmpqecWLVq0/+67704uKysTAHC5XFi4cGErAHj77bfbDBkypKh169auLl26lL/11lutjH2sxhv5Gj58+Jm5c+e6u8S+//57v8dcc801Z1atWtU6Ly/PDgDHjh2zB3ueq6666uyNN954Yu7cuR0CHfPpp5+2LCkpkby8PPsPP/yQMHz48LPmcxUWFto7depUoXdRtjHPKJ02bVrBa6+91gEAMjMzvZdiqQW5ublRU6ZM6XbnnXcet9nOn+WBt2zZErNt2zZ3d+ymTZviunTpUu5v/5KSEvvx48e35uTkbMvJydk2ffr0vMWLF4c9Tnj77bdbrlu3rsVdd9110vexsrIymT59epdOnTqVG931VkaNGlVUVlYmc+fOdWfqiouLz583oIaC7bM3xsvdZ9qmAPQIdKCI2AFkAchRSl2vrzLxLoDWAH4CcLtSqlxEYgAsBjAYwAkAv1VKHQiyfdSArc3Wxq1+su0ohvZoU8etqVvmcMnlUkhq3RQP/zoVhSUV+OOqHRErW6KU97JiRt05p0sL9LSMXeAZrsaxhtgm2t9QYwWMe5ZkIa5JFF64ZWB4n0AE1EXNOHP3EQBceeWVhdOmTStYsmRJ240bN+5q1aqV64MPPiiaPXt2p+effz43Li7OtWPHjrg+ffp0TEhIcH744Yf7AeCdd97ZP2XKlG5z587t5HA45IYbbjh58cUXV/kBCACvv/764cmTJyelpqZmOJ1OGTp0aNGwYcMOVbV/ZmbmuZkzZx699NJL02w2m+rbt2/J8uXLDwR7nieffDIvMzMzY86cOUf9HXPBBRecHTFiRK/c3Nzohx9++GhycnJFdnZ2tHGeBx988Pi4ceN6rlixotXw4cOL4uLi3BnIrl27Onr27Hlu1KhRNX4vX3311Q7Lli1z/2FauXLlXsAzXs3YPmvWrKN33nnnKeM9dDgcYrfb1W9/+9sTTz75ZMCuyXCoqk2++505c8Y+Y8aMpDNnztjtdrtKTk4uW7Ro0cGqzrto0aI21157rdd5brnlllO33nprj+eee+6ovzZdfvnlqUYwm56eXvLRRx8d8N3HeI1LS0ttqamppZ9//nm2McMVACZOnNgjOjraVV5ebrv00kvPfPrpp36zkzabDR9//PG+++67r+tLL73UsXXr1o6mTZs6n3rqqSP+jjvfSaQHVovIQwAyATTXA7plAD5USr0rIq8C2KKUekVEfg+gv1JqmojcAuAGpdRv/Z07MzNTZWVlRbT9VPf+uGI7lvxwEJOGdcOfR3uWsHM4XbDbpFIXS0OUPPtfAICpl/bAY9dpvQK3vvEDck6X4vFr05FfVIbHV2zHgyN64cGrU/2dqkaGz/0abeNjMP1XKQCAhd/9gm25hfhV7/ZY93MBhnZvjU+352HLk1ejRVy05TnKHS6kPvEpBiW1xE+HtM/P6/p1xL+25WHeTf1xU2ZX9/M88Jfrwv4cqkNENiqlMs3btmzZcmDAgAEFddWmmmjatOkFJSUlm+q6HZHy0EMPdY6Pj3dajWELRlFRkS0jIyNj8+bNu9q0aWNdDI7oPLNly5a2AwYMSPbdHnSKUUT6isjNIjLR+AnimC4ArgOwQL8vAK6EpyjxIgBj9dtj9PvQHx8hjeGTmgIyMjt20z+HwpIKpDz+KV7+OqRhIvWOC+YuV22igsAzAzVSX9BcPpMijDF0Rh06u96N6q/L152h81nLFQCcPu2uzRm81DitWLEiITU1tc+UKVOOM5ijhiCoLlcReRLAFQAyoK0SMRLAf6B1kfrzAoBHARjVqNsAOK2UMlKlRwAk6rcTARwGAKWUQ0QK9f3r1TdiCj8jSDDH9/nF2nCXpT8exP0jetVFs+qGzyxXEe11MWrERapAb6WyJTa9Dp17UoS23eknojNiNJdpHyMQ9D1O+VyPaqYhZ+cA4H//938rFeMN1tixY4vGjh27zbxt+fLlzR9//PEu5m1du3YtMwrqRlJdXDsvL89+xRVX9Pbd/u2332Z37NiRQW49E+wYupsADACwSSl1p4h0gJ51q4qIXA/guFJqo4hcYWy22FUF8Zj5vFMBTAWApKSkSgdQw2Nka8z/QOz6mItILUZ/vnIq3wyd9qoYAVVECwt7zXLVgi73pAj9sXJH1SGl0bZm0Z4/O8ZxLp+AzqUUbJZ/Eogix7wyQ2O4dseOHZ21tfIIRV6wXa6lSikXAIdei+44Ak+IuATAaBE5AG0SxJXQMnYtRcT4i94FgPEN6wiArgCgP94CQKVZLEqp15VSmUqpzHbt2vk+TA2QyyqgqyIQaOiU6flaZbEiufSXdx06LUPncrnckyIAoLC0yolw7vcxPrZyQOdbP6+Rva1ERCELNqDLEpGWAN4AsBHa7NT1/g5QSv2PUqqLUioZwC0AvlZK3QbgG2gZPwCYBGClfnuVfh/6418rDqQhmLtcPduMGf6Rykidr9Yf8HzHcbk8WTOj6zLrQKXvQGFRqWyJsZarXijYeD+i/JRecL+Ppm12fXenT/28xva+EhGFKqguV6XU7/Wbr4rIZ9BmrG6t4TVnAXhXROYA2ATgTX37mwCWiMheaJm5W2p4fmpgrMpdeB6r7dbUrZ1Hi9y3z5yrQJQeyLWI0+q4NYup1upBQVMu3y5XLUPncLm0gE6sx8J5ncPItJrPo7ff0djeSCKiMAt2UsRiAOsArFNK7a7uRZRS3wL4Vr+9H8AQi33OARhf3XNTI2AxytI9wL6RZHJaxjXB6VLv4v8nz5Yjpb22xKKIIMomiI2KzGoavl2uxizXcoeC3QZESeDAzCrTahzn+zbWi7d189KWKD4evgg6vr0DA2+r9dp2RNQwBNvl+jaATgD+JiL7RGS5iDwQuWYRefiWtAA8gVy9+OAPgzKLyQYK3llLEcD/4ls151LKa8kum2jB2w/7T+DQyVJIFbNVfc8BVA4MzY8ZIvU8wqr4eBRadKkI208QwaHdbh+clpaW0atXrz4jR47sUVRUZPk3/PLLL08pKCioVnRvHFNQUGD/y1/+EnCA8urVqxMSEhIGmhd7X7FiRUKg40Lx4IMPdo70NQzjxo1LTkxM7JeWlpbRu3fvjJUrV9b4ui+99FKbiRMnhm0W30MPPdS5ffv2/Y3X/fe//30iAAwZMqR3cnJyX2P7Nddc08Nq/7S0tIyCggK78R6mp6dnJCcn983MzOz9zjvvtKjqurNmzepoHG/8W0xLS8uYM2dO+4EDB6a5XNrfKYfDgbS0tIw1a9Y0M1+7V69efZYuXdrCX5usrltUVGQbPXp099TU1IxevXr1GTx4cO89e/ZEG8e1bdt2gPlc586dEwBYvHhxSxEZvGnTplgAWL9+fZyxT4sWLQYa7++wYcNSs7Ozo2NjYweZ2/Pyyy9XqmRvvMapqakZ3bt37zNx4sQkc7uN1yUlJaVP7969M5566qkOxuok5te7R48efWbOnNnJOO6bb75pOmTIkN7dunXrm5GRkX7FFVekrF+/PuAKLmbBdrl+LSJrAVwI4FcApgHoA+DF6lyMqCZ+PlZcaZvVeKyGLCbKhtIK7yoCxjqqBtGzZpGgLNZyNXOXH/HTAJdll6v226psCVVmXpdy9OjR3efPn9/OvAC6y+WCUgpr164NukCj7zHZ2dnRb775ZvvZs2fnBzo2HGuGBsvhcOCFF16ocZmSmpgzZ86RO++889THH3+cMH369G5jxozZXpvX92fatGnHrAoqL168eP9ll11WaZ3TqvY3v4fff/993Pjx41OaNm16YMyYMUW++86dOzdv7ty5eYBWtNo8Q/aHH36If+GFF9o+9NBDBc8++2z7gQMHnr366qvPfvrppy2Ma//000+xI0aM6H3LLbds8dcmX88++2z79u3bV6xateoXQFtqrGvXrhXG9asqMP3uu++2HjRoUPGSJUtaX3DBBblDhgwpNY4ZN25c8vXXX19orJSRnZ0d3bVr17JgZv0ar/G5c+fk/vvvTxw5cmTKhg0bsgHv/0dzcnKixo8f36OwsND+/PPP55pf7zNnztj69euXMXbs2MLk5OTyCRMm9Hz77bf3X3311WcB4PPPP4/Pzs6OGTJkiN8VXMyCytCJyFcAvgPwWwDZAC5USqUFexGimlJKYefRMwAAh6lGiTtDVyetqn1dWmlf1C5Mdq8nrS/HZcrQwX9AFQrfDJrvcEZ7UGPoKh9b1SzXxvK+hmL48OHFe/fujcnOzo7u0aNHnwkTJiT16dMnY9++fdGJiYn9jh49GgUATz31VIdevXr16dWrV5+nn366PaB9eFV1zMyZM7scPnw4Ji0tLeOee+7pMnbs2O7/+Mc/WhrXHT16dHcjy2Jl7dq1TVNTUzNKSkrkzJkztpSUlD4bNmyIXb16dUJmZmbvq6++umfPnj373HrrrUlG5uLDDz9sPnDgwLSMjIz0kSNH9igsLLQBQGJiYr+HH3640+DBg3u/9dZbrcaNG5dsrE27bt26phdeeGHvPn36pA8fPrzXwYMHmwBaBuXee+9N7NevX3pycnLfzz77LB7QAsKpU6d2SU1NzUhNTc145pln2vs7j9mIESOKjx8/7t7u79p33XVX1wsuuCCtV69efb755pumvuf65z//2aJ///5p6enpGcOGDUs9fPhwlNPpRLdu3frm5uZGAYDT6URSUlJf4z2sLcOGDSt95JFHcl9++eX2gff29n//93+Hn3/++Y5ZWVmxCxYsaP/iiy9WWkZr0KBB5+x2O/Ly8qr1vI4ePdokMTHRPeZkwIABZXFxcX7/TBQWFtqysrLiFy5ceOCjjz5q5W/fmoqNjVWvvPLKkdzc3Gir9ZATExMdCxYsOLBw4cL2RvbS0Lx5c1e/fv1KsrOzY+bNm9f+5ptvPmEEcwDwm9/8pvj222+v1hCMYLtctwIoB9AXQH8AfUWkWqlAopo4W+7JSplXSWhsE6CNOCmuid20zXtgmzbzNFIBnXUg5nvf6Qpch87MqCfo8pnl2tje3+qqqKjA559/3rxfv36lAHDgwIHYO++888SuXbt2pqamumvHrFu3ruk///nPNhs3btyVlZW1a/Hixe2+++67OH/HzJ8//4iRqXjttdeOTJkyJf/tt99uAwAnTpywb9y4Mf7mm28uBDxrgxo/O3bsiLn88stLrrnmmtMPPvhg4n333ddl/PjxJy688MJzALBt27ZmL7744uHs7OwdBw4ciFm8eHGro0ePRj377LOd/v3vf+/ZuXPnrkGDBpX8v//3/zoY7YmNjXVt3Lgxe+rUqe61QsvKymTGjBlJK1eu3Ldjx45dkyZNKnj44YeNIvVwOByybdu2XXPnzj389NNPd9afV7uDBw/G7NixY+eePXt2Tp48+USg8xiWL1/e4qqrrjodzLVLSkpsmzZt2v3SSy8dnDp1anffc1199dXFmzdv3r1r166dN91008mnn366o91ux0033XRiwYIFrQFg5cqVzdPT00s7derk8D3e8Oqrr3YwXvfly5c3N7ZPnDixh7H9nnvu6WK1/9ChQ6tcH3DIkCEl+/bti63q8ap069atYtq0acevuOKK9Icffvhohw4dKhUm/vrrr5vZbDZlPK9g2zR16tSCv/3tbx0HDhyYNmPGjM7btm2LCdSepUuXtrziiisK+/fvX9ayZUvnf/7zn0rBtS/ji4zxY3wZ8CcqKgrp6ekl27dvt3zNMjIyyl0uF3JycryC2Ly8PPumTZuaDRw4sHTXrl1xgwcPrpRVra5gu1z/AAAiEg/gTgALAXQEEPBFpYarpNyBu9/Owt9uvQBt4yPzT8EcBESJzbQ9Ipc7bxmvgzkDp+AdZEW0yxXKOxvok6FzFzb2s1SF0Tbzt8iqlgxrbO9vsIyF3QFg6NChRQ888EDBwYMHm3Tq1Kl8xIgRZ333//bbb+Ovvfba082bN3cBwHXXXXfqm2++SRg/fvzpqo7xdd111xU/+OCD3XJycqKWLl3a6rrrrjvVpImWrKqqy/Wvf/3r0QEDBqTHxMS4Fi5ceMjY3q9fv7MZGRnlAHDzzTefXLduXXxsbKxr3759sUOGDEkDgIqKChk8eLB7nMXEiRMrLR6/devWmJ9//jnuyiuvTAW0buN27dq5Mzjjx48/BQDDhg07+8gjj0QDwNdff9182rRp+UbbO3To4NywYUOsv/M88cQTXf74xz92OXnyZNTatWt3BXPtW2+99SQAjBw5sri4uNjmOy7sl19+iR47dmyX/Pz8JuXl5bauXbuWAcC9995bMHr06JQ//elPx9966622d9xxh99VksLV5eorlC9Ts2fPPj5nzpzEGTNmnDBvf/XVVzssW7asTbNmzZyLFy/eb9O/yAXbpmHDhpX+8ssv21asWNF8zZo1zYcNG5a+du3a3YMGDTpX1THLli1r/cADDxwHgHHjxp1csmRJ6+HDh/sNmoLtcvUV6DUzP56VlRWfnp6eYbPZ1AMPPJCXmZlZ6Tn0798/rbi42H755ZefWbhw4eFg2xHsLNfpAC4FMBjAQQBvQZv1So3YC1/+jP/uP4HMOV9GbDF1c+LGHNw1ltmtBqMr0/y0zStFAFqyLlKBkG8R40oZuiDKj1iOoatqybDG9fYGzTw+x6xp06aWobS/D5qqjrFy8803n1iwYEHr5cuXt37rrbcOBNr/+PHj9pKSEpvD4ZCSkhKbEVD6Ls+tfQlRGD58+JmPP/74F6tzJSQkVGqnUkpSUlJKN2/ebFl1ITY2VgFa9sTpdIp+DEREVec8c+bMOTJx4sRTzzzzTPs77rij+44dO3YFOsbqOZpNnz496YEHHsi77bbbClevXp1gZBBTUlIq2rZt61i1alXCpk2bmq1YsWK/1fkjbcOGDU1TUlKqDJT8sdvtlZ4vEHzg5k+LFi1ckyZNOj1p0qTTEydOxMqVK1tUFdDl5eXZf/jhh+Z79uyJmz59OpxOp4iIeuWVV47Y/NTKrAmHw4Hs7Oym/fv3txzfuXPnzmi73Y7ExETHli1bLL8Epaenl27cuLHphAkTTgPA1q1bdy9cuLDV6tWrqxzaYCXYZxYH4H8BpCmlRiil/qyU+ro6F6KG59TZqlcFCJeqgjh/maCGyGodVN8gy/hwjITKhYWr6nKt3hg6d4bOd1JEfYjo4ts7UHikSdh+4ttX2b1WU1deeWXxJ5980rKoqMh25swZ2yeffNLqV7/6VaXB7mYtWrRwnj171uuzYdq0aQWvvfZaBwCwyij4uuOOO5Iff/zx3JtuuunE9OnT3d1+27Zta7Z79+5op9OJDz74oPWll15adMUVV5zNysqK3759ewygzWjcunWr35R///79z508eTLqyy+/bAZo3aBZWVl+uwmvuuqqM6+++mq7igotmXbs2DF7MOex2+144oknjrtcLlm+fHnzQMe88847rQBtUHtCQoKzTZs2Xl2PRUVF9qSkpAoAMLqyDXfddVf+5MmTu48ePfpkVFStDp8DAPz4449xzz33XOf77rvveK1f3I8vvviiWX5+vh0Azp07J3v27IlNTk6u8gNoyZIlrW688cYTubm523Jycrbl5eVt7dKlS/kXX3wRsAu1OsrKymT69OldOnXqVD506NBKkxdyc3OjpkyZ0u3OO+887i+QnDlz5vH33nuvzZo1a5oZ23z/HwxGsF2uz4nIcAC3A1goIu0AxCulLL9RUeMwMKkl3t94BNFR4f3GY2YO4pwW2brisrB/Bp6XjOfrPY7QZzkuRC6x5TsBw/dvUzBryfotW1IfAjhf9aBm3PDhw0tuvfXWE4MGDUoHgNtvvz3/kksuKc3Ozo6u6piOHTs6Bw8eXNyrV68+V155ZeFrr712pGvXro6ePXueGzVqlNdzNsbQGfdnzZp19OzZs7aoqCg1bdq0kw6HA4MGDUpbtWpVgs1mw8CBA4tnzpzZZffu3XFDhw4tuv3220/b7Xa89tprB2655ZYe5eXlAgBPPvlkTv/+/cuqamNsbKx69913982YMSOpqKjI7nQ65d577z3mL9j8wx/+kL9nz56YtLS0PlFRUWrSpEn5jz32WH4w57HZbJg1a1buvHnzOo4bN+6Mv2NatWrlvOCCC9KKi4vtr7/+eqXPyMcffzz3d7/7Xc8OHTqUZ2Zmnj106JA7eP3d735XOH36dPvUqVNP+B4XrIkTJ/aIjY11AUDr1q0d33///R7A0+1p7Ldy5cq9gKcLsLS01NamTZuK55577pDVDNdIsGpT7969KwVqe/bsiZ0+fXo3AHC5XHLVVVcVTpo0qVJXvOH9999v8+ijjx41bxszZsypJUuWtL7mmmsql03QGWPojPsTJkwoeOKJJyoFtxMnTuwRHR3tKi8vt1166aVnPv30U3fGzRgW4XA4xG63q9/+9rcnnnzySb/ZyaSkJMeSJUv2z549u8vdd9/dpE2bNo5WrVo5nnrqqWrN6pZgvtGLyJMAMgH0VkqlikhnAO8rpS6pzsXCLTMzU2VlZdVlExq1z7bnYdo/NqJv5+ZYPePSiFwjv6gMFz7zJQBgwkVJmDO2HwBg65HTGP3ydwCA/c9e6+7ya6iueO4bHDhRgsxurfDBvcMAACmPfYJLUtrg9ouSAQAPLduMfl1aYOnki8J+/R7/8y9c1qsdJlzUDQDw5a5jeHeDNrSjY/MYjM/sir99vRevTRiM3/TtaHmO7/YW4LYFP2LMwM5YuVn7OzXz6lTMX7MHdw/vjj9en4Hk2f8CAPz0xFVoHaFxmcEQkY1KqUzzti1bthwYMGCA33FNDVVRUZEtIyMjY/Pmzbt8M07BWr16dcL8+fM71FaZk7owZMiQ3vPmzTtsNYYtGP/+97+b/uEPf+i6cePG7HC3jRqOLVu2tB0wYECy7/ZgUys3ABgN4CwAKKVyAdRKcUc6f9XGTETllaEzd7969qloBP2vxmQI8/OuVLZEnxQxfO7XuOvtDWG9vkt5Z+XMXa5XZ3Rw3z9zrsL3ULcKPcWaEOvpGLCbMnvmbteG/47WHytWrEhITU3tM2XKlOM1DeYosMcee6zjLbfc0vPZZ5/Nqeu2UP0UbCd9uVJKGQNKRaRZoAOo4XN//kYwOWYOYMy3zeUxpBGUFzbiWuU7ptBrDJ32+JFTpThyKuhalEFcu/IbbR4HFx1ldwfbjy7fivGZXas4j/Y7PtrzZ8dmGkPXmCe9nM/Gjh1bNHbs2G2hnuf6668vuv7662ulK6+urF+/vsaZtWeffTbv2WefzTNvmzVrVseVK1e2Nm8bM2bMSaO4byTVxbWXL1/e/PHHH+9i3ta1a9eyNWvW7IvUNRuSYAO6ZSLyGoCWIjIFwF0AFkSuWVQfuEtoRPCzt6oPeXOR4cbAPYbOt2yJaZ9IzXK1WpXDnKGz2zxBn784zGi7uXvcs/SXT/B+ftYtcblcLrHZbOdl46jhMa/M0BiuPW7cuDPjxo2rdtmQxsTlcgmq6MQIqstVKTUPwAcAlgPoDeBPSqmXwtZCqpdWbdZ6BixmqYeNq4ouV3+zKRsiY0KIZw1bqxIgwc9yffnrn3HJX74Kal9PuRHPNq+ZqmKzLFVQ+TyVj42ya3+CnMpV5Xt9Htmen5/fQv+DSkRUq1wul+Tn57cAYLkEXdDzopVSawCsAQARsYvIbUqppeFpJtVHX+7SJv9E8qPXHJ+YP+TN9c7qRYmLEPlmwKyCI5HgM3TzvtgDAMg9XYrOLf0v+uLOrFWxlmuUPbi1V93nMc+Wddeh883GBj5fbXM4HJPz8vIW5OXl9UXw44+JiMLFBWC7w+GYbPWg34BORJoDuA9AIoBV0AK6+wA8AmAzAAZ0FNGF1Jmh0/h2ubozdKZ9BFLt0HbJfw9i1kj/yzK768eZtpknxVnC7QAAIABJREFUFTtd3verYnSjVlWHzlVF8H6+GDx48HFok8OIiM47gTJ0SwCcAvBfAJOhBXLRAMYopTZHuG1UT0Tyw7eqcVVeGbrz77M/7FzK+rdXQCfVn0wQzHtn1eVqztAp38F8Fv7+7V787au9lY71jKFTPrOYG8GbSkQURoECuh5KqX4AICILABQASFJKNeiZSlQ9kQ3oTFk5r2xd4ypsYQSzvpk632W0IhEHeYJH6y7XJjYJWGbkr595Jv/ZvAJD7beCxQxeIiIKWqBxIO6iUkopJ4BfGMyRr0h++Jo/5M1ZuYpGO8tVu2/VDeq79FcwEyTMNeECXVssAjHA021qCBTg+2boRD/GK0PXuOJ1IqKQBfprPkBEzui3BUCcfl8AKKVU84i2juqF+JjIrTlojg3MpUoKS7XvGr7BREPlW4fOmAjiO7m0UuFhn8eveeHfOF1agfYJMTheVIaOLfwuf6mdxyK4cvoJFvMDnNc3MLSJwOkzhq42ilYTETUkfjN0Sim7Uqq5/pOglIoy3WYw18hldNL+CTSLaEBnPRGi6Jy2hmu03dYoxtA5fbparbtBvWf8WmVOd+cVIa/Qs0zlLwVnA17bEzx6rlVS5r1ggDnTp5TCztwzVQZlviVORO8qVlV0rxMRUWCcek81VhvlQsxdb2UOTxBh7gZsDGVLPLNbve97rxQhXsHtzqNnEMjfv93n9bpaX9s4v2ebuThwxxax6Nku3n3/3z8X4NqX1mHpjwctz2fuchUR2ETgUi6fMZIBm05ERCYM6KjGrJajCjdzlulchedTvrF1yZnrzymlrMfQwft1OXKy6uW/jheVuW8XFJf7vbY7ePZqj7YtuU1TtImP8dr/gJ71+/ce63XsfWvnGfXzzF2upRUOv20iIiJvEQvoRCRWRNaLyBYR2SEif9a3dxeRH0XkZxF5T0Si9e0x+v29+uPJkWobhYdv918kmOO2cxXmDJ31Pg2VO0MH5dU9KT7ZLvPrYgvT+EKrGbWG5rFNqjzO6Bb35VXPDqIFdC7lVZbmRIAgk4iIvEUyQ1cG4Eql1AAAAwFcIyIXAZgL4HmlVC9oNe7u1ve/G8AppVQKgOf1/eg85qrlDF1jXrzd6HpWSivxYRVEa2VLPA+UB+hKDZY7G2iKxJT7d9Xvw3/3n0BpeeWgzjwW0tPl6v2eBuoGJiIibxEL6JSmWL/bRP9RAK6Eti4sACwCMFa/PUa/D/3xERLMApFUZ4wP4EhWEPFdjN6z3fN4YwjtzGPotC7XyrNcfTN0B0+WhPXaVv8zSoCKwgcKvNsQZRMktW5qPoG7ILJXEenG8KYSEYVRRMfQ6Wu+bgZwHNqyYfsAnFZKGV/bj0BbVgz678MAoD9eCKBNJNtHoTEyLZHN0HluexWe1R84V+HC2Sq69hoKZQpafbu5bT7j0czvxHx9vdZQeSZFVE7RWb3zr67d575d7vTOtDlcqlKpGS1Dx5UiiIhCEdGATinlVEoNBNAFwBAA6Va76b+tvupX+qsuIlNFJEtEsvLz88PXWKo2z6SISF7Dc/KTZ911rr0+8IvLK9CQ+Y4XNK+qYM6Q+U6KMMrKhHx9vQHB/rEw/3Moc1hMVxXvmzYRuFw+ZUsaWeFoIqJQ1cosV6XUaQDfArgIQEsRMYpWdQGQq98+AqArAOiPtwBw0uJcryulMpVSme3atYt008kP32WoInMNz+3C0gqU6wFCOLvnJr21His25YR2kgjy7nbWJkW4LL4G2XzKlvRNDDKgC/D++RtDZ52j87AK6Hy7aQVWXa4M6IiIqiOSs1zbiUhL/XYcgKsA7ALwDYCb9N0mAVip316l34f++NeqsdWmqGdqY5ar7wd77mmtFIdX92sI2ZyzZQ6s3ZOPB9/bXONzRJr3ZBDtt7vYr2k/Yyya+36Q5w/06rksIrr0TgkAgNT2CX6PrQhQUE5E6zZ2Kfh0uQZoFBEReYlciX+gE4BFImKHFjguU0qtFpGdAN4VkTkANgF4U9//TQBLRGQvtMzcLRFsG4VBbc9yBVBpLBkQ2qoCpRXn/2xK89PTxtMpy3FtNhHviSNBnj9QNsxqUkSnFnF4dcKggNGgcer4mCgUlzkqnQcwJnMoy8CViIiCE7GATim1FcAFFtv3QxtP57v9HIDxkWoPhZ97XdFaqkNnvqbXGq8hfPq76kHkYM5cabNcPe2uXFjYc99qDVZLAV4C86ocZlG2wAl+z+xc00V8zmOs5WrexeniUhFERNXBlSKoxsylQyLFvO4oYJ2hC+Wzvz6sGeq3/p5PROe9lmtwL0ygV6BC79K216CKkHvijGmb+Dxus2lBq/fSX+f/+0JEdD5hQEc15lm9IHJmvr/F+5ruUinmdtQ8oqsPgYPVqhhW3aA2iM/rEuz5/e/o0AO6mqw8EUywL3qGznfyBxERBY8BHdWYEVzV5oxEq5m1oXS51oMEnVe3sFayxLo2nO+kiGCfW6D9KvQUqL0Gfy2sStuY26xgTIrwXvqrHsTZRETnFQZ0VGMuiw/rSPPNUAGhrVRRPzJ03l2u2qQIq1mu4tX9HGx3cqCeVCNDZw9izJwv8xq0VbHBWPrLdJxP0vV40Tm8s/5Qta9PRNRYMKCjGquNOnTDU9p63TcG15eb6puFMrGhfoyh89w2JkVY1YaLWIZOLz1SkzF0OadLUVzmqPoaSl/hotIsV+8DpizeiP/5cBu25xRWuw1ERI0BAzqqsdpYKWJYivfqb0aRkcJSz+oQoWTZ6sMsV2XKxhnLgHnWcjWVLYH4n0BRhRPF5X4fNwK6qABj6B79Te9K2579ZDfG/f17vyPibPoatOb3wrcbvaCoDABw7Iz3JBkiItIwoKMaq40MXVVlSw6e8Cz6bg7o7ly4Hsmz/xX0+etDhs5oo80mplm+2m9z5TkR3xU0vJ9bVcHrV7uP+b2+0eUaqEyJrYoMXvaxIq+g1ExBuTOL3l2u1m2tQZKQiKhRYEBHNVYbs1x9s2/GwgMl5U5ER9m82gEA32Rr6/sWlgS3vmv9GEOn/bbrBXiN4sKAz1quAr8TC3yD17uGJQMAurdt5vf6DmNShN1/O/0FW8rPPnabeI0LBKouVu27bBgREWkY0FGNmbtcI7VaRKWVIvT7Tpdyj+myCsqCLXvhuwrD+cgI0mw2/bWGZ9KA9yxX8RsU+b5OTWPslvv5CrYOnd+HLWbluo+D9nzMASfLChMRVU8kl/6iBs68CoBSkekOM4KZ2CY2nKtwuYMKl1Kw62O6QpoUUS8ydJ6AqsKnVIzXpAhY16zzPY8hWk+5lTsCBXRG2RL/b3BVXa7maxun+Ou4/sg+VoS4aDtsNoHT6fIKLOvD+0JEdD5hho5qzGoVgHBzKS0IuK5fJwBaYAfoGTojoAulbEkNZoXWNuP52WxGl6t1W20+GTrfLlbfiQZRdu31O+fwv56tewxdgEJ0Nj/doZ4xf9o+rZtF4+IebRBls0H0siVOr+5i68wsx9AREVljQEc1ZnwAGzMvI3INpSAi7kDAqDlnztA5Q1gpwrdo7/nInKFTAKA8XcqVypa4qg5QfTOZRnzmDPDyGYWFA81y9RdsGZnVy1LbVnrMJlpbnX7G/xmYuSMissaAjmrEHMRFcgzd9pxCOF3KHSx4jaEzAjqLgCTYwfP1IUAwnrPNJu4JEb4ZL4O/Wa6+z9U4NtDSaZ5ZriGMoQNweWo73DS4S6XtNtGel7mYsCuUBXqJiBohBnRUI16TCSJ0DadLYd3PBQA8Y6+MbkOnMk2KCCGY9O5yPT+DOyNgPXm2HC4F7Dx6xjSGztNm3y7XSpMifO7bJLgua/cYukBdrn4iOu39si59YpRbcXp1F3vvU663oTaXmSMiqk8Y0FGNVF6OKvzOljvct40SJSX6Nq8xdBYRSbAf/LURmIbK97l89FOOZ6UIn7IlyitD53Men6SXEX8FmlRSUc0MnQjw64wOFo9bH2+TymVLfNtUoBc/ZjxHRGSNAR3ViL/ZlOFi7gls2TQaAHCiWKsv53J5Agyr4C1QsVyDv4H454vK7VKWkwTEZ1/fLlaHT0Rnk6pfP6/jglwpwgjYWsQ1wf/f3pnHyVHW+f/9VHdPz525J/d9E46EgNzIpYAiHojgcriLoqvueuz+FN1VQV3FddUVdUFRFEQOERXkjtxXyEUIOch9Z5KZJJO5p4+q5/dHVXVXdVf3HJmZzCTf9+vVmerqqnqeqppOfeZ7XrlwQtbnRo79DacHbb4aei7D9BYJgiAccUTQCf3C59pjcB603jEKHHdf3MnINL1JEQFP/0VreynoRkKWa1Y4mUrH0GVoJO8pZLpcM4+T0lc9uVzdOng9xMi5H+cSfrn2D4VsV7GpexbXI6GzhyAIwpFABJ3QLzIL8g6G09X7UM8Ub5alUxafoId8b5/7I6GXa5a4UZ51Oq2SmtpjGfv5d8u8Tu6ePaUfJE2LkKEwemj9VVlcQGVxhNOmVgd+nqswcdhQNLbF+PeHVuWcqyAIgpAfEXRCv7AyLFuDY6Gzf54/uzYl6JIBnSKszAh6eu8+HUku1wUTKwAoKQilY+g8Gml0eWHGfv7jZGW55rFwekladkJDT3nDBWGDH15xIu8/YUzg57mSJoIKFmtfxmvu2DpBEATBRgSd0C/MDJfrYOC6DMsKIykxkExaqZIp4TyCpLcP/qGIBTxc3DlOqCoG7OuRjqFLi6Hasqhvv0yracLsbwydbQ3Nl8XqJSiTFezWZcHbZx/XOydvQWRr2KauCIIgHFlE0An9wmdBGbQ+rvZPBb6+ra6AC4Vyl93obRWzzGzd4UiqsLBrpTQt37VxyRRcmaL2589t8r13dVRPp21adsu1w+3S0BcLXa7kDilPJwiCEIwIOqFfZLpcB4NUNwTS1p2klQ6ez1eH7oX1Tb0aw2v9GU5yrjth0h6zS7S4wizsiRl0r02+RIVMobtiR7Pvveqthc7SGKq3pZpzk6tsSZBFzzt3b3bucK0VKAiCcKQZNEGnlJqglHpeKbVOKbVGKfUFZ32VUmqRUmqj87PSWa+UUrcppTYppVYppRYM1tyEw8ef5aoHNYZOqbS7L2mlOwpYnng6l2g4/SvdG7dr0vSKhcOd8cDxvtteZt63nrY7KDjz8nbG8F4bl6yM1xyFhFPbOz8bWrrzzsV0ElByCbLekjPLNSiGzjP3hCdGUpIlBEEQghlMC10S+Det9RzgNOBzSqm5wE3As1rrGcCzznuAS4AZzutG4PZBnJtwmGTGng1KlquVrrXmdTeaGfFjpseC4xUtvXn4+xrWDyOtsLmpA4DOuJntcrXSRXjzuVyzkmMzdJOrox5b1ZB3LraFrufWXj2RK/kiHMo+sPfetXUnUsui5wRBEIIZNEGntW7QWq9wltuAdcA44HLgbmezu4EPOsuXA/dom8VAhVIqOF1OOOLooXC5euLEDI971RUGxZGQsy69j1cc9KZP69u7WlLLwzGGzivewsr+upqmlb7+GYWFvWQmEEypKfG9763FzRwgl+vSbc2B64OSIrwxmm6XCBie90gQBGE4MCQxdEqpycB84A2gXmvdALboA+qczcYBOz277XLWCUNIPGlx27MbaelK5N3Oq5XaY8kerTz9IfXwVspvnbL8FivvQ76mNJq9fx5+v3h7ank4uvNMK50A4SaBJC1NgJ7LEmiZCQTvPW60731vLW6uhe5wFd3JkyoC1wcmRXjE6OrdadHdG5EuCIJwLDLogk4pVQo8DHxRa92ab9OAdVn/eyulblRKLVNKLWtq6l3gu9B7nl23jx8v2sA3/ro673aZYukrf1qVY8v+43Urus/8pOlJikj1cvXs4zzwS6KhPo+XNLNTKNu6EyzbdrDPxxoouhNpl6u3TIsrbLzttDK/QJlu8MyYut4KOtOyel2yxMsPPnw8p0yuTL2fXlsauJ3bBcSLd6rdCTO1LHpOEAQhmEEVdEqpCLaY+4PW+s/O6n2uK9X52eis3wV4G0COB/ZkHlNr/Sut9UKt9cLa2trBm/wxSpuTWbm3tSvvdkNhKfG2twrlETPeubhiz7L67gpOBpzT/72wmSvueJ2NjW19nf6A8Nc396REquEU97XdsPbnobxJEf73mafX2xIgbh26vjpdq0ujnDQhbZULssRBuk+vb26+cjLp9Zm/dz/9+0ZufXJdn+YlCIJwNDKYWa4K+A2wTmv9Y89HjwLXO8vXA4941l/nZLueBrS4rllhCEm58vI/vIfGO+kKGRUYQxfylPFwcT9ziw/3xJnT022qMpvXAzy8fBcAmxrb+z79AeBPy3f5s30NRTxppgsL4xV0mUkR/ivwrUfXAPCF86fzmXOmBlrGgjAtjepFp4ggvPorl5Wvojjie68y9vOKu0hGAsVP/r6BO17cIh0kBEE45hlMC92ZwLXA+Uqplc7rUuBW4CKl1EbgIuc9wBPAFmATcCfw2UGcm5CD3marBsWnfeb3y5l80+MDNpcgMZA0rZRoC6dcrt4SF7Yos+hdzbJ6T7usIKtjc6cdkH/4KQG9x3s+picpwnAslXGP29mrkTL1Ui6NU1YYYeHkKoqjYSIhRU1ptoXMi1uHrj+XIKgfbybeuEewLa/ea+C9jwFd3gDoiCd58u0GqVMnCMIxS3iwDqy1foXcj4ALArbXwOcGaz5C7+h1U/uADZ9asxeA5o44lSX5RUJfxvAWFk6YOquMh3cuHRnFeHvCexpmgFpI10AbOqGQ8FgKk5blcbkqomGD7rjpc0e7GBlft1xJIV5dlTA1+9vj7G+PZQmr/e0xfrxoA53xZMrd21fmjR3lGTf4CKOKIpwxrZrXNh8AbDey9w8Ln7Uux339zmPr+OOynfzx06dz6pSqfsxUEARhZCOdIgQfQS2l8m0XRH8C6APHcHSNUulYsc54kn9/6C3fOO5DPmladCXsnezaeD3jtcoFxdClGELDT9JbSNcTL6ccQdeZSKYsUb5rnRlDR7CVMqhcyaZ92S7lW/62lvve2MHSbc122ZJ+3NdRRWl3qiu2g5jo9KkFW7zncrnmssCt3GmXRNl5sKPPcxQEQTgaGDQLnTAySbXb6uHZnc+1lasJe19JWeicsiVKwUsb9nOgw3aDuiFgrvux08mGjIQUSbN33StyNYHPZChLmvgFXXqOBnYnjFgi7XbO5XJV5LG2BtzbIFf7k2+nQ1hjycNvolpamPu/G28tOkMptIafLNpAd8IkGklnLOe6D13Ovdd66FzjgiAIwwmx0Ak+0s/L/A/GfMasw20RlTkXRdo65Yo58LfCAuiM2Q/1wkjItk71wu3qy6bMo1mGsv6Z1+Xqi6EzFCHDyJnl6nW5Go7bMlj/pFded/okAKKR7P8KvAK3p/ZgvWGCxwqXScSToKGUfV9++uxGfvmSP+GhJ1f6QP0xIQiCMNKQ//6EPnOoM847e+2SgqdPzY5XGqjAdK+FDvyWK0g3dU9Z6OK2S8/t55rUPVuVvCIuKMvVZSgFnfc8k9ryJUWEDeUTebksdIaR20IX9qieoFp+QVQURfJv0AvyueJ9gg6VkQjRs6BLz1+SIgRBODYRl6vgQwcIhUyuu2sJq5yWWVNqSnl9y+AU3nUfze5cMl2irkDQKUGXttAB/PdT6/nQ/PGcPq2aXJjD0OWa8BQ4tiztiSVUhA1FwtMtw3ubXCEL9rXZc6iLpvZYKpN3Zn0pCn9mr2vV6+n8zshzDXvi9KlVnuSSYArCmRY6z4fexJUch9l9yK6b2NvaeoIgCEcbYqETfPTGErXK0/80SPgNlPRJu0NzZGu6MXRWhqBzxMEfl+3i6jsX5x3DZwnKJ+iG0kKXkajhzfYNhZQvUcJr9ar0FOg1lMLScPH/vpRaZ1qacMjw7eOGrmWeXzwjZs4ruPrKDWdN5cazp+bdxltfLmQoX9eO3ljoXLoT5hGrGSgIgnAkEUEnpIglTW7+21ogfwSdN3NxoDJagwjM5PRgKPvlCh63RVRBOB1En6v2mYuvy8QwEXRd8XSrq9Jo2BdDFzYMu5SJZ52L123pit3mznRPXtOtJ+fBdWdnCqX2jIzUSC+LEOfC6OE+eC14JQVh3/i+OMcexvnPR9Zw4Y9f5Ncvb+nXPAVBEEYqIuiEFK87dcAgOEjepdJT2V8pzYcXjPN9PlDeyUwNddb0Gt975ZTScI05bgyc15pkWprJNz1OV46SGd4x8sbQDaHL1XUfAhw/bpSvlEzYsdCZzly9BY/DIa/lLVtAmVqTqatyWegya9gdjoWuN3jHL4wYqfIzkFErsJc+1QeW7hywuQmCIIwERNAJKbyWt3xtoby9NxWKi+bU93ms7z62lk/dvSzvNqk4MUd0BIkRr4UunrR/ZraHAljd0Bo8htflmifOy+ohBmwg8bobw4bhK6TsJkWYnhp96W1V4LKLZWULvZSFTmdu618RdE0HkipPIeqQ4U+KeG3z/vS8eimsq4oPP4lDEARhJCGCTkiRIw49C7+Fzu/WVD3t7PDrV7ayaN2+vPFOacuUcsbK7FWqnFgxp7CwY70Jcg/Gk2bWOnuM4GzKTPIWHR5gEhmtzLxdIRSK/e1xvv2Y7Rr3lukYlSMT1bI0DS1d7D7URUfcb6nMtNA9vqqBv765O0vgDbbLeUpNCZ89dxr/ev50Qso+R5d1DW2p5d4mPcSSFlrb1tnvONdKEAThaEYEnZDCaxXJ9/wuLkgnRyuV3a2gt/1gAX79Uu5Yp3TGrX38TKNTW3cCRVpsuNmhQdbFzJInLr4YujxWuKEtW5JWLXHT3/qrpSvh29YrcsO+Wm7p9XHT4q5XtgKwIaMjhFvXz7WCfe6+FXzxwZUs2+7PXK4vK2SwWTCpkhPGV2AolRXD59JbC50Guh237W+ccxcEQTiaEUEnpPBqls547jZNXnGjMivz91L3uNaksZW5hUKqbEnqZ6aFzt/I3Q2sD3IP5iqb4YuhyyMWjkSWq8IWd946dJnn1ltPaFt3MnVML25m8Js7DvnWf/6+N33vB6I3b29RAf8rufP23oZ89Q61zk7sEARBOJoRQSek8D4fX910IOd2XvdjlhuUnpMi1u5pTVmawnlK+3uFDGR3AbA7SKRdpa4VLhIQwO+1evnGsNKJAvlqpQ2ly9U9j4KwQcL0ligxKCoI+bbNFLnp9Wm0Ts8/nKEAT59q15dbOLkSsLNqgxjMbObejOVmyb6wvim1rjMe7EZ3EUEnCMKxhAg6IUWmOyuzFpmLN9PQDOjG0FOniKdWp3uE5nOheZvSQ4B4cdy9rlbL53KN5xJ0WqdiAJNmboGQy2U7ELR1J/j94u2p6+bGAkbDBnHT8hV7rijyW8p6o7M02ue29eKeuyusc92PQc6J8BEk6AqdrGuvhbIjj2DTQLtjlQxKEBEEQTjakE4RQgrvwzyXpQYyrFUBz/+e4tZjprckRW6h5NaVS7lcM5/L2v7MyoihiwZY6BI5LGyWtkVNwtSpLNkg8pU0OVy+89ha/rhsFxVFES47cWzKUmhb6KyUu9dQUFniT3wI5bBwei1xPgudESzokpZFwrRyWr16quc3kAQNZSjFmFGFPovw27tbsjdMoWmL2VbgIIutIAjC0Yb8TyekcLVVeWGYwogRmNxwoD3GyxvTZSS89cJcegxc93ycz5P5mXuX2wvOMzxL0Cl8Wa6uEAoUdDmtjWkLXSKPaBtMl6vrft7S1O7MyRWmIZKmvyvEuTNqOWnCqNS+uSx0XgEWS5ppUZgp6JwDJEydirMLYgg9rllufLB/BSIh5bMaf+nBlTmPoTV0xJxC04dZFFkQBGEkIP/TCSnSMWsKrYNj4TILtrbHElnb7G+P9X7MPELJHb/ZycTMdMVpbVtz0jF09sN+b2v2+Plcrq67MTPLtcXTZWEwBZ3b2cIVK64wLYwYJCx/UkQ0EuLz581I7ZvrC+yNTXxgyU4ef7shcDt3s6RppVyU58yoyd4uKFNhkAiy0CmlCBmGr7TMiRMqgNw18tzfzcGuoScIgjAcEEEnpEhbgnInq2bG1Y2rKMraZufBrqx1OcfsxTatboZmhqWuqqTAttC5LlfLzXLN/rXuzBFv5bXQZYq21u60oEvkEIQDgWtBcmvEJT2WxkRSewos504WyMSrYe5fuiO1XJWRreqe+3PrG+lyXNxjA+5p3l5wA0xQDJ1yi0h77lFtWZTK4ghTa0qytre0TgnUw21bJgiCMBKQ/+mEFKneqRmV+r14Y7Du+IcFLJhkZ0eeM6MmJQ764uLKVw7korl2B4rjxpb7tj1reg23fvh4Tp5UiTJUSojGkxZhQ3Hm9OqsY9361PrAMbQmp6CLeYoR50oQGQjcNmtu3TTTslA4LlfLSsXv9SXTNOS5B3GPW/y9c/1dPaKOddDSpARdkAAaShtXoKDDvk9eC92+lm5KC8Opc/BiWdDmiHhxuQqCcCwgSRFCCu2J1cpVk81rEfIWsr3u9MkcN7ac21/cklOkrWtotT/zPK/zxdvVlkUpKwwzudq2wLjCK560qCmN2vPxHKM7YVIQNiiKZD/gc2FqnYojyxR03R4hNBQWOneMhKUxDEUkZCdreOvSZZKrbEl5Yfqrva8t7YI+cXxF1rYz60tJmBZdcTfmLNhCNlQEjaWUIuRYYy3n+uxt7aY8GgnskNHY1p2y0A1lQocgCMKRQv50FVL4YugIjqHLVwLCjQXLVfPtkp++zPt/9orvuPnyJ7TWvod7KNAVl7bQdSdMIiGjT2UqfC7XjHnHPFa57Qc6e33MvuImcSRMzdu7Wti4r42QUhSEQ3ZhYcupuRcYXBZ8zI/MH+9r0eYS5KKNGAb7WmPc+uQ6Zz4hrjplAtGwwZcunMEnzpgcaAUbLHqy0Glgz6EuNjd1UBwNBWaxNncm2H3Idv33truEIAjCSEYEnZAiFUNn2A/BoCxXV3wUF2Q/4F2t0FMCga/dVp5tLQsMjw1q3jg7u9MbM2UU9B/FAAAgAElEQVSo9AM75rhcvaLlpotn551L0rRSQfP5XK7LtjfnPc7h4Lo440mTy37+Cn9f10jIUBQ4FjrT0jktZLmka2lhOPDcg46zvz1GZ9zkrV12GZCCsMGFc+q57ar5HDd2FGdNrxlSK5c3dtFFKbcriC30f/i07ULfebAzJeAzs5ufX98I5M+kFgRBOFoYNEGnlLpLKdWolFrtWVellFqklNro/Kx01iul1G1KqU1KqVVKqQWDNS8hN5lZrkGUOPXpPnbK+KzPvDXNejNO5nLQdl4BMq22lNv/YQHnzKxNrfO2/oqbFiFD+Sw8NaX5W1aZlk65jk0rt4WuprQgp+WxP3jFoleQuhgqXYcuaVkYKti5miuuTimodtzSPW3flpEw4hbxPVKuysaALGWlFBFDpWrl/eXN3QDMGVOeEnQlGbUTW7vs8+qp0LUgCMLRwGBa6H4HXJyx7ibgWa31DOBZ5z3AJcAM53UjcPsgzkvIgTeGTqOzRJ1laTY22rXSRpdnZ0KmYtF66KrgzVS869Vtubdzw+08uiISMnxB+wpwhzNN233q1Sxhw2DumHLGVxYFlkhJWDolCLIsdE4MXWVxhLBhZNkrH16+i6XbDtJXHn1rD7P+8yn+tHynb1yvtTJkKCIhe8xY0kKpYOtaJBwsunIJvaD1Z0zzJ5HUBAjBocQMEGAKO0P3UFeCPy5Ll85579z6lPAscoSoK0hdxEInCMKxwKAJOq31S0Dm0+5y4G5n+W7gg57192ibxUCFUmrMYM1N8PP3tft4/89eThXyNZQt7tq6kz7rxt2vb+NXL20Bgl19Rg5hlElDS7fvfWbCwZamdj533wq6EyZKqZyB/+6Y3pZZStlu2nNn1touOGXH/VmW34G8rqGVtu6E43J1LXTBLteCUHCR5X976C0+esfrANy7eDvX/uYNwG8R2ra/g9+9utW37t7F2wH494dW+c7fe90MpShwXIgdsWTOa2DkWt+HLIaPLZzgq9VWWnhkc6Vc4f2h+WN9Z1dVUoBpae5bYpdhmVBZxKjigpSgqysv5KvvncX3PjiPabVpt7xY6ARBOBYY6v+567XWDQBa6walVJ2zfhzgrVi7y1kXXA1VGFA+ec8y3/vigjCd8U5O+/6zXH3qBL7/4RMA2ORY5yA4uN59sAZZWLw8s3af771pabyJqef/6EWgZ3cp+DtFJC1tCxkF1542iSsXjicatoPm46ZdoDeEorG1m0t++nLqGGNG2YIq04LnukAjYYNY0vJZLL3u19+8spXvPLYWgI372vjg/73Kt95/HFeeMoGvPryKN7Ye5NQp1fzw6XfY1dzFxKri1L6Tb3qca0+bBMBrmw/4xnYTETrjJjk6fGUp62++by6bmtp9rb96QinFL66ezwNLdxIOG76ixEcC936OKS/iAyeN5ZGVewBSAndLUwdnT6/hipPHEwkZFBfY/401d8SZUV8G+P9okKQIQRCOBYZLUkTQ0yfwf2Gl1I1KqWVKqWVNTU2DPK1jj2m1JZQXpXX+46vSmtpNSgDoDuj5mW4j1ftYs6CSEy772+M5XY0udlIEqXENlbZOuYKotjRKc0ci1Rv21qfe8R2jqc3uRJEpRF1BVxAy0BlJIku3pZMkXDEHtvWtI2bylYdt69tmp53X1v0dPL++iY2N7akOBy6d8eyix/GklSof0hk3UQRbKjMtcROrizl/dl2fLHQAhmHw8XdN4sqTJ/Rpv8HAvZ8hw3/G3jI5c8aUpWLmjnd+L7137wMnjgVgzKhCeogAEARBOCoYakG3z3WlOj8bnfW7AO+TZDywJ+gAWutfaa0Xaq0X1tbWBm0iHAbzJ1T4XI/jKgO6BhDctSBlobM0+9tjKQGVD9PSvLHlgO99T+N48XaKME0dKGTKi8KYWrO7uYt/vf9N/rxit/8YRvDYMWf+BWEDreGbj6zhI7e/BsDLG4P/mLj79e2pZa11qiCxt0Xak6v9hmev5dPF1DplkWqLJYa0DtyRxrWohT0JLo1tMV9LsOl1panl2rIoV58ygY8sGJdad+Gceu64ZgHjKopsMS5WOkEQjnKGWtA9ClzvLF8PPOJZf52T7Xoa0OK6ZoWhxTCUL9vSmznojfEKEhiuG7YzlmThd//OJ367pMfx2mNJrv/tUh5daYusTOteTzpGedqUuQV5MykrtK2AP3tuE4++lf13wofm20Ig07DoXodo2MDSmgeX7mT59mYeWrazV3XpdjR3pvqyHnD60QKsa2jzbeeWC8k+N/tc3trZ0qOl8mjCLXBcWBBib2vadVpRZLvgZ48uo6LY746/YE49c8eM8q0LG0bevsSCIAhHE4NZtuR+4HVgllJql1LqBuBW4CKl1EbgIuc9wBPAFmATcCfw2cGal2CLqBt+t5TNjW1ZlouQoXzdBLwaYseBjvT6AHHhulx/tGgjAIu35M4Ave2qk3i3p/zI27ttURPPFHQ9iBivhS5pWYHFh92uCRv2tWV9duqUKk6eaLcvy06KcGLoQkZKZAD8vz+tYrvnWuTCsnTqfLbtT2/f21ZUY8oLU8uZlsebLp7FJ86Y1KvjjDSuXDiBkKEoLwxz2pR0Bu7M+lK+e/k8Pn3O1F67lN2aij3FdQqCIIx0Bi0pQmt9dY6PLgjYVgOfG6y5CH5e3tDEs+80cqgrwYM3nub7LGQozplRw7yx5fzwmfW+kg93vrw1tawDwuSC6pbZ3R7s9ROritlxsJPq0gIKI6GUSxE83RKSmRa6fDmuGUkROVyuroVuY4Br85J59XYmrQrOcg0bipCh6M6Y1+o9rcwZXcblJ43N6hNbVxalsS3Gef/zYmrdH5ftSi3HTYuSghCfO286//10cI9ZsN3d1SUFPuuey/S6MqbXleXcdyRz/uw6zp5RQ9hQVJXYJVSKIiFChsHoUYU97O3HcDqJZCbeCIIgHG0Ml6QIYQh5Z69tqSqNhrNqdJVGQyilqC6NOu6qYMtGkMUjSNCt3tPCmj0tqc/HVhTy2XOmYSjlc6+6i4mMCPaEaeX1u6a6Wmi752lQgmZ5QBmO48eN4trTJjK+ws44NZQibpr81+Nr2ee4+WIJu6RJLmPQur1tVBZnZ+Jm1kELoiSa7lGbC6VUKhGlrTvZo/s573gFIeaOKT+MIwwt9nW3xfT1p0/qtzUybChMK7umoiAIwtHGkS04JRwRWrrsAH03NsxLbWnaAqKUv+TD9LpSNjW2M2d0WWBJkcKAnpqX/exVAJZ/40I6YklGjypkUk22kHG1YGYMXZB1yrcfiubOBI2tMZKmRVGAGaY0mv1rPndMGefOrEu9Ny3NorV2js6ybc3871UnsbGxjXBI0XCoO2t/sHVmkacF2qmTqzjUFeeEcRXsOLgrcJ+I086rqCDkKy1y+tQqXt9ykPryKPs8nRLG9NEilclpU6tYvOUg3758Xq+E5nDk7Bn9T35yu22Iy1UQhKMdEXTHIG5sWJDlwmvNct1VLqXRMNPrSvm398wKPG5BgKBzOfk7fwcIFFwAL2xo4l8umJEVQ+fOIxeFkRCdcZN3ff9ZJlUXByZFhANi1iJ54tj2t8c494cvALb7dPvBdALEjWdP5Vcv28WVT59W7Wtaf/bMauaMHsWWpmzXLsDo8kKKC0Js2d/B9gOdGErx7pm1tHQl+OjCCby9u5Wzptdw0Zz6VCmTd8+q5YGldonGUB9qy7nccOYUrjx5PKWF4T6XMjkaKAjZgk5q0QmCcLQzMv9kFw4Lt5RG0tJZD7qIR6Ao0lX2W7oSbNvfQT5N4S0xUlkcXF+u3VNzzTv0mj2tXPubN1Jzczl3Zm1eIXKSp6abK5J6Q3me+nc7m7tSy0WRENe+K+3umzcu7bZ873H1PjfzDCemLbOnqGshzGweD3DNaZP49LlTKS+M8OMrT+SiOfWEQwblTkant8hvfwr+KqUoLyo4JsUc2H9kWBriiYHrwysIgjAcEUF3DPLwCtsd2NTWnRJ00bDBjPpSIh6BojwWuhNveYZDXYmstl2ZXLFgPGALsSBmeuqHbWj0Z50u3dZMPOmvXTe6PL/LcWZ9qe99T/3krzxlPB9bOJ5ZGft5uzd4KSoIce6sWsKGoigjkcMto/Gt98/lM+dOTWXYFnvcsLf/wwImVdvHLgin4/G8/VNdoWYoFWhNBJhSEzw/IT/u/Qoq3iwIgnA0IYLuGKMjln6wrW1oY6tTTuOC2XV8+cKZRD0uUVNr1uxp5aN3vJZa19qd/WC0tObTv1/OL1/azAVz6rjhzMmcNb0m9fmXL5oBwOTqYj7q6URw+tTqrGNd/gt7rNpetP0CqCguYJSns0WukiBuduT4UcVcNHc0JVG/he7rl8wOnI/LT648iW++fy5hw+ADJ47hhPGjUmJhQlUxCydVpSyUbisqsF27bhycpTXVTtamtzBuT/zymgV88YIZvd5eSONtnyYIgnA0IzF0xxC/X7ydb/x1tW/dW7sOAbY1LjOubK9jjfO2uXrP3Pqs4za1xTC1Zum2Zj511lROn2aLuRvOmsLLG5qYUFnML685Ga21zwJ18XGjiYYN7luyM+uYnz9vBl2JZK/KVHzm3Gn8wCkdsjVHfbhPnjWFxVsOpKxlmYRDBjecNYW68miqdyjADMeSV1QQSiVAfODEcSQtK6cLNDPb13W5bm7q4NPnTOO4ceWcNL4iaNccxzMoicrfXv3BFfjtMbHQCYJwdCOC7hgiU8yB3S4LeteF4IdXnEBFQOyZN5HhuXcaudARfadPreZdk6s8iQr+QZRSnD+7nhfWN2Eoxa5D6di1UcURxkWD245lMqOujFFFEVq6ElTkiN2bXF3SY5kQgLOn16QE3cffNYEzp9UEbtdTPNuFc+pSFrwL59TzV+eYVSUFOY8pDDwz6kv52CkT8sZMCoIgHA2IoDvG6XL6lQYJujOmVbN1fwe1pVHGVhRRVhgO7K26tSltFVu+ozkl6IDArNNMPnXOVArDBpGQwf1LdnDSxAqK+1gF9pYPHMc9r2/jMqcpe3+pKC7gzmtPJmFaeWPaeuKqUyamlgsjIc6ZUUNVSe/cyMLAUVMa5fhxo7ISVQRBEI425H+5Y4TM7FGXlKALKFv7T2dOoTthUtiDuNqUo0xHTyzecoDfvrotVSPs19ct5J/fPb1fxyqNhvlsP/fNRClFQXhg2wpcd/rkAT2eIAiCIHiRwJxhxvLtzRzsiPPrl7ekCgAPBG63BpfzZ9tZqMud+DjTChZ8PYk5IOXKLCsM09gWy9ldIpNfv7LVV/A1GVCDThAEQRCEnhFBN4xojyX5yO2vseA7i/ju4+s48ZZnUp81tcXY7Ykx6ytPr9nnez+m3I5Pe3XzAQDe2Hqw18d6YX0jP39+U+p90hGDZ02voTthpgoX5yOojMRbu1oCtgwmnrR4cNlO1jW09nofQRAEQThaEUE3jLjyjtez1nUnbOFz/o9e4Mxbn+u19SuTO17c7HufmdF63uzet1e6940drNx5KGX1c5va15UXEktaxHpRxPUvb+5OLb/vhDEAPLm6ocf9OuNJ/vDGdu5bsoNFa/fxo0UbpAuAIAiCcMwjgu4I8frmAxx0+pTGkxaX//wV1nqsTfXldr2y7QfstlNtTv23NXtyW6QOdcb565u7sTz9uhpbu7ni9teytlUKvnbJbADGVxZx/qzsciRB7PUUFr5vyQ4Akk6mbI0T9N8W69lV7MbuQXoe2w50+uYexCMr9/D8+iZe2bQ/tU5ctYIgCMKxjgg67IbwF/34RR5wBIpLf61h+XhxQxOTb3qcq+9czILvLEJrzZOrG3zuxu99cB7Xnma3m/r6X1bzlMdy9fe1adfp71/fxmYnIaE7YXLStxfxxQdX8v0n30ltc+r3nmXZ9nQdObcmmgKm1Zbygw8fz7+cNz1vb1Mv3npeIUPxs+c28shbdkkON97uoeW7erx2i7fYLt7K4gjjK9O14f6+bl+uXQBSteC8rGtoC9jS5o4XN3Pfku15jykIgiAIIx0RdMBDy3axsbGd7z2xLrXuF89vYsrXnuDh5bsGdKzr71rie79hXztfeGClb11deSHjK2yRs3x7M5+5d0Xqs53NthWruSPONx5ZwwU/ehGAJZ4YuDtf3sLkmx5n8k2P+45bWRxJCzqn/Eh1aZTq0miv5+91b+451O0Toq7rdM2eVp7ohfsUbFEJ8N0PzgNgS47CwO7Yj62yjztvbDk3njMFgJ954vkyWba9mefeaSIhVjxBEAThKEYEHbDHSTao9/QNfXrNXgB+8NQ7gfvkw7I0T77dwKK1fmtTkNVq0dq9vvf/dtFMAEoLgyvKPLxiN8ff8jRf/8vbqXU/fmYDP3tuY875LJxUCdhdHk6ZbC9XFOeuWPO3t/bwyXuW8drm/VmfhWOHKKUza/2nzp7C2Ip0IeC3duZOcHCtimFD8b0PHQ/YTepn1ZexbFszn7xnGS+sb8zar+FQ2t378GfP4OuXzqXWEaOrd2eP5xW5z65rpK07wZ0vb2HL/v6VWREEQRCE4cqxLeh2vAHJWKrhvOmJ3ypy3IeNbbFUDTetNXsOdXHdXUuyBMTz7zTy/DuNfPnBlZzzw+f55z+s4FP3LOOuV7ZiWZrXNu1nyteeAGyB9fnzpgHwP89sSB3jowvHMWdMeer9fzlWq0w6YiZPrk4Lwdue25hqz3XTxbN82x4/bhQ3nj2VX15zMufNruOyE8fy/Q/NY0Z9WWqbFzc08X8vbGJfazdPvN2QcqHe9eo2bn9hMy9vbOI//7qaT92zhPctuZZF0a8AfnF68kRbKP7ooycCsK+1m1zsdT771mVzmTk6PY+PnDwutXzvGztoavMf4+VNTYB9/SJOp4b7bzwNgD+tSLt5O2JJ7ntjB796eUtq3z+t2MW2A528sfUg//P0Bt+9FgRBEISRzrFbWHjbq/C7SwF4rPt3QEFKhFiW9pXD6EqYFIQN7l28nW88sgaAlzY0se3W97Fo7T4+dc+ynMN8+7G1rN/byoPL0q7b2WPKqCvz9yj9748cT0Wxv5NAfXkhd1yzgDte3MKMulJauhI847H6VZcUcMBJrAC7b+XU2lK+e/lxHOpKsLelm5n1ZRiGojOepCtusre1m+rSaLp1VecBGpf8iRXWQlbsOJQ1/+U7mlm+wxaLtbQyztoDCs40VvOqdTz/eMZk7n1jO/Mn2b1JP3LyeL716BoKIwaWpQM7RbhZsAscy6HLp86eyp7mbn73+jYAvvv4On561fzU582ddrLFf75vbuq4bpP7Xc1d/OXN3Xx4wXi+8KDfhQ124oebPBE3LV7dvJ9zZvQ+s1cQBEEQhjPHnqA7uAVum+9bNd/YxGJrLh1xkxc3NHL9XUt9n1tOnbUX1jf51pumlVPMlRWGU5mpXjEHMHd0ua8N1A8+fDxVJcFxbGHD4PPnpTsgXDpvNG3dSX7z2lbOm1VHUSTE4i0HmD+xAqXBUIp1e9t4cKnd8L6qpIB/fvc0fvDUO3R7yonc/P65oGD2c5/nlwXL+VDsFt7UM1KfzxldxvyJFdy3xD7OGA4wYVQEYvbnt8zcTviyf2FSVTHfvGyuryXY2TNqWLGjGQuNEdCBIpa0M1zLvO2YWhtQv/8gN8+6lJtv/Rbv/uHzbDvQyaK1e7lo7mgAakujhA3F5JrirGMCPLF6L4cyijFPqi6mpjRKU1s3SY9VrnUAizYLgiAIwpHm2BJ0lgl3XZy1erxq4qrQc5gYXH9X9m6f+O1SX/D/2IpC9hzqZtp/PAnArNFlXLVwAg8t38nsMWWMLi/iuDHl/PnN3azZ08re1m5qSgu44cwpjKss4o4Xt9DhFNY9c1o1o4ojvLO3ldHlhVQUF7ClqZ2XNu7nlU37ueqUCVw4p54D7TEeW9WAqTWvbT7AqZMr6ehO8rtXt6EhZV379avbfHNvbItxy9/WZp3TzY/Z6x4s6AADfjF3Da/PvYLzZ9fR1BajrixKRUkBX7xwJk+9upTr3vh4SswBjGY/pTma3YdDBqalyZXoGktYKDIyVre9Ak3v2K/513L3P53KuT98gQeX7eK82XWEDQNT2xa/oH6yLq85hZLPnFbNN94/l3jS4uo7F9MRN1NlVgBxuQqCIAhHFceWoNu1DNrTLsszum/jtcJ/5X8iv0ytW2tNZr2awjXvmsiLG/ezdX+HT8zNqCvlqlMm8J3H7YzYmtICPnnWFCqLC/jyRf74tatPnYilNfvbYjy/vpEfPL0+a0qvbj6Q6tYAduyeW6MtTJJZb36Xqrc288n4twHNp0OPsUctZM22LlZvU2gKs44J8JX3zuLPb+4mkbTYfrATpeCRz53JuIoiVu48xA13L6MwYlBaFIUYjDm4hI/MHwuNa6msnQWhCGBn3F7XdmfW8UtV7hi5sKHIp5e2HbQzWX2lUg56Ch/veI1J86/hX86fzs+e25TK8j1p/CgMpVHahJ1vQmEF1M7EUGBp2xp5sCNOHc3MLi9lthOP+G/vmcW3H1ubspiCCLqjibte3crcMeXMn1jBruYuKooifcrcFgRBOBoYVoJOKXUx8FMgBPxaa33rQB5fb3wGMLiz4gs8tq+KBqqytnk8+nU2j/0AuyZ8jSm1k7l/yQ7e2WvXOfvqxbMYX1HE604NtUlVRXx04QS27u9gRUczptaMKopQFAmx/WAnr27az/72eNYY+XDF3MmVXTzcdUNq/RWhFzmoy/ha5H6+xv2p9esvewTGLeC2ZzcyZ0w5L23Yz1nTq/n0udP4rOOq3dvSRXfCYnJNCbTs4oKZo9l26/voTpgU3vYliIFq3g6L/w+e+Q+Ycxl87F57gPYmWPtI9kQTuduQhQ3FwY449y7ezqXHj0llD29uaqeiKMKmxnY0EDEUNK6Dujmw7LfpAyy7C+Zfw5fOncDJb93M9PYlVNNK0f44DUY15f+dFsDM+QA/D+/jgC7jXP0OL4VncVXoecLrLPjbJ2D1n/nHj/6OjaFnecA8D43BaA6gzHT8XijRjmHGSBRW9/IuCYOBaWmUssMGuhMmb2w9SMK0mFpTgmlpth7oYPuBTmbUlfLWrhbmjS1nVHGE1zYfSFlmwY4lHTOqEA2cOH4U46uCXfSCIAhHE2owiuf2B6VUCNgAXATsApYCV2uts/2FDgsXLtTLluVOSPBhWRz43iz2xQu5NH4r59d38dy+IuapLXy7+EHCMy9m2sZfU5K0EwC6VDEfq7if3a2JVOJBWTRMWyy7B2kuXGtbRXGEeWPL+eb759LUHidhWhw/fhQVRQWs2dPCB37+Kt+9qJ6J5k4WHaxj/Oh6blj/KcINK3oexOUzrwDKdllWTobaWfDAx2HsyXD2l+BvX4DNz0F3C1RNgyt+AwWl8POFUDjKXl8+HlqdeL/6ebBvNcx6H6x/HM7+f7D+CYg7JT8KSuGz2R0oAP7xt0t43ok3nFpTwldPCXPOC1fyXPI4vpL4NOcZK2kdcwb3zFkKr/wYxs6HPW9C6Whod7J3a2dB3VxY85feX4Me2GyNYWxlMUUttjUwRpSox4+8Z+Jl7JpxHa3VJw7YmEIaV7Dtbemm7dB+tjbHWd2UpL68EIWdba2BM6ZVs2pXi6+IdW8YM6qQGXWlNHfGaWqL0xFP0tadpK4sysP/fDoTqoJDBIJQSi3XWi/s2xkKgiAcOYaToDsduFlr/V7n/dcAtNbfz7VPXwTdhk0bmfL7U4koi0tj3+O4ibWURgye2FXAhBKLT8/p5jvLIrwrsZj/F/4jdcqOSduhxjJWN/Lnus8zv/kpxiR3cgPf4h8vOpVEKErRvhWcsOHnVMZ28fzc/6Kt5SDzupdTojupPu48IvFmQu88jjJjMPE0O44v1gb73gbLgpJqaNsHHU7dNWWA9hfB1SiUWyZk6nmw4BOgNGx/DZb8qk/XOZDpF8GmRbk/rz8OzvwSREvtuT33X9C4Bi6+1T6ng1tg9Z9td/bJn+AXr+6lau8r7NHVPGfN58eR25ll9KJA81lfhvq58PAn0+ui5TDrfZy+8gIa4sXMiTTwyJnbKBh7EhQUQeM6Nq9dxm+a5/PVEzrZt/Qv/CT+QT40ej/vOfiHfl2OQ6Pm0Fk5m+K2rVQcWEl7+Qxaqk+ks3QSSlvEiupAKaKd+6jd8yxLwwvRDW9RUaA5rrAJpU1ihXVsLZ3P3ikfpla1cKhoAuWJJmKRCpq7NVPbltNVPoVQoo1odxNmpJTGce+hpHUTNQ0vcmD0mSTDpaAU4Xgr2gijVQjDjKG0iRkuorRlI9qI0Fk6CTNchBUqZOzWP3Fw1HE80z2X2rIo02pLsSyLZOteZu/6E+FEG0qbHKpZwKGahRS1bSFOlObKEzm0ax3b1q8ibLazPVFBzYTZTK4qYGK0k/3JIuJEKOvaSXXnFkYXmSQ7W9lcfCKJiWcRs0JsX/8mpgrRWTqJaV2rqWxZw4vll9FthXlh3W7KrFamGQ3MUjv5evgPGGhuSV5HCd1s1aMpKa9mdUsBForTinbzrnpNS9l0Tm18iE2hqbxY83GOr4Hi/W8zdfocnmoso2rPq1xSd4D66QsoiIRRRZUw5kSS219HNaziqT2FfHlFDf/z8Xdx2Qlje/07IIJOEISRxnASdFcAF2utP+m8vxZ4l9b687n26ZOFrruFDbd9iJmdy9lsjeEVax5JwhhYKDRJQiQJU1sEF05QlO1YhDLjdrxWz7Mnsy5bjxgRMAzQGoxQ+meoAMy4/XnFREh02yKnZVfa+tZ9CCIlUFIL2oSD2yDh6bBgJW2XqBGyl93xAIqrINaadplGiqFuNuxZaYu1+nmwfyMUVULZaHvMcadAWT10NdvbNG+D5q29PlUNrLUmMdfYnp3zWjYWOg9AaS1Uz7DPLRmHtgZb+FZOgfKxvLq9g0nmVnZTxyk1SYyDmyEctWP94h226C2pYa81ig2tESaXWUwsD0HHfvt6hqPQuttuYhutIBEdxQ8mt30AAA0LSURBVJ7OEEkNa2K1jKKDU431REgSVragtlAYfb2vQIIIpoZCdWQyabWGOBFCmBhK9+sc+kpCh4io4O9KXIcpUH2ztgWiQvbvex9JRkpJXvMIhZN6r89E0AmCMNIYToLuo8B7MwTdqVrrf8nY7kbgRoCJEyeevH173/p0PvGXe5nz1n9RoVsJY2Io2/YVwiSMRZhk2hqmDFsU4VjNlLKfllrbFjJ3GW1voxSEC5wHj7bfo2wxoUKOcDNtMZbshkSnfVwjbL/ChbaICYVtIdbdYrs2Y232vuFoWvAVOcJMGRAts4WLlbSP4Z0nCnQSQlFnPs65mQl7Lu7YlgXxDnvbXESK7PNMdNjHM2POvItsYdXdkr5uyk140KBC6FAYcDJUlWFbKrWZXlbu9Su0553shoISe/6JDuKmZpcaTX24g5KQhvJxtkWwbDRECm1RqDWYcWIJk7ChCeHeG+e44QI7kWLfGvtcwlF0ootYwkRpi3BxOasORam1DnBAlxNWSapUG3usGlopZrQ6QDExuolSRDchNK2UUEiMVkqwtKKdImJEqFRt1BktGKEC2pMGlUY3LZSQIMQo1UXS0oQxCWOCtiijgzgRYhSwT1dQSbs9bZK06hLiOkyZ6sRUYZS20ChaVCk1tGLoJBpFCIs4YUpVN1HDBAySWrm/nRykjBI6KdbdJAgRwiJJCK0MQmjChqZEd6K0BUaImCoiiYGyTKK6C0uFQVuYKkKnLiBKnIhKEtEJ5zvj/kv6uqOxJaUiRN/FWH9FXBYffwhmvqf3w4qgEwRhhDGcBN2guly9aDOJSnTQHU8QjhQQNpT9gHXNR53NtkgIRRxBB7YwstLvXbeotvyCxHD3UY5gCfktZcqwRZll2uushCN+lC2OlLKtZ+Ei6Dpgi7VkzBFj2KIlUpw+ZjJmH08ZtkAMRZwxw/ax3fvrCqnU/dbOw9Lj3rVM6NyftuYZztyNsG0pDEXssePttiBKxtLXI1Jsj2cm0tfCna8RtsfTlv0+FEm7ll1Bh06LwHChLehS1yppn1tBmb3OjPmFq7eMiVdkW6ZzT8Lpa+BuYybS8zLj9rVAYxkFNLd1EDPBAsJmF0a4gFCkEK0t9ja3EbcMwoayhQ8KlKK2NEKXqWiPWSRNi/KiCGNKFcXRKEnLtgKHIunMS20m0BgY2NekMwktHR0URwspLYrSGU9ioEmY7u+WQWtnjLLCMGHDro0YMgyi0ShmrIuGdvt4lpmkPGpQVxJy7qNGW6YtpENRLA3JeCfxeIxwtASsJIUFBf7fQ++1D0Wc39Nk+n5p7dyXRPp7Ycbt65n6XnjEtPu9iXc6fwSEnHsTtkV2rNX+PXePqxR0tdg/S2oh2ZWelxGy//jAAtO0NaOVdO6D4WSxKygotn9HCkrAKICSKs93uWdE0AmCMNIYToIujJ0UcQGwGzsp4uNa6zW59umvoBMEQciHCDpBEEYaw6ZsidY6qZT6PPA0dtmSu/KJOUEQBEEQBMFm2Ag6AK31E8ATR3oegiAIgiAIIwmj500EQRAEQRCE4YwIOkEQBEEQhBGOCDpBEARBEIQRjgg6QRAEQRCEEY4IOkEQBEEQhBGOCDpBEARBEIQRjgg6QRAEQRCEEY4IOkEQBEEQhBHOsGn91R+UUk3A9j7uVgPsH4TpDPexZXy598fq+P0Ze5LWunYwJiMIgjAYjGhB1x+UUsuOVI/GIzm2jC/3/lgd/0ifuyAIwlAgLldBEARBEIQRjgg6QRAEQRCEEc6xKOh+dYyOLePLvT9Wxz/S5y4IgjDoHHMxdIIgCIIgCEcbx6KFThAEQRAE4ajimBF0SqmLlVLrlVKblFI3DdIYE5RSzyul1iml1iilvuCsv1kptVsptdJ5XerZ52vOnNYrpd47AHPYppR62xlnmbOuSim1SCm10flZ6axXSqnbnPFXKaUWHMa4szznt1Ip1aqU+uJgnrtS6i6lVKNSarVnXZ/PVSl1vbP9RqXU9Yc5/g+VUu84Y/xFKVXhrJ+slOryXIc7PPuc7NyzTc4cVT/H7vO17u/3Isf4D3rG3qaUWjkY5+7sl+u7NmT3XxAEYVihtT7qX0AI2AxMBQqAt4C5gzDOGGCBs1wGbADmAjcD/x6w/VxnLlFgijPH0GHOYRtQk7Huv4GbnOWbgB84y5cCTwIKOA14YwCv915g0mCeO3AOsABY3d9zBaqALc7PSme58jDGfw8QdpZ/4Bl/sne7jOMsAU535vYkcEk/x+7TtT6c70XQ+Bmf/wj45mCcew/ftSG7//KSl7zkNZxex4qF7lRgk9Z6i9Y6DjwAXD7Qg2itG7TWK5zlNmAdMC7PLpcDD2itY1rrrcAmZ64DzeXA3c7y3cAHPevv0TaLgQql1JgBGO8CYLPWOl/R58M+d631S8DBgOP25VzfCyzSWh/UWjcDi4CL+zu+1voZrXXSebsYGJ/vGM4cyrXWr2utNXCPZ859GjsPua51v78X+cZ3rGxXAvfnO0Z/z90ZP9d3bcjuvyAIwnDiWBF044Cdnve7yC+0Dhul1GRgPvCGs+rzjqvnLtcNNEjz0sAzSqnlSqkbnXX1WusGsB+EQN0gjg9wFf6H+VCdO/T9XAfzd+OfsK1CLlOUUm8qpV5USp3tmdeuARy/L9d6sM79bGCf1nqjZ92gnXvGd2043X9BEIQh41gRdEFxOYOW3quUKgUeBr6otW4FbgemAScBDdjuqMGa15la6wXAJcDnlFLn5JvqQI+vlCoAPgA85KwaynPPO7Uc4w3KPJRS/wEkgT84qxqAiVrr+cCXgfuUUuUDPH5fr/Vg3YOr8Qv6QTv3gO9azk1zjDXUv4eCIAiDwrEi6HYBEzzvxwN7BmMgpVQE+wHzB631nwG01vu01qbW2gLuJO1aHPB5aa33OD8bgb84Y+1zXanOz8bBGh9bSK7QWu9z5jFk5+7Q13Md8Hk4gfXvB/7BcSXiuDsPOMvLsWPXZjrje92y/R6/H9d6MM49DHwYeNAzr0E596DvGsPg/guCIBwJjhVBtxSYoZSa4liQrgIeHehBnNih3wDrtNY/9qz3xqV9CHAzAx8FrlJKRZVSU4AZ2EHi/R2/RClV5i5jB+ivdsZxs/euBx7xjH+dkwF4GtDiuqsOA591ZqjO3UNfz/Vp4D1KqUrHRfkeZ12/UEpdDHwV+IDWutOzvlYpFXKWp2Kf7xZnDm1KqdOc35/rPHPu69h9vdaD8b24EHhHa51ypQ7Guef6rnGE778gCMIR40hnZQzVCzvLbQO2deA/BmmMs7DdNauAlc7rUuD3wNvO+keBMZ59/sOZ03p6meGXZ/yp2JmKbwFr3PMEqoFngY3OzypnvQJ+4Yz/NrDwMMcvBg4AozzrBu3csYVjA5DAtrTc0J9zxY512+S8/vEwx9+EHZPl3v87nG0/4tyTt4AVwGWe4yzEFl+bgZ/jFPzux9h9vtb9/V4Eje+s/x3wmYxtB/Tce/iuDdn9l5e85CWv4fSSThGCIAiCIAgjnGPF5SoIgiAIgnDUIoJOEARBEARhhCOCThAEQRAEYYQjgk4QBEEQBGGEI4JOEARBEARhhCOCThh2KKVMpdRKz+umHrb/jFLqugEYd5tSquZwjyMIgiAIQ42ULRGGHUqpdq116REYdxt2fbL9Qz22IAiCIBwOYqETRgyOBe0HSqklzmu6s/5mpdS/O8v/qpRa6zSof8BZV6WU+quzbrFS6gRnfbVS6hmnafwv8fT1VEpd44yxUin1S6VUyHn9Tim1Win1tlLqS0fgMgiCIAhCFiLohOFIUYbL9WOez1q11qdidxX434B9bwLma61PAD7jrLsFeNNZ93XgHmf9t4BXtN00/lFgIoBSag7wMeBMrfVJgAn8A3bT+3Fa63la6+OB3w7gOQuCIAhCvwkf6QkIQgBdjpAK4n7Pz58EfL4K+INS6q/AX511Z2G3n0Jr/ZxjmRsFnIPdSB6t9eNKqWZn+wuAk4GldstQirCbvP8NmKqU+hnwOPBM/09REARBEAYOsdAJIw2dY9nlfdg9O08GliulwnhcqQH7Bh1DAXdrrU9yXrO01jdrrZuBE4EXgM8Bv+7nOQiCIAjCgCKCThhpfMzz83XvB0opA5igtX4e+ApQAZQCL2G7TFFKvRvYr7VuzVh/CVDpHOpZ4AqlVJ3zWZVSapKTAWtorR8GvgEsGKyTFARBEIS+IC5XYThSpJRa6Xn/lNbaLV0SVUq9gf3HyNUZ+4WAex13qgJ+orU+pJS6GfitUmoV0Alc72x/C3C/UmoF8CKwA0BrvVYp9Z/AM45ITGBb5Lqc47h/CH1t4E5ZEARBEPqPlC0RRgxSVkQQBEEQghGXqyAIgiAIwghHLHSCIAiCIAgjHLHQCYIgCIIgjHBE0AmCIAiCIIxwRNAJgiAIgiCMcETQCYIgCIIgjHBE0AmCIAiCIIxwRNAJgiAIgiCMcP4/PMUHudYwUkEAAAAASUVORK5CYII=\n", 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" ] @@ -216,7 +233,7 @@ } ], "source": [ - "model_dirs = ['data/walker2d_ddpg']\n", + "model_dirs = ['data/halfcheetah_ddpg']\n", "show_config_group(model_dirs)" ] } diff --git a/fast_rl/core/data_block.py b/fast_rl/core/data_block.py index 51d9678..190cdca 100644 --- a/fast_rl/core/data_block.py +++ b/fast_rl/core/data_block.py @@ -7,7 +7,7 @@ import gym from fastai.basic_train import LearnerCallback, DatasetType, DataLoader, Dataset, Tensor from fastai.tabular.data import def_emb_sz -from gym import Wrapper +from gym import Wrapper, Env from gym.spaces import Discrete, Box, MultiDiscrete import gc @@ -20,6 +20,25 @@ # Because concurrency errors happen from Open AI when there are multiple environments. os.environ['KMP_DUPLICATE_LIB_OK'] = 'True' + +# class OpenAIGym(Wrapper): +# def __init__(self, render, **kwargs): +# super(OpenAIGym, self).__init__(**kwargs) +# +# def render(self, mode='human', **kwargs): +# r""" If human is used as a mode, the returned image is blank. Get image regardless of mode. """ +# out=super(OpenAIGym, self).render(mode=mode) +# if mode=='human': out=super(OpenAIGym, self).render(mode='rdb_array') +# return out +# +# +# def openaigym_wrap(env, render): +# if isinstance(env.unwrapped.__class__, Env): +# env=BulletWrapper(env=env, render=render) +# if render=='human': env.render() +# return OpenAIGym(env) +# WRAP_ENV_FNS.append(openaigym_wrap) + try: import pybullet import pybulletgym.envs From dc9671beae948780ecd068c3c3829bcbf1b9e325 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 19:33:43 -0500 Subject: [PATCH 06/29] Added: - initial gifs, finished notebooks --- README.md | 19 + docs_src/rl.agents.dddqn.ipynb | 408 ++--------- docs_src/rl.agents.dqn.ipynb | 664 +----------------- res/reward_plots/ant_ddpg.png | Bin 0 -> 36850 bytes res/reward_plots/cartpole_dddqn.png | Bin 0 -> 78095 bytes res/reward_plots/cartpole_double.png | Bin 0 -> 74701 bytes res/reward_plots/cartpole_dqn.png | Bin 0 -> 49081 bytes res/reward_plots/cartpole_dueling.png | Bin 0 -> 79526 bytes res/reward_plots/cartpole_fixedtarget.png | Bin 0 -> 89615 bytes res/reward_plots/halfcheetah_ddpg.png | Bin 0 -> 36317 bytes .../lunarlander_all_targetbased.png | Bin 0 -> 107464 bytes res/reward_plots/lunarlander_dddqn.png | Bin 0 -> 79614 bytes res/reward_plots/lunarlander_double.png | Bin 0 -> 77435 bytes res/reward_plots/lunarlander_dqn.png | Bin 0 -> 45994 bytes res/reward_plots/lunarlander_dueling.png | Bin 0 -> 84743 bytes res/reward_plots/lunarlander_fixedtarget.png | Bin 0 -> 76104 bytes res/reward_plots/pendulum_ddpg.png | Bin 0 -> 70205 bytes 17 files changed, 117 insertions(+), 974 deletions(-) create mode 100644 res/reward_plots/ant_ddpg.png create mode 100644 res/reward_plots/cartpole_dddqn.png create mode 100644 res/reward_plots/cartpole_double.png create mode 100644 res/reward_plots/cartpole_dqn.png create mode 100644 res/reward_plots/cartpole_dueling.png create mode 100644 res/reward_plots/cartpole_fixedtarget.png create mode 100644 res/reward_plots/halfcheetah_ddpg.png create mode 100644 res/reward_plots/lunarlander_all_targetbased.png create mode 100644 res/reward_plots/lunarlander_dddqn.png create mode 100644 res/reward_plots/lunarlander_double.png create mode 100644 res/reward_plots/lunarlander_dqn.png create mode 100644 res/reward_plots/lunarlander_dueling.png create mode 100644 res/reward_plots/lunarlander_fixedtarget.png create mode 100644 res/reward_plots/pendulum_ddpg.png diff --git a/README.md b/README.md index 43883eb..b681e09 100644 --- a/README.md +++ b/README.md @@ -11,6 +11,8 @@ Our goal is for fast_rl to be make benchmarking easier, inference more efficient as decoupled as much as possible. This being version 1.0, we still have a lot of work to make RL training itself faster and more efficient. The goals for this repo can be seen in the [RoadMap](#roadmap). +**An important note is that training can use up a lot of RAM. This will likely be resolved as more models are being added. Likely will be resolved by off loading to storage in the next few versions.** + A simple example: ```python from fast_rl.agents.dqn import create_dqn_model, dqn_learner @@ -166,3 +168,20 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe ## Examples +### Reward Graphs + +| | Model | Gif(Early) | Gif(Mid) | Gif(Late) | +|:----------------------------------------:|:-------:|:--------------------:|:--------------------:|:--------------------:| +| ![](./res/reward_plots/cartpole_dqn.png) | DQN | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | +| | acn | | | | + + + + +| Gif(Early) | Gif(Mid) | Gif(Late) | +|:--------------------:|:--------------------:|:--------------------:| +| ![1](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![2](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![3](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | +| | | | + + ![2](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) + ![3](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) \ No newline at end of file diff --git a/docs_src/rl.agents.dddqn.ipynb b/docs_src/rl.agents.dddqn.ipynb index 6eda5ef..b667d82 100644 --- a/docs_src/rl.agents.dddqn.ipynb +++ b/docs_src/rl.agents.dddqn.ipynb @@ -72,7 +72,7 @@ "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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\n", 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ZBwlCKcslUWHLps6PbTwk4xKZYFs2bEfBdlzBpzm7vDwRgQjYWNuEZNIp7PAuIKTZsrM7IvnDQMMmoGVXzkAc1OQoQRAEoTAiNgWhM5y4W9CdyC0rBLiu9UKWzd660XWm2CyUIKSQp3L1QewS1EUIDNtWIAKSlpsR357IfzaV4QAMg6CUytfuzG7pphy0ZWdXAfCHgdDgvOdFhL7p6CQIgiD0ConZFITOsBNuWSHDDyS97O5CopKo9wlCaTFpALpAnckCbnTW+pArYM4EOEoh4AugtjGCfa0xxC0HQX9+D3MQoJTO04VMBG0ViNn02lpmz5FvCWaWOpuCIAiHAiI2BaEznKTrRicCLK9+ZCFRSQagk71bi7WrNQlF3OgF3PT6ULNrAgDBthXCg3zwe3UyB5cFQIUKzLPXgjLnLsgwCopNnbQBs4BTpoAlWNpVCoIgDDwiNgWhM+yYF7NpAFbMO5YoUBfScBOHekPavFckQSiVPJR1KL/25kBDRFBKwyCCr5AwzEEpRq7NkwwDsPItyGzbBSybhToukYhNQRCEQwCJ2RSEznASrtg0/B2WTZXoSBpK0wfZ6CnBVDRByCnQPUcfaloTIILtuGKzKyjbAeVm2ZuGG5+ZA1uFLJuU5zInokMyU18QBOHThohNQSgFs2vFNExXXFrtQP37buZzrjgqJhC7tV6G2CzaQShbwGmVf2zAIYKjFHINkMVQtnL7V2ZOYRiusMyBbVXAsol8y6ZhSMymIAjCIYCITUEohXYAsCv+iAB/CNjzppsoFByUPTZlxeuNwEm70Ytko2snX+Q6CmQcOmLT1owPk4Dj6MIxmjkQAbZj54lNZQBrG7egPtmcPsbM0LaTNxYo5Eb3anIKgiAIA4rEbApCKVRORnjZsNLj09bNHn6OY88lTl7HIq2zy/ykEogy0HaBvuJdJNWv3MwVsL0goRk23DhMgwhJ7eDdyA5MLRuLQf5w3ngigmOpPGHqkEYs0Y52lZF05YnHPBFbyLJJBO6L9qGCIAhCrxDLpiCUQlndE3LMvSt/lGedK9SWMbeDUCFLX9fYnWzE3mRLj64thqMBGwR4xeaTykarE4fFheNZDXKtoLk+d4cY7ChYGXGwrFSRiAECUKD5urjRBUEQBhwRm4JQim5nlxdxf3eV3GvzXhfoIGTnWwW7SkOyDfutNuje7DmHmNJQILA3p8UObK3SVtRciAgRy0ZbzmlFDO1oWBk1TdnJL/4OADbr/AQhw5AEIUEQhEMAcaMLQimU1b1M72L1MbtMxmLaBvZ9AJiBjmPxFjduNPMKlW8V7Ao2O4izjYTTjt3JRkwIVfd001kkvHwl8sRlTCVd62WR5xL0mYhYGu9bcRwVUhjirwDgjicDsJxssZlLUttY316LmcFqhHLOsRLLpiAIwkAjYlMQSpEbs9kZjD6wbHqCM1AJ1L2VPyY8JPsSp2cxm0prEAODfeVoV0m02Rphk+DvZbKRnSoyrxkxZaE22YSA4ccBO4Kw4UdVoDJrvGEQyg3GAVaIOApD/EBCWdiTaAYxwc60bNr5luYDVgQNdgT7KYjx0KCUw0ZiNgVBEA4JRGwKQimUjW4Xsex1zKa3XllV165RPXOjK7jJRn7DQFzbaLY1DDJ6JTaZGZZ2y2CyZtjahqMVys0gbFZoV0lUoTL/QkdBQWNbu0a5oeD3KbQ67W4JpUzLptJ5/c5bnHZUGmXYGm/AcDuOMn+5e0Lc6IIgCIcEIjYFoRTp7kFdhJAnhroFa3Q3lFqr/BqVxUhZHQMGwcnIRI84CSTBUL0sDq8AaK9UFLOGAsM0DBAAWyskiyQJsWL4TQWGhg3AYA2HNYaYIdiODZ20oCwLBxr3IeRFbSrW2JtsQZPdDqAc7Q6hORGD3wjBb5qSICQIgnCIIGJTEEphx7snNoHexWz2xAWvdJfd6G22hgZQHTShWYMZIBA0GHGtoHROK0xPMPoot5lkPk2WQsxTq273Hg3NDDDDMAwktAW7gNWXmcFaQZkMQENphjI0AuSDz1CIOw7Wv/QCytod7LMimFl9BAAgquLYFKtDhRmEpQxoAM2xKMJmOQaFQl74rIhNQRCEgUay0QWhFHbM7R7UVXods8nottte6S4XdXcAOF5JIiezVBATLK8+ZsdWNN5v34232j7q0ty1cYUmSyPg7YU1w/0fYIDg6OwyRh0LuQZhxRqaNRQAS2swGARCwk6irnkv9lcy2of4YZa7tTqjThIhw48yM+hZlAlRK4HG9na0xeOSjS4IgnCIIJZNQShFTyybvYrZ7L4fm5UCUaDzgXDd6B3fq3TvcgagwFnn49pGi90OIgIzl4wL1exKwwqfOyYJ9xrF7DZfAsGGAxsFLJtae+trEGtEHUaTrQEyoLUGx5NgZhywo/CRa5ElAPutVgRTPxsGDDIQt+NQQUZSKcDv793PQhAEQegTxLIpCKVwEt2zbIJ7Z9nUTrczy4sXOs/H0e4X4JY+MojQaptIKB8czbAztq6gQSC4zu3S9+Rq1A6hGjIJQdZQrEAgGORaNu2Clk33OsUM7YUgRBxGi1WGvboM7dEoKswgqgODYICgoNFoRxFRCQQNP1IrG2QibiexN7YPe6MNABG0xGwKgiAMOGLZFIRSJKNA+fDuXdOrmE2FLitHePGOSrsu4y7gZFgoYyoJgw002yYcmAiZjJhyrZt+g7xC767cdFjDLBG3qXN2HTANOAQonRKbBkYHh6JdJ6GZ0xZV92INZgaIobyYTc0atjbgI2D0XoUg+dI2UaU1diUOoNwMZu2BQEjEmuC01YENA/D7gEEju/RcBEEQhP5DLJuCUAxlu+KvW5ZN9NKy2c2amZoR165VsCs4DCQ1I2orNNnt8Jt+aCZoTTBII6YY7V6Sj2ZOx0IW6/6TIjeL/YDVhogTh+OJTQDwGz6AATtXjGudbmXJrLEjcQAxHUPY1OCwH1RRCTWkzB1LgMUK7cpCICO8wb19gnbisJncL6tdYjYFQRAOAURsCkIx7Di6Y2VM07gdiDb0bE3tdG9NrdGoCMlO9G3EVmi1FRwGlGa82NSIA0kTxJTh/Gb4jXRLcyhopFJ8VKdudM7ad0QlENMWnIy4UMAdsjvRmCVeWQPNdnvaXR9RSYRNPwKmz62zSUaWAI/pZJ4e1yAwCKw0bDKQ1Aaak0kpfSQIgnAIIG50QSiGk0S3M8PLqoB9G4BABVDRg/aP7CbGdH24hgPXnZ704iFTcYyZ1CU1LN1RR9PSNsK+MriFjQgAwdEahum62gGkyxYRDDhagQ2GBmAWsLwqwMs7TyUcudcqrbKEYaURwo74fowMDEaFL5S+B8UaIcMPg0wEtAGDUln5DJ0hYpmBBqsN4Ow9aABQCiYImglkOG7SkpQ+EgRBGHDEsikIxXDi3b/GFwIqRngWyh7Q3QQhzbDZFVvbYnuxJVZfcBhxR1WlpNZgcqDZgGZ4NkGCAw0igkqVRtIKBhlgMDQYEYfxYXv2fdnajfHUOZpcsSs9NbtdiVKYhomgEYDKdKVrDQV3XKomfuoJGNSR0AQAYdOPFrsdITP7czIzgUwfynw+VAUNt4C8tqRdpSAIwiGAWDYFoRjKRo/c6KBeiM3cVJvSMDMcuK7vpAYMKmzJY/KSeAhIKA3DW8Nhw8s3J7Q5MVSaQTh+1+LoQHlli9wyST4DsHNE5Y6YgsOMkcGcuNZUhrnSyM8r4nT3otRYxRo+SjVgcsvMA64QVhnPI2j4C1puNQP+gA+mN9SCg+ZkBOMlZlMQBGHAEcumIBTDSXS7DBEAtyd3Ty1q7HTPja4UFLuJPw1JPxJF+k1q7kjiKTM0DEODQYgpA0QE0/BBsUZ9sgkRJwkAsLWGAcOtkcmOJzrd2pmWZjTbGknNbskk5qw3k5QT3OGOBKGOc5wds+l1GkqNy5TLRICji/8MkoqQUAYczl4lRAE4UL1rHSoIgiD0CSI2BaEYTrJbwq8DoxeWze6JVKXcCpi21rA0oc0q7KzQ3PHHHtVR+GHAR4ykIvhIA0yo9AWhoBBT7t4VKxhwe6db2vHWASwNtHsude25yx3tllTSrBHXVjqxSGuVtqKmMMhMx5e692BnRcYyOjS+AUBxcbHZbPvQYptwmLLawxMAzcrtYiSCUxAEYUARN7ogFEMlu989CHAFak/FZjcThHRKbDJgEKNdG1DMeUk8aWshA3FlIWD6QOD0G0BSu/U0/WTA1ho2O2hTcRAMmACS7EAzYDGj0VIIGQTFSLutHU/M7rfbELHj0J58VFrBn7MXE4QkZ4hNJ7sofYVPpYUjee5/5sJGZs0EzUDQyA4fICLY2nPAF7tYEARBOCiIZVMQiuFYPbNsEnnxnj2gm3U2laPSFseUEzo3WQfIqMNJgAbnubZT2UMEty951Emg2YkhYPpgEMHSDhxmhE1Cm81QSHX8cS+3tJvME3HiWT3X3daSuZZNA1EV98olAcrJTorKbfPeEcHpus2bLDPtHWcGbG3kX5PZPUjKHwmCIAwoIjYFoRh2d1tVepDR8y5CrLslNnUqc5zdskQa+cWa2KuB6TcIfmKvRFHOGHLd0K7VUSOhHIQNPwxQ2o2uNMME4MB1m2vuWMvSrlBV7JYx0syui13n91QPGT40WVG0OTH3HhwnX2Fm7w6aXUtqXBlos33p+FO3TSXnX05uIXp2H1LJZygIgiD0LyI2BaEYykKBVOrOod5kozvozp9le8L2EoTckujMnNftx81vd62SfoMKSE2g3HRd14ZBcFghpm2YnlXXIAM2KzcJiFy3teNN4nAqPtJdP2VBdcslFRbcRAYCXkISADjKyS2bmXsFktpAq+3zEp0ILd73DCDsyxeTBsjts06QmE1BEIQBRsSmIBRDJd3M8u5CvclGz45f7Iy6ljh8AGoTjbC19nqKZ6/NGRZInVUiPWPL3kGT3JjPNseC6b09EFzXuys2XeFqayBouIXg48pGQjuw2QEIXva6gmIGFfLpA163IPdc0k52cs8MR7tZ6RoEv8GIOCbiygAXUakGeX3gUw9AEARBGDBEbApCMZQFUE9y6Ixexmx2/c9SaY2QAdjstpYkMtBkK+xod9IWvcxGkjpVk6gIRG6ZoxbbSls2AYCYkNQdFS8tzSj3ESr9DnYmD6A22YS9Vits7aDcF8QQf5knJgsvRoS0uz2ajMFXMlyBoJjgeKLZR25NzhbLV/xWyIBOZaKLG10QBGFA6XexSUQmEb1NRE96rw8jon8Q0VYi+jMRBbzjQe/1Nu98TX/vTRBK4lg9tGySG3vZE7RCV02bzAxHafgB2JrSLuwGS6HV0Wi0NFptnVW3slC8ZtbWQWBmJJSCP0MAMhhxpdJvGBoMsEaTHUXQMMDQSCgLOl2MHQADRWrMg+B2+Wm2o2hJRmGWyPpnMBwmL/Oc3McLRlIbBV3ogCdmoQEvblQQBEEYOA6GZfNKABszXt8G4E5mngygGcC/e8f/HUAzM08CcKc3ThAGBq09l3YPxSZ6aFHjrmeja2ZAu2WO3LQfBwZcK6fDQNThdCJP+pou9Hov8wVQ7gtnZZEzAzGlvFJHBGYgwTZanTgqfT74DdeyOsRX4V1BJeMlDRAcKNisEWADRgnLphsT6makpxKDggajzFc8VMEAQYFAXChlShAEQTiY9KvYJKJxAM4EcK/3mgCcAuARb8gfACzyvj/Hew3v/KmUm8YqCAcLZfXueqKeZaSzQlf/LLX2/s8gBAwHbuNKgqVdUWh5rSwzpZbObDxebOsoEOZIPtisQGlhCzDrdKY5wXXBGxl/spo1dJHYVYMIjlawteNaP0vsySR2Xegpyybcx1sygR1ekhJrcaMLgiAMMP1t2fw5gO+go6b0MAAtzOmKzrsBjPW+HwugFgC8863eeEE4+Gi7d4XAmXvmStddL32Usmym/jfYF4bPMN12k+4pOJq9TPXUtjq38rkJQTktJtlIZ48TgIRO1evMvCr7GgWGKtKbnEBwWMPSDoxOBLBJbi3NVARoV38qbmKUiE1BEISBpt/EJhGdBWA/M6/LPFxgKHfhXOa8y4loLRGtbWho6IOdCkIBlN1L7yv1LCO9G0XdtZf8osnNnPEbPpgwkVA2bHbAABSAVlunOwoxuAv3xS/w9dYAACAASURBVHktIh1tpIVqhc/AsIABh50MV3t+MpBCacumDQ1LWe4cJe6ZCAiYOv1m1ZXH4wYyEFgrKX0kCIIwwPSnZfOzABYS0Q4AD8F1n/8cwBCidIrvOAB13ve7AYwHAO/8YABNuZMy82+YeR4zz6uuru7H7QufarTTrRJEeRB6ZtnkTnzKGWjNYO3WtkzJKQYAz9Wt2S0ZFHUYfu8vXXeaIuSVCc0Z5LAJomzhaHN+3/PseQywyn4GiaYQWHsxm9qBpZxO3eEAEDC8Xuvd+KFQqtamiE1BEIQBpd/EJjN/j5nHMXMNgC8DeI6ZLwTwPIBzvWHLAKzxvn/cew3v/HMsJglhoFB270VKd2M2tZfM0g3LJmtGVCdyYiXhGlbZbSmZ6lsOALZ2ssYWImUVTGFpQlKZrks6A4d1ybkG+cIYnk4Ych+nk/DBifkBx4TlMGzlwOji25BpAEp38xOAFje6IAjCQDMQdTavBbCSiLbBjcn8rXf8twCGecdXAvjuAOxNEFyUhV6ZNhk9sGx2T9ymLJstThxBw9+xLFyXt9u/3BWdqTuJ645i7cVws787XicVedbSXLGpYHjZ+oV2TkTwZa7FACsDyZYQEvsGo31/GHGVzGtnWQw/MUJm155pakrFGixiUxAEYUDpScXqbsPMLwB4wfv+QwDHFRiTAHDewdiPIHRKT9tNZs3RTZHTTXGqmWEpCw5r+D115TcYhtYgT2TajHSxdwBIKLuTAureVuBZIr0McJPc9Q5YbajwhUAgxJWFcl8IQBFZTgRkuNFZE4gYZsgBayBkBxCEz63t2YX7JQJ81HVBzvDqnYqDRBAEYUCRDkKCkItygMZtPSvonqInMZvdHB9LOmhKtsEwO/YZMBhhwwGIPatmh9A6YEXQrpOdu9G90zYT9ib8SGjDjeOERkxbbotKbWXV4QybAYTNQP5EmZnwmS5wAgwYCHkW2f5CM4vYFARBGGBEbApCLnY70LgdCA/txSQ9qLOZkxwUSzrY19JeeIuOxoG2OBxlIWBmOyhSTSrd/uMue5MtaFUxlBnBLu/fjfl0C7gbIGgwEsqGgnbrY2aIVvL+l39PHUJP2zlvN0xFe6f3DVJnUxAE4VBAxKYg5KJsIFAG5FrqukNP6mzmjI8mLOxviRccur81htZYEqSc/JhHQjobXWm43YRUAo5WnVo1MzbjCU1KJwsxM2xWUFq5heO7Uh3eE5OsASsShFZeEXhK3XL/Wh01a2lXKQiCMMCI2BSEXHpdYxNwq6p317KZXdzcbxpIOgrKs8wltI1WJ+ZuUTPKQ353nZw/Y8OLVTSI0klCDitoMMwuhwaQKzaRSjDyugaB3fqYXEDk5t4OEUhlWjZNGBm9zBnIr7HUxzB0z/vUC4IgCH3CQUkQEoSPFdpGn/TT7pEbPeMlA5atkbQ1yoIGNkR3o9mO4rRhR0GnRJrWhbNziDEsYKAhqdBkR6HBcFjlx1VmLgZkmBw5LTYZbmtIzdqdRys4WsHsQqJRel6GmxwU7HgmBdti9jFa913M5rp160b4fL57AcyEfFAXBEFIoQG87zjOpcccc8z+QgNEbApCLsrum3l66UbX7LrCU+Vmbe3A9gSsW8hdF+wrboDSrSUZQFzb8BkMXUJAD9mwEyNf+QBbvvZ5sGkCRGmjY+qqkOGHAw0LDmwo+KmTtw+ijnhJpoKimDT6VXGyVn0Ws+nz+e4dNWrUtOrq6mbDMMQ3LwiCAEBrTQ0NDdP37t17L4CFhcbIp3NByMVJANQHfxo9Kn3UociUcoVmKqM8oW034QWA1to9TihYBL7ViaPNiWGw34BB7nWDfGVFl1ahAKzKMIxESmgzHCYv7NL9N2D6ETICSCg7K8u9KG51eG82FDYWZxYB7Qf6OGZzZnV1dZsITUEQhA4Mw+Dq6upWuF6fgohlUxBysRNAV1zEpSDqvoWUs/uLK09QpnRdkm0o74UqYREkAAlt4YAdwWGhEExykOgkOSgyaQwik8akXxte1SIid0eUPk4wQPAZXXnrIJDOidHMwW1n2X9qkwlg1Qc1U10MEZqCIAj5eO+NRa00YtkUhFycONAlMVUCMnqQIKSzFJmjGWCC9gSbpRUUOiybXMRNTyAk2UFC23A85/ngElZNMGPkC++hfMe+jjnY7UNOYDBni8Gg6Ye/K8+HkK69xFygMBJ5bvQuZ8h3HwZL6SNBEIQBRiybgpCLnQCol5ZNEKCt7l3C2ck+WjNiOolXmjfjrIrZSOoOS6liBrMqaC70mz5Um4PQ7iSRVG4v9FJdg8y4hYpdDRiyaTecUAC1C4/HxL+/jV0nz4VdNcj1dPdED2ZmAGWaRzNvWTG4n7Qmpxpsqm6K/i7yyNraIQ1Rq8/eQ6srAs6588a3lBpjmuYxkydPjiulaNKkSfGHH354R2VlZZ6aPvHEEyetXr36o+HDh3f55lPXAMC9995b9d3vfreh1Pgnn3yycsmSJUeMHTs2/Yt+66231i5atCjS1TW7y1VXXTXmpJNOivTnGikWL15c88Ybb1RWVlYqZsZPfvKT2nPOOadH6951113D1q5dW37fffft6ou9rVy5cswDDzwwvKqqygGAU045pfW///u/9xx33HFH7t+/3x8KhTQA1NTUJP72t799mDseAF555ZXNb7zxRtmSJUuOGDdunBWPx43hw4fbV1999d4lS5a0Flr32muvHbVmzZoqANi6dWt48uTJcQC46KKLDjzyyCNVb7311ibDMOA4DmbOnDn9l7/85c6nnnpqcGptpRTdcMMNuy+88MLWYnsq9DsbiUSMCy+8cOKmTZvCzEyDBg1y/vSnP320cOHCSQBw4MABv2EYnJrrnXfe2RgKhfi+++4bsmzZsiPeeuutDXPmzEn885//DC9duvQwAKivrw9UVFSoyspKVVVV5axatWrH7NmzZ9bU1CRS665YsWLfihUrGov9HFK/IxUVFSqZTBpz5syJ/uxnP9tz2GGH9SjwP/P35Cc/+Ul1WVmZLrV+V0n9XgQCAW3bNi1YsCDys5/9bE/qWW/fvt2/fPnyCdu2bQsrpeiUU05pveeee2rD4TA/+eSTlWefffaUBx98cNsFF1zQCgAnn3zypKuvvnrfWWed1eW/BxGbgpCL0xdudKP7LS9zxKOjNSIqBsuJu5ngrKEV0BRNuH3RufN4x4S20ZmaU2VBbF96Koa8vwPJoZUwHAV7UDnIUTDAcHrq5k4pVM1FfOjo15hNAoFZpy3DfU1D1PKNGRLqo2wyoK4l0Wk7pWAwqDdt2vQBACxcuPCwO+64o/qGG25Im6RdizfjxRdf3NbVdXOv2bx5c+C3v/3tiM7EJgDMmzcv+vzzz3d5rd7gOA5+/vOf1x2MtVLcdNNNuy+55JLmJ554onLFihUTzznnnPcP5vqluOyyy/bdeOON+3KP33fffR/+67/+a6yr4zN/hq+99lr4vPPOm1RWVrajkLC+7bbb9t522217AaCsrGxO6ncRAN54442Kn//858NXrlx54JZbbhlx9NFHt59++untTz311ODU2m+99Vbo1FNPPfLLX/7yu6X2lMstt9wyYsSIEfbjjz/+EQC8++67wfHjx9up9VeuXDmmoqJC5c710EMPVc2dOzd6//33V82ZM6fuuOOOi6euWbx4cc1ZZ53VeskllzQD7u/9+PHjk5n31BVSvyNaa/z4xz8ecfLJJx+5adOmDaFQqFchN9/5znc6/fvrDqnfi0QiQf/xH/8x9owzzpj05ptvbtZaY9GiRZMuvfTS/VdeeeV2x3FwwQUXTPzGN74xbtWqVbUAMHLkSPu2224bnRKbPUHc6IKQi7L6Rmx2N1ZQK2TFbDKjXVtIahtRlQQDsJNAfXMUSjM0OhNRDAfZc5aiZWYN4mOHITFiCPZ8/hi0Vw8FEVDu661lsPj6/etGJ/cZOf1j2RxoTjjhhOi2bduCmzdvDhx++OEzLrroogkzZsyYvn379sDYsWOPqq+v9wHADTfcMHLy5MkzJk+ePOPGG28cAbj/YS12zdVXXz2utrY2OHXq1Olf//rXxy1atOiwBx54YEhq3YULFx724IMPDi62rxdffLFsypQp02OxGLW1tRmTJk2a8eabb4aefPLJynnz5h15+umnH3HEEUfMuOCCCyYoz+r8P//zP4OOPvroqdOnT592xhlnHN7a2moAwNixY4/69re/PfqYY4458ne/+93QxYsX16xatWooALz88stlxx577JEzZsyYdsIJJ0zeuXOnH3CtOJdffvnYo446alpNTc3Mv/3tbxWAK1aXL18+bsqUKdOnTJky/eabbx5Rap5MTj311Oj+/fvTx0ut/dWvfnX8nDlzpk6ePHnG888/nxe/8sc//nHwrFmzpk6bNm36/Pnzp9TW1vqUUpg4ceLMuro6HwAopTBhwoSZqZ/hwWL+/Pnxa665pu5Xv/rViO5e+1//9V+1d95556i1a9eG7r333hG/+MUvdueOmTt3bsI0Tezdu7db91VfX+8fO3Zs+oPd7Nmzk+FwuOQbW2trq7F27dqKVatW7Xj00Ud70w6uSxiGgeuvv37/8OHD7UceeWQw4Ary1PlVq1YNXbx4cQ0A1NXV+T7/+c8fMXPmzGkzZ86c9swzz5Tnzrdy5coxP/rRj0YCxX+nI5GI8cUvfvHwKVOmTD/zzDMPnzVr1tSXXnqpRMwUEAqF+Ne//vXuurq6wOuvvx5+4oknKoPBoL7yyisbAcDn8+Huu++uXb169bDU3+G0adNilZWV6tFHHx3U4+fT0wsF4ROLsnrvRifDq9fZDVghZeZjZmjFsNmB025iX3sEZtRCxXt1SMYt11jYicXOIANWF6yrVeu2Yfg/N2dvnwBK2K51s7da0Is9LaQ5uQs++rcDe/B0eEv69S6zBS8FP0ISpe+N4Vl/uxs7+zHAtm08/fTTg4466qg4AOzYsSN0ySWXNG7cuPGDKVOmpN3aL7/8ctkf//jHYevWrdu4du3ajffdd1/1q6++Gi51zR133LE7ZeG55557dn/ta19r+P3vfz8MABobG81169ZVnH/++a0AsHbt2oqpU6dOT31t2LAheOKJJ8a+8IUvtFx11VVjv/nNb44777zzGo899tgEAKxfv778F7/4Re3mzZs37NixI3jfffcNra+v991yyy2jX3rppS0ffPDBxrlz58Z+/OMfj0ztJxQK6XXr1m1evnx5c+pYMpmkK664YsKaNWu2b9iwYeOyZcsOfPvb3x6bOu84Dq1fv37jbbfdVnvjjTeO8e6reufOncENGzZ8sGXLlg8uvfTSxs7mSbF69erBp512WktX1o7FYsbbb7+96a677tq5fPnyw3LnOv3006PvvPPOpo0bN35w7rnnNt14442jTNPEueee23jvvfdWAcCaNWsGTZs2LT569Oiiv+R33333yNRzX716dVoELF269PDU8a9//evjCo0//vjjpxSb97jjjott3749VOx8MSZOnGhfdtll+0866aRp3/72t+tHjhyZ94f33HPPlRuGwan76uqeli9ffuCXv/zlqKOPPnrqFVdcMWb9+vWd9t198MEHh5x00kmts2bNSg4ZMkS98sorJUUYAKQ+ZKW+UqKuO8yaNSu2cePGks/v61//+viVK1fue//99zc++uij2y+77LKazuYt9Dt9++23Vw8ZMkRt2bLlgxtuuKHugw8+yBOthfD5fJg2bVrs/fffD61fvz48e/bsLEt4VVWVHjt2rLVhw4b0c77uuuvqb7nlltFdmb/gmj29UBA+sdgJIFDZuzl64kbPsGzWN7cjmrSgSMHUhLZkAhWb9kK12rATCRjhcrQ58ZIeaALgcKnqmi7+SAxGjvUv0BTBkQ+/jF2nzkF8co/fXzqFVOdu9PcCexElC5/3Xu/2teLZsq1wSOOUxBHF5/b6uX+SEoSSyaQxderU6QBw/PHHR6688soDO3fu9I8ePdo69dRT23PHv/DCCxVf/OIXWwYNGqQB4Mwzz2x+/vnnK88777yWYtfkcuaZZ0avuuqqiXv27PE9+OCDQ88888xmv9818hVzo//kJz+pnz179rRgMKhXrVqVjlM86qij2qdPn24BwPnnn9/08ssvV4RCIb19+/bQcccdNxUAbNumY445Jpq6ZunSpc2587/33nvBrVu3hk855ZQpgBsKUF1dnf50d9555zUDwPz589uvueaaAAA899xzgy677LKG1N5Hjhyp3nzzzVCpea677rpxP/zhD8c1NTX5XnzxxY1dWfuCCy5oAoAzzjgjGo1GjQMHDmR9cv3oo48CixYtGtfQ0OC3LMsYP358EgAuv/zyAwsXLpz0ox/9aP/vfve74RdffPGBUj+XvnKj58K9qHv73e9+d/9NN9009oorrsiKM7z77rtHPvzww8PKy8vVfffd96HhdTLr6p7mz58f/+ijj9Y/9thjg5599tlB8+fPn/biiy9umjt3bqLYNQ8//HDVlVdeuR8AFi9e3HT//fdXnXDCCXnPJZOeuNFz6crze/XVVwdt3bo1nHodjUbN5ubmksa/Qr/Tr732WkXqHo899tjElClTSt5foX0yM4gob9O59/GFL3wh+sMf/hA9EeCAiE1ByEZr18LY5baORSDqvhvdyy7/MLYf+9qSaI+xW+5TG2hJtMPXbsMK+mElLQTDZdifbMFQw19UTBogaNadhkTuO2lW3jF7cBlq501FvKrHXpMOUuWbcjbCXu/0zhKEzo5NQ4w6rMTzkxOxIbAPjUZpnUQEKFbgfkoQGggyYzYzKSsrK6ioS/2Hr9g1hTj//PMb77333qrVq1dX/e53v9vR2fj9+/ebsVjMcByHYrGYkRK7uS1OiQjMjBNOOKHtiSee+KjQXIUSoJiZJk2aFH/nnXc2FbomFS/n8/mglCLvmrz/qHY2z0033bR76dKlzTfffPOIiy+++LANGzZs7OyaQveYyYoVKyZceeWVey+88MLWJ598sjJlpZo0aZI9fPhw5/HHH698++23yx977LEPC83f37z55ptlkyZNKiriSmGaZsE2tl0VlaUYPHiwXrZsWcuyZctali5dijVr1gwuJjb37t1rvvHGG4O2bNkSXrFiBZRSRET861//erfR2/f2Tli/fn3ZaaedthfI/tnH4/H0C2bG2rVrN1ZUVHRZ2Rf7ne4JjuNg8+bNZbNmzaqrrq521qxZkxVm0NTUZDQ2NvpmzZqVeOGFF9Li8nvf+179zTffPNrn83V7YXGjC0Im3bVGFqMnbnRlAWRga2wvtrTtR3mZATJc0dgWi7qeaJNgtcehtFusvLRl0+0k1FkP80KwaaJt7uHgqi55ZUpC2lWaue+LlEoQKnAX9WYEcU9gVukybAjsw99DW9PnvxY5DufFXJHcaMRQb+YnRTIIDP2JEpvd5ZRTTon+9a9/HRKJRIy2tjbjr3/969CTTz65ZAbp4MGDVXt7e9Z/Gy677LID99xzz0gAmDdvXqdC5OKLL675wQ9+UHfuuec2rlixIu3KXb9+ffmmTZsCSik88sgjVQsWLIicdNJJ7WvXrq14//33g4Abh/bee++VdJPOmjUr0dTU5Pv73/9eDriu7bVr15Z0XZ522mltd999d7Vtu79X+/btM7syj2mauO666/ZrrWn16tWDOrvmT3/601AAePrppysqKyvVsGHDsn4BI5GIOWHCBBsAUuEJKb761a82XHrppYctXLiwyec7+Lagf/zjH+Hbb799zDe/+c2CLQcHimeeeaa8oaHBBIBEIkFbtmwJ1dTUFC33cf/99w/90pe+1FhXV7d+z5496/fu3fveuHHjrGeeeaZHVrmuoLXGTTfdNKKhocG/ePHiNgAYNmyY/dZbb4WUUsgUdCeccELbbbfdlo6Lfe2118KF5uyM+fPnRx966KGhALBu3brQli1bOp0nmUzSihUrxo0ePdo6/vjj4wsXLowkEgnjV7/61TDAFaLf+MY3xn/1q1/dnyuGv/SlL7W1traaGzdu7DQkIRexbApCJtpGn6RHk9H9ou7KAchAuRFEwo6BfAAY8LVZSFgKFQC030AkFoWphoGK1RNKbYEISiuYJbohheubMGztVuxbMBP2kGxh6dcKgZZ2JIf30rrptScvtFNWDJiUM5zx34Nex2cTE3FCogYf+ZpxwGhHJQfxfGg7IkYSC2PTAQDvBOqwutxNEP5x8+ey5qFUglA/udGrKwJOVzLIuzNfX82V4oQTTohdcMEFjXPnzp0GAF/5ylcaPvvZz8Y3b94cKHbNqFGj1DHHHBOdPHnyDK8Eyu7x48c7RxxxROLss8/OKs2UitlMvb722mvr29vbDZ/Px5dddlmT4ziYO3fu1Mcff7zSMAwcffTR0auvvnrcpk2bwscff3zkK1/5Sotpmrjnnnt2fPnLXz7csiwCgOuvv37PrFmzksX2GAqF+KGHHtp+xRVXTIhEIqZSii6//PJ9pYTwt771rYYtW7YEp06dOsPn8/GyZcsavv/97zd0ZR7DMHDttdfW/fSnPx21ePHitlLXDB06VM2ZM2dqNBo1f/Ob3+RZa3/wgx/ULVmy5IiRI0da8+bNa9+1a1daWC9ZsqR1xYoV5vLly3tc7mbp0qWHp0ofVVVVOa+99toWoMOVnRq3Zs2abYD7M5w2bdr0eDxuDBs2zL799tt39bTEU3cptKcjjzwyT0Ru2bIltGLFiomA2xrxtNNOa122bFleeEWKv/zlL8O+853v1GceO+ecc5rvv//+qi984QvRYtelYjZTry+66KID1113XUnhfd1114279dZbRycSCWPOnDntzz333OaUFfI///M/95xzzjmTRo8ebU+dOjWe+hD3m9/8pvbSSy+dMGXKlOlKKTr++OMj8+fP73ZZrGuuuabh/PPPr5kyZcr0mTNnxo488sj40KFDC366Xrp06eGBQEBblmUsWLCg7amnntoGuL/bjz322Lbly5dPvP3220c3NTX5zj777OZU1YFcrr322vqLLrpoUnf3Sr2Jzxho5s2bx2vXrh3obQifJBKtwPurgcpexik6SddKetS5Xb9m9zpg/wd4IdaAD3Y1Y9qQkdjaug9l26MwQjaqY81oC5Uh4VTAf8QYxOIHULU7Cl1R2KCjmRF14gibgaJF2Mt2H8Dwf27Gns8fA1WePU/V29tR/Y/N2HrJ6dDBnmkqI5qEPXkkLF2GZHMYZqhDTzkJH8obaxEoS2YJThsK/69sE4LsQ4UO4JmyrVjedhzGqyF4OrwFEUris8ka/G9oKzYHDmCKNRynJiZhjMoWxW3JBKaEKzFj9hdReeK/dmvfRLSOmedlHnv33Xd3zJ49u2Qc3SeVSCRiTJ8+ffo777yzMddS11WefPLJyjvuuGPkwSqVNBAcd9xxR/70pz+tLRQz2RVeeumlsm9961vj161bt7nz0cKnHcdxYFkWlZWV8YYNG4Kf+9znpmzfvv393pRdevbZZ8uXLVt2+J///OftCxYs6Nbv8bvvvjt89uzZNYXOiWVTEDLRhQuldxuioi5527bBzAgEcoxL2nWjJ5QDzYyISsJnaZClYRvKjT/0mXDiNkyd3dqy2BYUNMwSmfWxccOxa9zwgucih4+CNagM3JsYp8zC7jmmTcPUSFoVrtj0cKBRb0ZwSvwI/HTwSzg1MQkrWv8FQ7XrtflcfDIIhHozghYjgfmJiZhqV+cJzdSCWutPZDb6weSxxx6rvPzyy2suv/zyfT0VmkLnfP/73x/1+9//vnrVqlUFY1cFIZdIJGIsWLDgSNu2iZlx55137uxtfc/TTz+9va6ubn1f7TGFiE1ByMSKok/UZgE3ulIKpmli165dSCaTmD59evY1ygbIgOWJo3YVR8hy4Dc17HYbyYDbR9xiRkA5bo3KUm50EBzWJXuil8IeXA57cH7M5gi7FgCw3z++80k4FZtJyH2uhl8D2o2tTO3wxdCHeCH8IU6NT8IIVYHZydEYwmEwGA+Uv4Ug+3BebBZGq0qsiMwHADQbcbzrr8d0ewT8yBbWGrrfOgh9Wli0aFFk0aJFvf6Pz1lnnRXpTseRjyP//Oc/e2yRvOWWW/becsstWa7LzI49Kc4555ymYi7OvmQg1l69evWgH/zgB+Myj40fPz757LPPbu+vNT/ODB06VL///vsbB3ofXUHEpiBk0rwT8HVawq1zCvRG37x5M8aMGQOtNVJJCplsbP0IEzXBchy3v7lWqGxLwBc2EAmHwQFAaQLDAcjyLIalhXF1oHS85fjHXke0ZiSajz48/6TSCDZH4ZQHocIdz2Rq4i1UqQY8Nvir7n2WxA3YLLhLpTGJ3kFUD0a5jqDBNxoLEoeh1UjgjeAufKPtM9jpa8Fb5h6ckpiESc5wrA/sRRIOgvAhTjbaKIFaXyvWlH+Ab7WegCqdGbdO0MxuLU9B+BiS2bHn07D24sWL2xYvXtyr0kPCoYmITUHIpK2u9zU2gY46m+wWLddaIx6Pw3Fc13rKlZ6ZKb4psgu2rwJJpQACHNuCP+5AlwdRrgMoM0wQAwm0A1BujcoeJDOZ8SRGPf8e7MoyOBUhqFDheExfLImaR17B3hOPQuu0Divm2rKTocjXBaHpwQDr/H2OSO7Csebz2G7PQII+wKPlx+JYazLmWmNgghBmP54ocz+0n5KYhM8kJ+DY5DiYXhGN14O78Hx4O77WdhyuaP0sBuvsmNNUNv6nORtdEAThUEDEpiCk0Bqw2oFgH4hNwIvbVIDpg2VZSCaTSCQSsG0bjuPAcRykCkxr1kiqBPYyw9EajlbwWRYAAohAxLCYQEQIkx+20oDS6El7H39bDBW73La7m5efUXQOVRbAns/PRWJ4R2dCH1uIGZXdbDHpdRDKqRvcblRivf4MDvhG4eXyIP5WXotjrSmocapQ47jeu6tbFyDTLmpmVGubn5iAoTqM8WpwhiMe2ODfxGpCcAAAIABJREFUh4cq3sXClukYpUZJzKYgCMIAI2JTEFLYXuJdX/bqZgXAh2QyCa012tvbYds2iAgNDQ1oa2vD1KlTYWsbYI36lgQsxwQTQyWTSLnJDTBsbcAghmkYaFNJ+JTTo+jSxMih+Oj8BfC1J0qKVTZNRA8blXVsVuw1DFUNeC/8L5hgbcVbZSeCO7Nwau82cpZq9w3Fev0ZVJhtmGsPxqzmGfDllP4NlniLCsGPOdYY2FDYENiHbb5GHJsch4cq3gUAVKlyKInZFARBGHBEbApCCjvexxNSuiuQ4zgIBAJobW0FEcEwDDQ0NEB5QiipkjCYEbc0WBGGByoQYgU23D2ZBNia4Ddc93CI/AgAABUtRVgSq6oSVlXnFtxgYxuYKD223l+DZt8IhHUMVWo//JyERaXqCFO6g1Cm1vTrOIYm6rEfw0DMGGHXImZUImoO6fa9+GBgt9mKCg6gSpfh36KzMEJVoEKFoQ0bedXkBUEQhIOKiE1BSOHE0Td1jzLwXLjxeByZHUGUUnAcB1praK1hKQusFcJUBjZM+AwTvqQGTNfSR+RmbStmmGCUkR8GOz2ywo54ZQNiY4YhevioTseOev49qKAfu88+HgBQH6hJn9sVnNK1BZkBzrZY1sTex2eaHseTWAqLQ9htvIp9vgkYz/O7fB8pCISz4tPSr2fa7n3F4cBhBqt+6o3+zoNDEN3fd++hFSMcHH1hS6khpmkeM3ny5PSnoi996UtNuRnMfcmDDz44eMOGDeH+XCPFXXfdNez6668fN3LkSDuZTNLFF1/ccP311/eok83mzZsDZ5111uStW7du6Iu9Pfnkk5VLliw5YuzYsRbQUSx95cqVYx544IHhVVVV6Tpnr7zyyuY33nijLHM8ANx66621ixYtiqR+ho7jkGmavGTJksYf/vCH+0wzv0RZZnb2rl27giNGjLBDoZAeOXKktW3btvDrr7++ccKECQ4AXHTRRRMmTJhgzZ///7N35vFR1Pf/f31mZu/NtSH3CbmXHEBSLkEFxRsaoHgUKlXgW/DnjRa/PUBbWkVAv1VrvQU82qIoCLYiaAVEkQYxBHIQkEDIQci1u9ljzs/vj9ndbO5wqeA+H499JDszn2OOnXnP+xzvvO2229ISExMFnufJ9OnTW1evXt3QfR8C59TbPi9ZsiR2w4YNkQzDUIZh8Pzzzx9//PHHY2tra3Uul4tpa2vjfH09++yzx70pc7jk5OT8xx9//MTDDz/cDAD5+fnZgiAwNpuN9Xg8TExMjAioCdwnT56cZTKZZF8JybFjxzrWrFlT29d58F0jsbGxosvlYpKSkvhly5bVT5kypf/atX0QeJ3s3LnT+Nprr0X2N/5gCbwu3G43k5WV5X788cfrCgsLPYBaBemuu+5K3LZtWxghBGlpaZ6XXnrpREZGhgAAhJDC+fPnn3r55ZdPAsDSpUtjOjo62Keeeqr+XOf2fREUNoME8SGp92BRVnDa5kb8uZZqJACoDEopXG4XWJaFXq8GsbS3t/sDhCRJgiiLgCJDBx3AEBACEI8IygUKaRQyJdCAQlaoP/joTGB4EcaTzZBM/Vb289N0mRWSQc0HSqgCLfWAJ4YzGJeq9c+7mdG/NRbAIxvQ1hwNI3FifWgyKDT4xVk9MlSOcM1oZl1IlSLwt5A9uMyViimueNAL5bPZ0cQhLPEMy0T1g+3kgJnz+6qNfiEQRRGzZ8+2AbB9F+MBwNSpU9vWrVt3orGxkc3JycmdPXt2W3p6+vk7xudAUVFRR28J6fuq+93X9oHnsK6ujps1a9Ywm83GPv300z0EicDo7O4J45988smoe+65J2nTpk3HPv/8c+PevXvNr776asW2bdvMvrHtdjuTl5dnLS4utvU3p+5s377dtHXr1vCysrJyg8FAGxoaOJ7niS8FUV8J+tetWxdRUFDgfOeddyJ9wuaBAwcqAVVQLCkpMa1bt65LpZwdO3YcjouLG3T1LN81AgCbN28Oue2229I//vjjqr7qpA+Wyy+/3HW2yfh7I/C6ePnllyOuvfbarAMHDhyKj4+X7r333oSOjg7m2LFjBzmOw1/+8pfIadOmpR88eLCcZVlotVr6r3/9K6KhoaHxTI7ND5lgbfQgQXyILoBh4fSIaHF0NakfO2XDqXZVEhKkQQovFIAi42j7UZScLIGEznuGoih+E7okSZAUSRVMFaJa3glAZO8/fggAAsIQNThIoWf8C1Z0GtTcegVaR6YNant3nAViuFpOOERpw/X2txEv1gCUYoRrJ4byA8k9BFCUTjM6VcApAmRGi5O6LLV+OSWY4xyP2c6iAfrqn136GnxorMQrIXsx0TMUKWIEZOoNpLqEaWlpYVNTU3NLS0t1ADB16tShq1evHgIARqNx5IIFCxKtVmvOuHHjMuvr6zkAOHTokG7ixIkZw4cPzyksLMzav3+/HgBmzpyZOn/+/MQxY8Zk3nXXXYnPPPNM5O23354MAPX19dy1116blpubm5Obm5vz8ccfmwBVizNr1qzU0aNHZyUmJuYtX77cX/P5ueeei8zMzLRmZWVZi4uLh/bXTyCxsbFycnIyX1tbqxlo7OLi4qFjx47NTElJyfXtdyBVVVXawsLCLKvVmmO1WnO2bdtmAoDi4uKhb775pt9vY9q0aUPfeuutsO7tLyQJCQnSK6+8UvP6669HK2dYVnXx4sWnjx8/rtu8eXPIPffck/yXv/zlhE6n62KaCQ0NVfLy8lxVVVVnlM+trq5OY7FYJIPBQAEgLi5OSk1NHVDof+eddyyrVq2qbWxs1Bw7duy8lXLti6lTpzrmzJlz+q9//WsUoArkO3fuNAJAQ0MDl5CQkAeo99hf/epXibm5uTmZmZnWlStX9rhOtmzZEjJp0qR0oP9r+uGHH44bOnTo8PHjx2dMnTp16NKlS2MGmueCBQvaJk6caHv11VctDoeDWb9+/ZAXXnih1mftuu+++1qMRqO8adOmUABgWZbefvvtp//85z8P2PfFQlDYDBLEh+gEGA0kWYEgdhUoXbyEhlYXFEpRXd8OtzCIl00CgCoQJAHN9mZU26r9qyil/kAhSZIgK6KqBPSW8iYEPYVJX15NQkBkBURWQM9HHfd+YAQR5mON4Bxu8MSAUsN4tHFDAEJgVDqgUwbwc2UIiELVpO6EIkRqxa0nlyPFWabuCoAdxsP4SL8P8eIZlwbuwkxnLhbYR+Pmjnxc7UnHMHEIZFDQC1Qb/fuA53kmOzvb6vu8/PLLEZGRkfLTTz99Yu7cuUNfeumliPb2dm7x4sXNAOB2u5lRo0a5ysvLKy677DLHI488Eg8A8+fPT3n++edPHDp0qGLlypUnFy1alOwb4+jRo/rdu3cf9pnwfPzqV79KevDBB08dPHiw4v333z+6cOHCVN+6I0eO6Hfs2HH4v//9b8WqVavieZ4nJSUl+lWrVsXt2LHjcFVVVfmLL754YqB+fFRXV2t5nmfGjBnjHqhNRUWFYfv27dV79uypXLlyZXxNTU0XISc+Pl7atWvX4fLy8op//vOf3z7wwAPJALBgwYLTa9asiQRUgX3fvn3mm2++uU8trq8OfHZ2tnXJkiV+H5QXXnghxrd8zJgxmb1tn52dbT106FCvAp/VahUURUFdXd0ZWRpZlsXzzz9/fM6cOWnDhg3zXH/99T1qfjc2NrL79+83jRgxwn0mcyouLrbX19drU1NTc+fMmZP84Ycfmgeaz5EjRzTNzc2aSZMmuaZNm9a2du1ay0BtAOCKK67I9M3nscceix64RVcKCwtd1dXV/Zpq/u///m9IWFiYfPDgwYrS0tKKtWvXRlVWVmr7a9PbNb1z507j5s2bI8rKyso//PDDowcOHBi0+WvkyJGuyspKfXl5uS4uLk6wWCxdbkwjRoxwHTx40L8fDz/8cNN7771naWlp6bsE3EVE0IweJIgPwQUwHFy8BFmhkBUFrNeXiOMYONwi7C4BTo8IZRCJwm2SB3trP0OoMQkMYcAElH00Go3weDyglKr1bRWPNzMQhUIBEiBY+iEE/jTulHpTHw021yWFrsWO8IPHoeg0OD0uZ+A2AFiXgIStX6NhcgHsmQk4puusevSF+YaBhwW8QrNaQUgiWpSGTUKrNh7w6kkEokBLW5HnPoJGTcrg9qcXQqkeobJ6r1ZAIRMKKlNQKKCKAnIuZTd/IPRlRp8+fbp9/fr1Eb/+9a9T9u3b5/dTZBgG8+fPbwWAO++8s2XGjBnpNpuN2b9/v3nWrFl+9bYgCP4LbcaMGW2B/sU+du/eHVpdXe2PBuvo6GDb2toYALjmmmvaDQYDNRgMksViEU+ePMlt3bo1dOrUqW0+M2BMTIw8UD+bN2+OSE9PD6mpqdGvXr26xmg00oHaXH/99e1ms5mazWZp3Lhx9l27dplGjx7tN4cKgkDmzZuXUl5ebmAYBsePH9cBwI033thx//33p9TV1XFvvfVWxI033tjmS0XWG+fLjN4b9CyD2MaPH+/OyMhw33333V18W0tKSsw5OTlWhmHofffd11hUVOTZsmWLZrBzCgsLUw4ePFj+0UcfhXzyySchc+fOTVu6dOnJe++9t6WvNmvXrrVMmzatDQB+8YtftM6bNy/10Ucf7XFcunOmZvTuDObYbd++PbSystL4wQcfRACAw+Fgy8vL9cOHD+/T9N7bNf3ZZ5+ZfdcbADplypR+fax7m6eiKCCE9Jh09/2wWCzKrFmzWp544olog8Fw0b8xB4XNIEF8eIVNN897hU3qi8+BLKuBPM12NzyirPpMDsBRvgUNTgVuSQstq1X9Mr0YDAYYDAY4HA6IogiR8iBgoFA1gF198nfXWnrzVTKqZhMKVcPUB4G2rQOp7+6GwjKwZQ+izKQXMcSAmp9NgBhqgEHpgAwWAtNf9Hkv+KLRCeDmQlEWNgkAQLx5RK92WhHKRuPzAXUn/VOuacJufQ3mOkbh+dA9iJNCMa0tWb2JX+IR6bIs4/Dhw3qdTqc0NzdzaWlpvZo8CSGQZRkhISFSX76fZrO51wcbpRQlJSUV3gdtFwLNtyzLQpIk4vVJ7vWh2lc/Pn+87du3m2bOnJkxffp0W3JystRfG9LNf7j79z/96U8x0dHR4oYNG44pigKDwVDoW3fzzTe3vPLKK5YNGzZYXnvttZre9vtCU15ermVZFgkJCWclcDEMg+7BRWci6PYFx3H+EqP5+fnuN954I7I/YXPDhg2W5uZmzXvvvWcBgKamJk1ZWZkuLy/v7FJmDJKvv/7amJmZ6fbOmfrck1wul/9CoJSS1atXn5g5c6Y9sG1VVVWf2s2+rumz5ZtvvjEWFha6hg8fztfX1+va2tqYiIgI/2/twIEDxltuuaUtsM3//u//nho1apT11ltvbT7rgX8gXPyv+kGCnAmyCDT1UUpWVIVNXpTV6jMBAqUke/NbugSwDIE8gGmWUorjfBs4wsLFu6BhNKpfZjcYhgHP8xBlHoQS+OWiXrrXMhRa1mtjV6hqnh6MrOm1yzdcmYdv50xC08Thg2jkhWXADwmFotVguHsvruj4wL/KLLdhouMDWCQ1UFkBhY141NyW/h0kIF6fTRAKnexUo+jVr6qmVgHcjBlu5tykTRcRcIJrh4dIGO9JgVWIgUKJmhT+EjKl98Yf/vCHmMzMTM/atWu/nTdvXirP8wRQtSivv/56BACsWbMmcvTo0Q6LxaIkJiYKr732WoRvmy+//HLAN4gJEybYV6xY4TdzfvHFF/22ue666+wffPCBpbGxkQWAU6dOsYPt5+qrr3bOmDGjZcWKFTEDtfn3v/8d7nK5SGNjI7tnz56QCRMmdAkzs9lsbFxcnOg1O0fKAXlXFy5c2Pziiy/GAEBRUdE5BZicDfX19dyCBQtS7rjjjibmB6R5Ly0t1ZWVlflN7Pv37zckJiYK/W3vcrnYpqamA3V1dWV1dXVld999d+O6desGZUo/Wz788EPzm2++GXXXXXc1A2od9b1795oA4K233orwbTdlyhTb3/72tyjf7+LAgQM6u91+xgf8yiuv7Ni6dWuYy+UiNpuN2b59+6Byta1ZsyZ8165dYXfeeWdraGio8rOf/ax50aJFSb6Kcs8991ykTqdTpkyZ0sUVIiYmRp46dWrb22+/3cPH9GIjqNkM8uOCdwCnDgFaMxDeTcMnukE1JgiSDJYFZDlA2FQUhBg16PCI0HAMpAGCThyyByKVEaYx4qTNBiNjhECFHiUqWZYFz/PgNW41/yYhUBiA9BJBTUiAbKmoUd6DETY1DjeG/nMnGibld6lxPlhMx09B0WrwbZQVOqXzeSwRLSgYEG+6KBcRsCp8J250ZWMsn9zZgUz9yeOvaP4HAIqPY+YDoGjSteLjyL34qSsR4912NGhSITCDi5TvTqGQgBFCPDgwGC0kQVIAATYoiqIe97PqtR/M0dJgIsjPqL8B8Pls+r5PnjzZtnDhwuY33nhjyL59+yoiIiKUd9991/HII4/EPf300/UGg0E5dOiQYfjw4bEhISHye++99y0A/P3vf/92wYIFKStWrIiTJIlMnz69ddy4cf064L700ku18+fPT87MzLTKskzGjBnjGD9+fJ+OtkVFRZ7Fixc3TJw4MZthGJqbm+vasGFDzWD7WbZsWWNRUZF1+fLlDf21GTlypPOqq67KqK+v1z700EMNqampYqDG6v7772+aOXNm2saNGyMmTJjgCDRJJiUlSWlpaZ6pU6cO2hzanRdeeCFm/fr1kb7vmzZtOgJ0+kf6li9ZsqThjjvuaPOdQ1/qo1tuuaVl2bJlA5qbzwd9zan7dna7nb333nuT7XY7y7IsTU1N5deuXXu8r37Xrl0becMNN3Tp59Zbb237+c9/PmzlypUN/c3piiuuyPQJ2jk5Oa7333+/pr/tN2/eHJGdnW32eDxMYmIi//bbbx/xRaI/8sgjp2655ZZh//jHPyInTpzo12I+8MADzTU1Nbq8vLwcSimxWCziv/71r6P9jdPHXF3XXXedzWq1Dk9ISODz8/OdYWFhvUaM+q4Lt9vNZGZmurdu3VoVHx8vAcCzzz5bt2jRosRhw4blejwexmKxSCUlJRW9vXD89re/bVy7dm3Umc71h8Y5qYW/b4qKimhJScn3PY0gFxOuVuDgewCnBfJvATiv8KUowL7XIZpi8c23TQAIMuPDwXEMOtwiTpx2IMSgASEEHW4RcRFGxEeqmjinR8SRxnZkJURAr1Hf35oEGz6r/xJRSeNxpNkOo2CEm7gxLn4cOKbzHU8URXg8HjTjOOx1eyDyFuj0DIhHhOZwIxRzT+GQiBLAMCBusdf13WF4EebjTXDFRkAKNZ7xIUv9xw7wkaFomDKy3+08kPCp4QiiZTOKhER1rrwEatCgXTMUjFZGslu13NYarXA4WvC38PfAUgYPtaVgjm0HdplvQgs3cP7PgZCgQFAUUMGJyQmXIWbWbWD0gxdiCSH7KKVdwuNLS0trCgoKLipzltFoHOlyufZ/3/O4UDz44IPxZrNZ7s1ncjA4HA7GarVav/nmm4rIyMhgqakgA2Kz2ZiwsDDF4XAw48aNy3rhhReOT5gw4axTJp04cYK75pprMufPn9/00EMPXVT3l+6UlpYOKSgoSO1tXVCzGeTHhSKplYIUURU8Q+PU5bI3x6akqHW2CdDhEcEwBC12D4BOjSTDqJpOH5KioL2Dx/EmB1KjQ6HTsOAVCRQUBAqG6IbAI3m8KSfVBO5aVlW8sCwLu90Ot9YDt5OF3uDVv/Vj9qUgYKTBm4UVnQb2zIQzOEhdqbu+CFq7E5GttbBFxEAi3dycvA6ZenCwMR58ratHM+vECD4eccSgamCpul+1xs4AIzd1Qydz+GnrOISxGmwNjYOHnLkw3Bv/MJXCxngw97T1R+GzGeTM2bhxY8iiRYtSFy1adCooaAYZLHPmzEmprq428DxPbr311pZzETQBIDk5uU//6UuJoLAZ5MeFIgE6k+os6G7vFDYVtRpPXUsHCEOg17BotrsRZzF582p2GmEZQsCLncIepYBRx8HuElDb7EBabBh4RVSFVgoosgJCCAgl4GUe37Z/i/yofH/ZSkO4ASdO2QCZ+IPLe4ZVBMAQQBz8s1FjU13YxLAzS1L/le4EUqQIxIaYMHT9TkRmOFA7fhROatMBqGZzUSnHdPsh7AydBRsDFPIJKBDi8I6pDIlSmCpset0RtNQDveSEg4sACINYMQIP1PwUMmeAHHIabub83Y5GCfFwQwJAQKl8yfts9sWlrNUEgHOpqFJcXOwoLi4uC1wWWLHHR1JSEu9LZn4h+T7GbmxsZK+88sqs7ss/++yzqtjY2KAA3gubN28+9n3P4WIkKGwG+XGhyKp0yHDe8pS+5WqeS6dHhEHLgmUYuHgJikJ7+GcyDIEYEGSgpkEiCDFo0GL3INyohZ16oGFYQJEgy6yaiJ2qNdBFWYSoiH7tZovQAt4tQA/S6c/ZnyaOUQOEBsuQkmoYGlrx7ZzJPdZ9ra1DI+vA5Z6hMFEtXESEiWrRyDiwXX8Es5x5iGVC0HBNARwhTrRxcf62R7lWrDc3YZgYAxkcSnQ12G44gnw+FiOEeOSKsaCQ1SB6APHualzesh4fxi5EqzYBUCj+mvIvODg3Hmu+HkOlcjiZEDRr4ge9b31hFWMgU8AFBxSqnHVqmSA/LgIr9vwYxo6NjZV/DFq1IN8/P5zwtyBBvgsUVdulCps8FEWBx+MBZNXsLcoKmIAAHo8ogxflLrIfQwhEqXOB4l1JCIFWw+CUzY2jdXaw4NTqOZJqgqeUokPoAK/wcAcIuk7RCTfvgSwFhLAo/oyaPfFGow/WNNxaMAyNV+T1ui5CMeBL/QkooPjIcBgvhnwFDyQYqAYjhXgkympBFUdKPBosGfAwndpRG+NBthCFBs2VoIRBthCF6c7h0IGDCLlzrt44ptO6ZHxpKUa7Ri2KcYyrh0HR4oq2UQCAHE8JEsVzytbiR4QMF1FTKwHKj1azGSRIkCA/BILCZpAfF9QrdDAsIHngdDpRXV0NWeL9lXt82kUCwCNIMOk1CA8IxGEZAjFA2ykr1J97nWMY8KIMp1sCZBagkt+MzjEc2vl2CIqAqtYqtLhboFAFTtEJRSdCHxjro3QrJt4dZfACFD8kFK6knsGMHxmq0MA68Jv2SQileliFaIzlk8GAIIzqcZknFQc1pyBAgtnRgtjqKhCxM31jA2tHByPgjZAS1DI1iFFCMEpIwGg+CZGKEVsNhwEC/Fdbi3rmFFxcGI6YC6EQ1aDSytphZ10otGeBUoJPQ2ag1DBhUPs0ENsM1fhL2OeglEKhQWEzSJAgQb5PgsJmkB8XsogOQQYvAaLHDUmSYLfb4XTYIfvyQQYgSDI4tuvPxKel9OXalGVvUBEAlmXgFmRIVAZRWCiSrFaMYAh0rA4e2QNBFtDiacFp92lI3kCiONMQaDUBwqWkoE/NJgCiUBBpYM0mw4swnWhSI9i70cK4sEt/DBxV9y9FjsB4PgVasLARD05yNmw2VaCBdSDhZCXCPjkKXVtnGrhZrnzMd/wE8ZITdWypf3msHAKByPiWa4UIBR+EV+IL7V7Euw9DK3f60hfZ0/FAXTFYsAAYCIwBlJyfW5JVjME17gy1nCelQTN6kCBBgnyPBH02g1z0SIrUJZ1Qv8gCjp7mERamg/P0KYSGdkAQBAgeDzTd0lZSqAoxro/KtL4KQ3JAVUmWISCgkBgFoCxEvlMTyDEcnKITelYPk8YEj+SBqKjrNd3mT3gRlO1H8Bqkz6bxZDMStu3H8enj4YkJxxCxHqlCJUpMkzHLmYcybSPYgHdOFxFwkrXhfdMhpEgReNA2EeGKHidTchD602bwkaFd+mfBYGbHcJgUN04HBKlf486AjXjwpeEEHj05CXxoJK5qeQqvRl2Jz40mTKZjvQeXUX06KRAtnoRJseGY7gySzkNtS+FP5QkASJUikEIjYEdHMBo9SJAgQb5nLpiwSQjRA9gJQOcd511K6TJCyFAA/wBgAfA1gF9QSgVCiA7AOgCFAFoA3EIprblQ8/tekAQ1v2OQ84ZCFeys3Ykrk68EMwitmOBxwS1SsLwCl8sDarNBp9PB5XRAT7uarVUTLAXppV8C+CsMyYrSpYR5RIgecCtQZKaLsEkIgUhFEEqgYTRwS27I1OvbqHSNeCe8CPQjbBJZgcINvL/O5CjUTh0NzxBVSEwRqkBA0UZcoAQYJST4tbIAUKE5jY2mQ7jSPQzDJAsiFLVQi9NogdPYtRjIR4YqJEhhyEMsuuf+ICA4ydmw3XgEwxwRCGPT8GH0HfhYX4XTpB2gwN6QwxA0Csa2jwQFQax4HAnisTMWNj0Kg2NOA+L0PEI1ElgCCJDhJqJaoegCmdE3HtkY3upuPW/3UIvBIhWnF/ebXJxl2cKMjAy/w++MGTNa//znPzeerzl056233go7dOiQ4UKO4eOZZ56JXLZsWWJMTIzI8zz55S9/eXrZsmVNA7fsSVVVlfamm27KqK6uPjTw1gOzZcuWkNtuuy0tISFBAACLxSJ98cUXhx988MH4N998c4jFYvGbDj7//POqPXv2GAO3B4Annniitri42OE7h76k7rfddlvL73//+1PdS04CXSPUT5w4oYuOjhb1er0SExMjHDlyxPDll19WJCcnSwAwZ86c5OTkZGH8+PHO2267LS0xMVHgeZ5Mnz69dfXq1Q3d9yFwTr3t85IlS2I3bNgQyTAMZRgGzz///PHHH388tra2VudyuZi2tjbO19ezzz57fMqUKc76+nouOTk5//HHHz/x8MMPNwNAfn5+tiAIjM1mYz0eDxMTEyMCavL7yZMnZ5lMJtmXzHzs2LGONWvW1AbOI/AYu91uJisry/3444/XFRYWnlXFpy1btoSsXr065j//+c+R83l9z5w5M3XPnj0hZrNZ5nkUUa50AAAgAElEQVSeGTlyZMdTTz1VN3ToUBEAWlpa2Pnz5yeVlJSYAbUYwauvvnoiKipKrqqq0mZnZ+ctX7689re//W0TANx+++3JRUVFzv5KhF5MXEjNJg9gMqW0gxCiAfA5IeTfAB4E8DSl9B+EkBcAzAPwN+/fNkppOiHkVgArANxyAef33dJ+AmgoBXKmft8zuShpb2+H2WwGx3W9ZCVFgltywyN5YNQMnKNRFnhQELgEBU4PD85lh16ng9vVDhlMF8O1pFDwkuqz2R0KNSenQatGowdWBZKorObilACIEgjXuY6XeGgYDRiGgUhFCJLQWbOxi7ApgfYjTEpDzOjXpxNASHU9dK12NI/O8qte95kmgaEC1pv3wUkE3GefCDagnyxxCOY5foIEKRQasHARER8Yy1HcYURcnQ6ioEXHMDXpeqXmNBjKYIQQCbNsQwcbBpl0HqtsMRpPNqci0nMafxzyAQQiYgLGoYO6UE2Po0lrg1vje0YTHDKMQZlhXL/71BuUApJCcNxlwFCTC2EaGf/V1eIj42H8P88YVdi8AJrNVncrF2uK7bUG+dnQ6GwcsBqRTqdTvqvoYVEUMXv2bBsA23cxHtBZG72xsZHNycnJnT17dlt6evp5O8bnQl/1xhcuXHiqt6TyfW0feA7r6uq4WbNmDbPZbOzTTz/dI41TYIT66NGjs1atWlV7+eWXuwDgySefjLrnnnuSNm3adOzzzz837t271/zqq69WbNu2zewb2263M3l5edbi4mJbf3Pqzvbt201bt24NLysrKzcYDLShoYHjeZ740jAFCmyB7datWxdRUFDgfOeddyJ9wuaBAwcqAfVloqSkxLRu3bou1aJ27NhxOC4urt/qWYHH+OWXX4649tprsw4cOHDIV5HnbDnf1/fy5ctP3nHHHW2KouCPf/xj9KRJk7IqKysP6fV6Onv27BSr1ep5//33DwLAAw88EH/rrbemfvLJJ0cB9QXmxRdfjF68ePFpvV5/yZliLpjPJlXxOXhpvB8KYDKAd73L1wIo9v7/U+93eNdfRQKf4Bcz9nqgoQwQOgbeNkiv1NfXo729p9LHJ2y6pMHl1VUkHhzLQqvlEKYFHEf/Cz0rw+V29UhdGWbUwtJHhR6WIWjtUF+sZUVB5Omv/AKNTFUfTVkhUKSugmiUIQqRBn9lu855U7nTFq9Qb5Wgfi5/lgHY/n8eLC/AXNMEdPsZUXB4tf4wHm7VdTGhA4CZ6pAqRUADVcsiEAk1XBuihBLElFUhak+lf9v77RNwjScDFukUJnVsRLjc9QWcA4NCzxEMoxW4p+UQ5p52Isylw4fMZ3if+xgTWnPwsxY1IIgqBDLhzspn08gpGB7WgaEmN0ysqsFMkyIxzWkFSxkoigx6BqmiLjZaWlrY1NTU3NLSUh0ATJ06dejq1auHAGoFoQULFiRardaccePGZdbX13MAcOjQId3EiRMzhg8fnlNYWJi1f/9+PaBqZ+bPn584ZsyYzLvuuivxmWeeibz99tuTAbWO97XXXpuWm5ubk5ubm/Pxxx+bAFXzNGvWrNTRo0dnJSYm5i1fvtxfw/y5556LzMzMtGZlZVmLi4uH9tdPILGxsXJycjJfW1urGWjs4uLioWPHjs1MSUnJ9e13IFVVVdrCwsIsq9WaY7Vac7Zt22YCgOLi4qFvvvmmv7b1tGnThr711lth5+esDI6EhATplVdeqXn99dejlTPUvi9evPj08ePHdZs3bw655557kv/yl7+c0Ol0XS700NBQJS8vz1VVVXVGdWrr6uo0FotFMhgMFADi4uKk1NTUAYX+d955x7Jq1araxsZGzbFjx85fKdcAFixY0DZx4kTbq6++agGAhISEvIaGBg4Adu7caRw9enQWANjtdmbWrFmpubm5OTk5OdbAc+0j8PqeOXNm6i9/+cukkSNHZicmJua9/vrrEQAgyzLmzJmTnJ6ePnzSpEnpV1xxRbpvXV8wDINly5Y1DRkyRHz33XfDDh48qCsrKzM9+eST/heKlStX1ldWVhp9v1uLxSJNmDDB8de//jWy754vXi5ogBAhhCWEfAOgCcA2AEcBtFNKfW8jJwH4SpskAKgFAO96G4BL46C72wFPOyCeldY/CABJktDbzVhURLhkV5dUQv1BhQ4QloFBy8EEJ2L0AlhCIPE82t0KuAABjmOZHsFBPvRaDq0ODyil0LYdQdLRNxFR96k6V6p4sxMRyJKs5tj0ouN0nf6lFGjn21Xzf6CwSb2R6Gf5rhV+8DjiPyoBbwnFqQmdJulY8TiGubeBQESTdjRCMWzAvsIUPZa0Xw6GvQZ140fg+MzLemxjY4fgK+NVsDPhiBJP4sb2dcjyfA0A2G26Hl+Sa2BWroLRlYAm2gxQIF/ORIRk8pvwKWUQIrch270PWmVw59KHQlW5O0wjgWPUZ22sHIKfCIngQKBI7s4sBBc5vrravs/LL78cERkZKT/99NMn5s6dO/Sll16KaG9v5xYvXtwMAG63mxk1apSrvLy84rLLLnM88sgj8QAwf/78lOeff/7EoUOHKlauXHly0aJF/mL2R48e1e/evfvwyy+/fDJw7F/96ldJDz744KmDBw9WvP/++0cXLlyY6lt35MgR/Y4dOw7/97//rVi1alU8z/OkpKREv2rVqrgdO3YcrqqqKn/xxRdPDNSPj+rqai3P88yYMWPcA7WpqKgwbN++vXrPnj2VK1eujK+pqeki5MTHx0u7du06XF5eXvHPf/7z2wceeCAZABYsWHB6zZo1kYAqsO/bt898880396nl8tUVz87Oti5ZssRfU/WFF16I8S0fM2ZMZm/bZ2dnWw8dOtSrwGe1WgVFUVBXV3dGlkaWZfH8888fnzNnTtqwYcM8119/fQ9tRmNjI7t//37TiBEj3Gcyp+LiYnt9fb02NTU1d86cOckffviheaD5HDlyRNPc3KyZNGmSa9q0aW1r1661DNQGUGuj++bz2GOPRQ/cAhg5cqSrsrKy3/qzv/nNb+ImTZpkP3jwYMWuXbuqfve73yXa7fZ+ZZ5Tp05pSkpKKjdt2lS9bNmyBEDV1tbW1mqrqqoOrV27tmb//v0DHgsf+fn5roqKCn1paanearW6Ai1zHMfBarW6Dhw4YPAtW7p0acNzzz0XI0nnpLD9QXJBA4QopTKAEYSQcADvA8jpbTPv396erD3UEYSQ/wHwPwCQnJzco8EPEo0BcJ4GtCZAlgA2GJd1pkiSBFnuqnosby6HXqOHIAtwis6BO6EUiqsN1Fdu0TIUxNWqCiKKhA5ZAacb3PsXyxAokgTlwHqwUgRao8ch+tt30RGZB4UzAaBQZAJFksHwIqDpec4ZwsAhOKBjdV3N6Odq8lUUEJnCHd/1Xq+hPF4IF9CgKcPcjqI+GneFeIVeGxcJBOh8WhkXPtUfxQRPKmIRggbtUABAO6JwWJ+P41pvURJCIBAdDjOF+Dx0J/aE7sJ98lzoRA5Am3cMCoUyMCl2ZPH70aBJgcAYMBhkCpTZQpBidMPMyXBILCI0EkQiw8nwUAgD6mq/ZFIf9WVGnz59un39+vURv/71r1P27dvn91NkGAbz589vBYA777yzZcaMGek2m43Zv3+/edasWWm+7QRB8N9/Z8yY0dbdXQUAdu/eHVpdXe0/MR0dHWxbWxsDANdcc027wWCgBoNBslgs4smTJ7mtW7eGTp06tc1nIo2JiZEH6mfz5s0R6enpITU1NfrVq1fXGI1GOlCb66+/vt1sNlOz2SyNGzfOvmvXLtPo0aP9pg5BEMi8efNSysvLDQzD4Pjx4zoAuPHGGzvuv//+lLq6Ou6tt96KuPHGG9s0mr6VcefLjN4bZ5stYfz48e6MjAz33Xff3cW3taSkxJyTk2NlGIbed999jUVFRZ4tW7ZoBjunsLAw5eDBg+UfffRRyCeffBIyd+7ctKVLl57sz39w7dq1lmnTprUBwC9+8YvWefPmpT766KMD1qwfjBm9O4M5Xp999lno1q1bw5955plYAOB5nhw5cqTfoIlp06a1syyLwsJCT0tLiwYAdu3aZZ4xY0Yby7JITk6Wxo4d26uPa3/zpJT2aqjtvh/Z2dnCiBEjnC+++OKgBPWLie9E6qGUthNCPgMwFkA4IYTzai8TAfjUyicBJAE4SQjhoD7aWnvp6yUALwFAUVHRxWEbo94EjiCAzAeFzbNAURQIgtBl2THbMUSboiErMiRlEPcq0QUqSwAT8DJPAFAFOpbC7pQRaRy8sl/HNwF1+6EzpKItdiK0UgdAFUhUUfPGN9pBNQx0Sg2kvIweAqdJY4JbdEPH6dQAocFUDxoE7flD0Z4/tMfyWm0mYpUQWAQZHBWgVTxwsaG99NCVCq4chzXtyHKlIKHiNKKGpMIZB9RwbRhNkgAAZrkdGiqgjYtGtX6Eun+yDSnCYRxVstAhyoiXLLjKFgqdWesNiPKh1k5v5JKwKWzeoDS6RJRAORYKZWBkZRhZGU6JxQmXAVqzCzWGRvzTfABzxSLI4qWf4U2WZRw+fFiv0+mU5uZmLi0trVeTJyEEsiwjJCSkz3rMZrO5V8mcUoqSkpIKs9nc4wINNN+yLAtJkgilFIT0LLzaXz8+n83t27ebZs6cmTF9+nRbcnKy1F+b7g/x7t//9Kc/xURHR4sbNmw4pigKDAZDoW/dzTff3PLKK69YNmzYYHnttddqetvvC015ebmWZVkkJCSclTqLYRh0Dy46E0G3LziOw0033eS46aabHPn5+e433ngjsj9hc8OGDZbm5mbNe++9ZwGApqYmTVlZmS4vL48/l3n0xjfffGMsLCx0AQDLstRn9XK73f4fO6UU77777pGCgoIu49fX1/f5RhHoKxkgKJ71PMvKyoxXX311Y0FBgWfJkiVGWZb950qWZVRWVhrHjh1bG2i1W7p0aePNN9+cNmbMmEELtRcDF+wuTAiJ8mo0QQgxALgaQAWA/wD4mXezuQA2ef//wPsd3vWf0kslOZ4iAVoz1KiR8/67+1FAKYUYkFDcJbpgF+yglHor/wwihkBwQumuQPcG5+gYBVFhxi7Vg7pDZAFE7jx/HkMc2ic+itrkGRBCU1GXexdEY6zfjE7cIuDwgLG7wLh5MHZnl5rmLMPCrPNaZALMvOQc/AvNxxqhbe37HpUvxqFISESu+ytc3rF5UH0a5QaIaEOpvgmjdtVDX9uEODkUD9kvR7KsukHluvdghGsXEoVqmOV2xIrHMcq1E+n8AWggArKCbFcCRjsyvfsYsL+EQlFYgDCDdh2I3HcE5oqTEBWCdLMLOpYiTCMh0+yEmZORKIdhunM4TLIOcj/5Si8V/vCHP8RkZmZ61q5d++28efNSeZ4ngPqS5vMvW7NmTeTo0aMdFotFSUxMFF577bUI3zZffvnlgKrkCRMm2FesWOE3c37xxRf9trnuuuvsH3zwgaWxsZEFgFOnTrGD7efqq692zpgxo2XFihUxA7X597//He5yuUhjYyO7Z8+ekAkTJnQxc9hsNjYuLk70mp0jAy0kCxcubH7xxRdjAKCoqOg793Oqr6/nFixYkHLHHXc0+SKyfwiUlpbqysrK/G/l+/fvNyQmJgr9be9yudimpqYDdXV1ZXV1dWV3331347p16867hm7NmjXhu3btCrvzzjtbASAxMVHYvXu3EQDWr1/v96WcNGmSffXq1TE+QW737t2DM5d0Y+LEiR0bN26MkGUZtbW13FdffRUyUBtFUbB8+fLo06dPa2bOnGnPzc3lhw8f7lqyZIm/3u+SJUviJkyYYM/IyOhyXEeOHOnJyMhwf/LJJ9+p//CF5kKq2OIArCWEqBmbgfWU0i2EkHIA/yCELAewH8Cr3u1fBfAGIeQIVI3mrRdwbt8tiqQ+SKkCiC6oWZ+CDIRXMwJFUWtbB2o27YIdDsEBj+wBS9jOFEL9oUj+0pJdl8tqbXS2f392c0spoo5txMm8u0EJB7PLDo9ggqxQMAF+mYIigoABpQARJMCoATrcYBwdQFwUFE23eAhZAmQR/ne/c5CNIkuOwBMdhlO9lKcscO1AM2PESX0Rjmsz0cQl9NJDT9KUicjp8MDGmvDOgjDUGj34Wv8pHrRNRAhVn0eV+kJwVMB450c4pB+NMLkVGirgg7A7Idu85TUZptOcHbCPhCiQFQ5QKHL4fWjlonFK07+LjP60DR1u4HC8CWkmF0I0MghRg4VEhcCkGDFKMcBGBXS6iJ9fLAaLNJgI8jPpb6BtfD6bvu+TJ0+2LVy4sPmNN94Ysm/fvoqIiAjl3XffdTzyyCNxTz/9dL3BYFAOHTpkGD58eGxISIj83nvvfQsAf//7379dsGBByooVK+IkSSLTp09vHTduXL/Osi+99FLt/PnzkzMzM62yLJMxY8Y4xo8ff6Kv7YuKijyLFy9umDhxYjbDMDQ3N9e1YcOGmsH2s2zZssaioiLr8uXLG/prM3LkSOdVV12VUV9fr33ooYcaUlNTxaqqKr+59P7772+aOXNm2saNGyMmTJjgMBgM/jedpKQkKS0tzTN16tR+U071xwsvvBCzfv16f3zBpk2bjgCd/pG+5UuWLGm444472nzn0Jf66JZbbmlZtmzZgObm80Ffc+q+nd1uZ++9995ku93OsixLU1NT+bVr1x7vq9+1a9dG3nDDDV36ufXWW9t+/vOfD1u5cmVDf3O64oorMn2Cdk5Ojuv999+v6b6N7xi73W4mMzPTvXXr1ipfJPrSpUvrFy5cmLpixQqxsLDQ/6LxxBNP1P/P//xPcnZ2tpVSShITE/mz0fbOnTu3bfv27SGZmZnDhw4d6ikoKHCGh4f3+sD53e9+l/jEE0/EeTweZuTIkc5PP/20yqctffvtt2vmz5+fnJycnOtwONj8/HznJ5980ut8fv/73zdcdtll1t7WXayQi1l5WFRUREtKSr7vaQxM/Tdq2iMAiB4OJA3OX+7HjKIoqKioQFRUFCwWC/bt2weDwYD8/HwAQHlLOXbU7kBGRAZqHbXItmRjXPwAaXPaa9G8/0Mcc+oRavQ+i1ytQGwucOoQoA/vV7OmcZ9G7OE3UJ89D+ENu2Bu2ouTo5ei2SlBr2eQceh58OYkfBl7GZoFBzQV7SBON4yxiVAiQ8GeboeUGgclqlsgY8tRQHCr7hWsBsQtQFN9CkofkfD9oWnvAMuL8MQEjEEpdHIVPjTVYIeRwQ2uLIzjU86oXwoKCQr+EPEJMoUhOKxtBkcZLGu/ust2JtkGnjFABgsFLFoEDUxuGaIcAY5VXxbkZAuIUwDb5AD1ppWSZA1CzM24wbEONdosVBh+0udciCiByAokrQbtkgahnITALFHVDiOcMov4iEYwPEGRDAyf+3to4uMHvb+EkH2U0i4/1NLS0pqCgoLmQXfyA8BoNI50uVz7v+95XCgefPDBeLPZLPfmMzkYHA4HY7Vard98801FZGTkIN5Yg/wYsdlsTFhYmNLY2Mj+5Cc/ydm9e3elL7/p2VBaWqq76aabMlatWlV7yy23fGepxS40paWlQwoKClJ7WzcozSYhJA3ASUopTwi5EkA+gHWU0rN+G/xRIYuqZlNrBtprgISRam3uIH3i8XjQ3t4ORVEQHq6aagMj9Jpdzf4qPBpGMzifTUWCrHSTJwlUzSKl/ZtwqQLREIXaggcBAI7oQrg14XCLgFP2oMXjQbIpHqIuEqIigyEMFIYBp2cAhoC4eEAUwZxqBQ0xgeq7+akrIsCpgte5mNHFcDO6OxSYFRvKNWXYYQzDZZ4UpEoWEKrArNjAEwMEpu+gTo4KMEoHcV90MyZ6UvG/h3ORVNWKf05OwUltz1ReTrbT8pPeUYJSaRJS4AEHNSUFSyk0bgEhlKK7ClehDP4dOrvX8xB4elLe/xJCmBH11xbCou153uMMPJqYDjwbvhsz2/Iw0jWwX2qQHx8bN24MWbRoUeqiRYtOBQXNIP0xZcqUDLvdzoqiSB5++OGGcxE0AaCgoICvra09eL7mdzEwWDP6BgBFhJB0qObuDwC8DeCGCzWxSwrqNaNr9Gpy96p/AVk3qmbFIL3C8zy0Wi08Hg9cLhcYhoEsy37TuktyQc/p4ZE90LG6wQmbVIFMabcAgsH50UYffQfG9irUFC2Fxn0aGk8LbLHj4TnVCqGpCa44DqfTblbnbj8OlhAYIQI6qgqbvACiKGDa26G0hYDGBWb4IKqweY7R6OZjjVA0HFyJXVMNdjChyBMn4bFWPRii+ogaFAeucmzAfsNEHNdl9dmnSbZjgvNrXOHKwygxEbFtbbBU1uH6/IkQQ/tOoq9TXEiTKjGKS8JpKRENRIQHgEIIuFYXQkJUAbddVtBBKWLAAbT3dE8KBQ7azEgyehChldCWlwqH0QjP0XbENzag9bKuSS4MrAzJGY6ZGIcohUD5Efhs9sWlrNUEgKeeeqpHIvTBUlxc7CguLi4LXBZYscdHUlIS70tmfiH5PsZubGxkr7zyyh43gM8++6wqNjY2KIB72bt3b9X3PYeLncEKmwqlVCKETAfwf5TSZwkhl/RN7Lzi02wCgOBSTbeyAPSjUfox4/F4UFdXB0IIKKWoq6uDKIrQaDRQFAUsy0JURHAMB7fkRogmZNA+m5JCu4YIEQKI7oGK8cAdmgaZU30to4/8EzpXAxw/+QMkhUJqc6hpmWLU4BeRStAQFoxCoTAElBAwVAHVaEDszQDtFodAGFW7eg7CpgKK0JJKEKOpi7AZLdainR0CGzekSzSgizHhv8ZJaOVi+u3Xxg3Bx6G/wLUeFjLhYE/Xw54RP2AgD88Ysd80CZSLgtPGQgaQxhKIvAQm1OAvKN9BKURK0QIRZhDEC8dgkU/hoGGsOr7IwimxXcRFW04STnm0aHBrkXT0WI+xCQBCWaRIEeDggUzPLG9nkB8vgRV7fgxjx8bGyt9VRaogP24Gq1oTCSG3QY0W3+JddkGqA1ySyGLnw9kQDvAOVdgM0iuCIKCtrQ16vR6SJMHpdPpzbPoiC0VFhIbRqOUf2UGa0SURCkhXzSZhAGngIFRHdBFaUm8CAJweNh2OqFFgCIEgSJA5BjIoQuv+g2Ff/hq8zIMBUQPCGKJ+FPV/ylBA7G7opgCn69R0n0VKyG+5Vtz1Sx5fTe70S+SogDHObWgmJfi76Rt4Ag3shEGdNg1upmd+YoZK0Cid2l6R0UEm3vdSZnAR45ICVNMUyGCgh4IohQFhGGg5FqwoA4oCSggSORZxHAs7ZHTIBGFyC+LE436B2yZyaOJ1GB7agXCNBMgKXE4FHFGQE+rE6WtGqgMGCOgMAYaFdIDXt8FNeJxTxFWQIEGCBDlnBits3gFgHIA/UUqPEUKGAnjzwk3rEkOWOjWbIbGA1hgUNvtBURTo9XpoNBpIkgSe5/3+mj6hU1ZkEBB4ZA84wg1O2JR5yJR0k5UY9WWgH3mEKGKXlEeCKQGnh80ECIMIjkDLylBkCW69Bc0Rw8FQGWp2Qe9AhACCBMqwACQ1GCgQqqiJ/wO/nyFxcgiGMGF4Ja4cVtcXSBSqYZId2Gn+KY5p42BjPNB2M2RoFB7xwrcgAVphloq4zv53pPMHkMJXYoJjM5hu0dyWfUcQfqjPwFQAgEdhUeMyoENiEQ4KveyrigR0iBKaPCIoUTMO6AAkEB14meArbgy2hd7iF2iTDDwKwhxgCfCt04Byuwn2Ey7Uug3QeKsFhR+sQfzWr0Gkzv1wEgF/DfsSVfpmXHq1OIIECRLk4mJQwialtJxSei+l9O/e78copU9c2KldQlC5U9j0cRbCpmv/N6DCpS+kBia49QmdsbGx/jRIvMDD1eKCgTEgKSQJhJBBBggJUCjpmkuTEAykSjS1lCFj9wPQOuv8y1yyAElRQCUZIkMBSUaNKQmlKdeDsLqupnDirXVOoKZZCvARJbwI4ubR5aeo9AyeGYjY6mbM32PGle4wJIhVKHLtQIpQCRsXiQIxHQsdY1VtawCRciNGuz5FpNToXyYTDQ7rCnBKkwSFsJCIBgrploz+ZDNYl3cf+jD5G1gZGWYnTJwMCgZE9h5jQiAqgE1WUA+g2isg6giDFpGFXVTH8sgMapx6CIr6ckAIoBN4pMutyJBbMIo7HVA6nkAyG8A5OzXUpx3hmNV0BYbxlnNKyhwkSJAgQc6dfn02CSFl6OepRynNP+8zuhRRxK6mR4p+g1LcBw+BaDXQZ2Z2WS7WnYQ2MQFcVNQFmugPg0BhMzS0M5KYUgpZllFXXwdnkxNylIwQfQgUqkAaIJeiW3JD4R2QFIIushNhAMnVb3YAwRiHluTrIRo6g3oqnXUI54yAsxkioTBRDU54mhHCGaAhDLjjrYAkAzoGoBREkgCiClZE5FUhjQKa8m8B+ykIOXGdAyoBpSsHQR1rR2r9cQxrksENn4DtoUWIlBphYyP7bXeKS8Qu841oYf1lnpHKV4CBglYuFq2IRa02o0e7hqtGQDLpkLhlL4RwE5oC6q/7YAlg4rwuD4w3z6a694gAhRmAkyHQB7g1xOtkxHJNyHF+gwPakbCL8YjTdwq1V63fAntGPBquGtFlrPbcnmmcWALEymYYGTcUuHqsPx+0v/9+uNTcfN5yFXNDhkjh06cHM3wECRLkkmMgzeZNAKYC+Mj7me39/AvAuxd2apcQgQFCAADar2ZTrDsJ4VjXwAcqy5AdHZA7OkAphdR8UaX7OyMkSepRcg5Qy9BVVVWh6XQTGJaB4tWWERDIitynBotSiu3Ht2NfW6UalxIoyGn0AKNV69b3gWCKQ0vqVFCm001ZVGQ0Cja0ehwQGRkcYaDx2HFj6VPIbDkIxiMEpDCikOKiQEUbKMsCsgwoMoiHB0QJkCQ1EludLIhHQoDark/+bajCG6avcUTTjEd+6kDbdfEwyTYohKBBEwOR0aGNceG5kC9QpTnd87gQFi1cXJcXoUipEVFSPXSKCwWuz6S9DlMAACAASURBVBEuNfVoJ5n1ACHwDAmFENb1uNlEDqd5DRwiiw5JFeCpRgMl1JszlFFTO+lkigiWQSTb+bswshQKBYjoQjgcyAl1Qsd6jyEhqJ9cAHt6vFprvsfOUGhsTr+mNdXkgWxqgY1xQz4bJ9hBIDU3c5q4OPF8fQYjuLIsW5idnW31fX7zm9/EDtTmXHjrrbfCLvQYPp555pnIiIiIguzsbOvQoUOHP/bYY9EDt+qdqqoqbUZGRs+3oLNky5YtISEhISN8x338+PGZgJrnMzo6Oj/wnDQ3N7Pdt8/OzrZu3LgxBOg8h+np6cOzsrKsjz76aExgVaNANmzYEOprbzQaR6ampuZmZ2dbr7jiivSEhIS8EydO+K+ZOXPmJP/mN7+J9Y2dk5NjHTZs2PDFixfH9bYPgXPqjSVLlsSmp6cPz8zMtGZnZ1s//fRT05QpU9Kys7OtycnJuYF9bdu2zQSoFZE4jhu1cuVKf5Rifn5+dnZ2tjUuLi7Pd36zs7OtVVVV2oSEhDxf/9nZ2dZf/vKXSf2dB981kpOTY01JScmdMGFChm9sAJg5c2ZqQkJCXlZWljU1NTV3+vTpqceOHfPfuH3jZWZmWtPS0obfe++98W63238DLCkp0Y8dOzYzNTU1NykpKfeBBx6I952bZ555JpJhmMKvvvrK7/OUkZExPLCAQJC+6ffmRik9DgCEkMsopZcFrHqEELIbwB8u5OQuGRS5a3UahgMEZ9/bg0DhuwatUEkCRBH80W/BHzkCKooIu+HSzDwlSRJ6K90WEhICRVGgVbRACzqFTUJAQXHKdQrRxmgw3VwWOsQOtHnawIkuhFMD2O5ynK5nkIwfSqF11UMwxgKkU/vJEgaUUjCyArAsAAKZ0aM6NA0dhiGApID6BEYKgCiqNpvTqlo+WVCt9wReLacqJBFBAtvSAcU0cEL3JrYDHiJionMo8vlYJJH3MXNIFMJlPdpZDx5pvxI8ZJioFnFS788UjgrI8JTCpDhQYpqMfaZJ/uVDhUoIRI92rvdnfvPY7B7L2gUObaJ6rZtYCRkhboB2DSoiAVrOrhAcFmLwFW5GLuvw+2SyTg9MJ5vhTByClPe+AG8JQd2NXZO+R31ZCcuBY6i7dhQ6hsYi5EgDjrUfwIHxychyx+FSQafTKd9V9LAoipg9e7YNwHeWdNpXG72xsZHNycnJnT17dlt6evogatFeePqqN75w4cJTvSWV72v7wHNYV1fHzZo1a5jNZmOffvrpHmmcAiPUR48enbVq1arayy+/3AUATz75ZNQ999yTtGnTpmOff/65ce/eveZXX321Ytu2bWbf2Ha7ncnLy7MWFxfb+ptTd7Zv327aunVreFlZWbnBYKANDQ0cz/PEl4Zpy5YtIatXr47p3te6desiCgoKnO+8807kww8/3AwABw4cqARUYa2kpMS0bt26LtWiduzYcTguLm7QrtW+awQANm/eHHLbbbelf/zxx1WjRo3yAMDy5ctP3nHHHW2KouCPf/xj9KRJk7IqKysP+Sr5+Maz2WzMnDlzUmbPnp3y3nv/n733jrOquteHn7XL6Wc60xtlOp0RFDGiQmIDEdQYoyBWUC7YEkw0IdcQX7Fco4lGo1cFYpJrRMWSWDGIBWUAYRiGGRwYYHo/dfe13j/2nDNzZs4U+IFeufN8Pkecvddae+3+3d/yPK/V+v1+cvnll4974oknji5cuNDr8/m4Sy65ZOzatWuT16xZ0wIAKSkp6gMPPJD2zjvvHBrufEdgYrgFQk5CyKzQH4SQmQAGdgWNIBJUR8Sh5gRAi14BLR04ACpLYHIfY1PTwAwd1OeF3tgIo7PrtM3fNAwjqmcTgMm3CXO90Utn3KAGPjryETxK//dip9wJC2+BT/NDpXTAsaNBlNsweudaxDZ9AQBQqY6AoUBjOuy8BUSnYN2n1sk7sD/nUrQ7swAw0LgQDyXt5tEEQIhpbBmaWUTEAICBGN0GGDPbDMezea1/CiaoaThQ+THGbPsGtbYfwk1FdPEyEgwH7ExEKnVjqb8UMSw6zZYOERamwMfHRS4nFrwX82NU2yZH7RcGY4DR4znMdshIsJjXZZZD6dkl9HgoB6R2YsAoq4rRzmCEIpCt1YO0j/eC90tonDMZ7aX9Q/sdU8bgyMKZ8OemIP3dnTgm2xBjPQNTpIzTvha9vb2dz83NHb9nzx4rAMybN2/0Y489lgSYCkI333xzZnFxcdFZZ52V39DQIABARUWF9ZxzzskrKSkpmjZtWsHu3bttgOkZuummmzJnzJiRf9ttt2U++eSTiYsXL84GTK/Vj370o7Hjx48vGj9+fNH777/vBEzv3pVXXpk7ffr0gszMzAlr164Nf5388Y9/TMzPzy8uKCgoXrBgwejBxumN1NRUIzs7Wzl27Jg41LYXLFgw+swzz8zPyckZH9rv3qiqqrJMmzatoLi4uKi4uLgo5AlbsGDB6L/85S/hC3/+/PmjX3755W9VjzojI0N//vnna1988cXk3ulDw8Hdd9/deuTIEetbb73l/o//+I/sJ5544qjVao243GNiYuiECROCVVVVxyVHVl9fLyYkJOh2u50BQFpamp6bmzuk0f+Pf/wj4dFHHz3W1NQk9vYonirMmzfPd+2117Y+9dRT/XLLOI7DmjVrWpKSkrRXX32133mNjY2l69evP/LBBx/ENTc3888991xiaWmpf+HChV4AcLvd9E9/+tPRp556KuzZv+CCCzzV1dX20L02guFjuMbmDQCeIoTUEkIOA3i6e9kIhgNdicwJ5ARAj879px46BBgGaDAIw9NjODFNA7HaQGU5/PKkp6mxOVAYPQRGGQhHoCs9H8NezQtJl6LybXpUDyycBaAG6pSu4TD3hGGITjQULEUg3pSpbVW9qPTXQQcFZzBYwEPkhG4lIgqe4838zL5eO73H2AQ4INDanbfb7dUMefuOo5iFA0Ez78coPwe7X0WQH4Uf+ydjtBaPxf4p0GBAGaoWmxDsccxClW0qLFRGaeAjJOimk0bi3D2UR9G2r2gY98IH4cp02q3yk2ZTURLjh40PvTz7SDb18uT2BmOmtvk52icYrVSElwezkvD1FWfAF2eDlJYAOSWuX1/DboWcHAeiGyCMwUhwQhmXhkTDeVoZmyFd7dDvueeei09MTDQef/zxo0uWLBn95z//Ob6rq0u4++672wBAkiRu6tSpwf3791eeffbZvnvvvTcdAG666aacp59++mhFRUXlI488Urd8+fKwGH1NTY3ts88+q37uuefqem/71ltvzbrrrrua9+3bV/n666/XLFu2LDe07ptvvrFt3bq1eseOHZWPPvpouqIopKyszPboo4+mbd26tbqqqmr/s88+e3SocUI4ePCgRVEUbsaMGdJQfSorK+0ffvjhwe3btx945JFH0mtrayOMnPT0dH3btm3V+/fvr/yf//mfQ3feeWc2ANx8882tL730UiJgGuw7d+50XXXVVQN6cUO64oWFhcWrV68OGyDPPPNMSmj5jBkz8qO1LywsLK6oqIhqoBQXF6uUUtTX1x9X/i/P83j66aePXHvttWPHjBkjX3TRRf0kvZqamvjdu3c7J0+eLB3PnBYsWOBtaGiw5Obmjr/22muz33nnnUHCPya++eYbsa2tTTzvvPOC8+fP71y/fn3CcPbj3HPPzQ/N50RSJ6ZNmxY8ePDggKTVEydODFZWVkZdn5CQQDMyMtSKigpbRUWFberUqREJ3iUlJYosy1xbWxsPmAbsqlWrmv7zP//z9AmXfEsY8uImhHAAxjHGJhFCYmDqqZ82Wp6nHIYOoI8UIsebROLdYNTUUCSEgKkqqCSBWCzQmprAx5ofZEw1i4yYLIGPiwdTFDBFAVxDPgO+dxgojB4CBQUv8gh2BeFKdEG0ihgbOxZdShcM2t/YlDQJAifARSw4pkmR1ehDgAoO+FKmh//mCIFXl8ERAk7RIHAcOF4AmKnXPePQa3DKndiGH/YMEujoUZECAE400yiCXoRsQWLQ7mh7f9Po37ZDEBmHs5Xc8DIVBj6xHcIMJQujzigBUWuQpDUASMf1/lI08348FPdv6ITinq4fIHYAz2YYjMLCJMQZ7RDYwB8x7YoAQoAEiw5qEdBVkg01wQ3GgIN+B1yCgbHeJsjJcQgZmf2YnFj4P30Wm8fHRb3QSU8aFON50Dh3f0aHaLshCuickIvENBHNfBtaDANJ8nF8Xfwvx0Bh9Msvv9z7yiuvxP/85z/P2blzZ9hS5zgON910UwcA3HDDDe0LFy4c5/F4uN27d7uuvPLKsaF2qqqGD9LChQs7BaH/q+Gzzz6LOXjwYDhfze/3852dnRwA/PCHP+yy2+3MbrfrCQkJWl1dnfDee+/FzJs3rzMUIk1JSTGGGuett96KHzdunLu2ttb22GOP1TocDjZUn4suuqjL5XIxl8uln3XWWd5t27Y5p0+fHjYaVFUlN954Y87+/fvtHMfhyJEjVgC45JJL/HfccUdOfX298PLLL8dfcsklnaI4sDPuZIXRo+FEGRNmzpwp5eXlSStWrIhIri4rK3MVFRUVcxzHVq1a1VRaWiq//fbb4nDnFBsbS/ft27f/3XffdX/00UfuJUuWjP31r39dt3LlyvaB+qxfvz5h/vz5nQBw3XXXddx44425v/nNb4bUrD/eMHpfDHXshrueMUaiOTn69r/11lvbH3300bQDBw6M5GoeB4Y0NhljlBCyAsArjDHvtzCn0wu9ZQhD4PgIInG1pgbywYOIuegiQNdB/QEIo0aB+nzhNqybCJxzx4BzOmEosmlsnoYwDGNwY5NR0ydPAapTwApYeEvPuj4I6kHwHA+Bmeo+MlVh4/o/Jw4FW5BrHxVhjFp9R0AFJzS7GZ1TqA6FarByIkhQjfyI0Cnq4/JhDfqBjtBkDYAGzevAGmNWmlNm5ol6WwHJZxaQhVICojwYWzk/PJyMY4IHZ8s5yDLiECQq6gQPkqgT6bobhfIu+Ph4tInpeCz2E5PwgFBMVdLhZgNHfKp9DqRwnbhS+wfet83DhzFXRW2nUQKfzqNVsUDkGGIEHR2qBejO22QMiBF0uAM+ZG3+ErVX/6CXnGUktykxKJg4cPX/566LIv521DbBquvoyB0eC0MwMwn2+nY4a77G++c7UYiioTt9z2EYBqqrq21Wq5W2tbUJY8eOjRryJITAMAy43W59oNxPl8sVNZ7LGENZWVmly+Xqd5H2Dt/yPA9d10m3tGy/toONE8rH+/DDD52LFi3Ku/zyyz3Z2dn6YH36Ggh9//7d736XkpycrG3atOkwpRR2u31aaN1VV13V/vzzzyds2rQp4YUXXqiNtt+nGvv377fwPI+MjIwTMrg4jgPPR95Px2PoDgRBEHDppZf6Lr30Ut/EiROljRs3Jg5mbG7atCmhra1NfO211xIAoKWlRSwvL7dOmDDhlL6odu3a5cjPzx9QJqy8vNwxZ86cpmjrOjs7uYaGBsuECRPkkpISadu2bRHem/3791vi4+P1pKSksBdDFEWsWLGi6YEHHvhWCudOFww3jP4BIeQeQkgWISQh9DulMztdYER55nNCBPURVVToLa1gkgRmGKCqAggCjECPR59pKkANCDEOEEEAA2DIQyvffB8xVBi9d6i8d54TA4saRg9qQQicANbNd6pGqfzUqYEO3Q+tT/+06o1Irnkl/LdCTb5MhWmAYfQUARECaAaOJYzHodhJCHvuqG7+7HEAx4ER0pOfyYmAroI5Y8H5us9lt7FZz3uxwbUTbVwAlwfHY0GwBBWWZgQ40+sYx+yYpKbjvI9akfnWV/jYfTn22s8CA4NCDJQqGfhV5/m4PDi+H79mCPWSFUGDR62WiIexHKqqgRtA9tOrCTgatCPbIWOMU4JXF9CuimCUgVM1cATIkdqR1dCAjilj+hjNBBGeTMrAhL6PHtZTkd8HcfuOIHlP7XHl2jbAiY6MWbiga8wpC6MLSUm61tgonqyfkJR0wt6dBx54ICU/P19ev379oRtvvDFXURQCmPfHiy++GA8AL730UuL06dN9CQkJNDMzU33hhRfiQ22++OIL+2DjA8CsWbO869atC4c5P//880H7XHjhhd4333wzoampiQeA5uZmfrjjzJkzJ7Bw4cL2devWpQzV51//+ldcMBgkTU1N/Pbt292zZs2KqL70eDx8Wlqa1h12Tuxd+b1s2bK2Z599NgUASktLv/UHakNDg3DzzTfnLF26tGWwD+xvG3v27LGWl5eHv1J3795tz8zMHDDksWfPHmswGORbWlr21tfXl9fX15evWLGiacOGDafUTnjnnXdcf/nLX0bddttt/ehZKKVYu3Ztcmtrq7ho0aJ+jjKPx8MtXbo0Z+7cuV2jRo0ybrnllvYdO3a4QxX6fr+f3H777dm/+MUv+hVurVixov3TTz+N6ejoOGnUZ6c7hnugQvmZt/daxgCMObnTOQ3RbZxEgPCmsclYd2hcBtNUGH4/QBnsJeNBJQlU7hVql2UQuQ1oPAZkzQBnsUJvaQXGnPgpYJoG8DwIx8H/xRewl5SA78VrOSy0HQRcyYDt5OXV67qOgcJZsi6jzlcHnvDd6Y49pgQBierZlHUZsaI7nBdJo1DhaMyAQnVUBepR4EyHtZvmqCnvWrBeRo7KdCSKbnCEgGiesMQk4wg4VQMFwKsKeNZNuCNGeR+H5kgEwOIAEwXT2GTMrFBnDHbjCDo5CXYmQgCHJOrEbzt7QvOHhHbk6vFgCRpkiwxKBMhEAAHwi67Z4EAiKZ6iwGCASCgsHEPA4FBADwBqAg5bi/u1TbBosPMG7N15mBaOIdGigS+vR/q+GtRcPRvx1fVIKq9Fy9nFGPO3rTj0k3OhxTq7C4R6QGMd/cbvvT5LrUa6egRfuuYCAGrnToLL4MCOw2w0ktxgOo94iwAmnRqeze+CEzOUsxn6+/zzz/csW7asbePGjUk7d+6sjI+Pp6+++qrv3nvvTXv88ccb7HY7raiosJeUlKS63W7jtddeOwQAf/vb3w7dfPPNOevWrUvTdZ1cfvnlHWedddagIvJ//vOfj910003Z+fn5xYZhkBkzZvhmzpx5dKD2paWl8t133914zjnnFHIcx8aPHx/ctGlT7XDHWbNmTVNpaWnx2rVrGwfrM2XKlMAFF1yQ19DQYLnnnnsac3Nztd50NHfccUfLokWLxr7xxhvxs2bN8tnt9vADICsrSx87dqw8b968Ez6XzzzzTMorr7wSJrXdvHnzN0BPfmRo+erVqxuXLl3aGTqHuq4TnufZj3/84/Y1a9YMGW4+GRhoTn3beb1efuXKldler5fneZ7l5uYq69evH1A2bP369YkXX3xxxDhXX3115zXXXDPmkUceaRxsTueee25+yNAuKioKvv7667WDtX/rrbfiCwsLXbIsc5mZmcpf//rXb0KV6ABw//33Zz700ENpsixzU6ZMCWzZsqUqVIke2h5jjFBKcfHFF3etW7euAQBcLhd7/fXXD65YsSL7jjvuyGlubhbvuOOOxuXLl3f0nYPNZmO33HJLy69+9atBqZpG0APyfVbXKC0tZWVlZd/1NAaHvwWofBuI6ZNP7G0Api4GeBH+bdsgVx6A+4LzEdyxA0Jyill9LkuIvewyyDU1UGsOwaivgmC0AmNmm8VBmorYefNOeGq+jz4Cn5AIx5TJ8LzzDuwlJbDk5h7fIN9sAZLygLhe9xzrk6M6CPx+P7xeL9LTTU1vSil27twZQebeG/W+euxv348UZwrUoIq41Dg4481i1pZgC0pTSjEmrscAN6iBTdWbkGxLgF79Mb5p4zEpMRMJYk+0xKfLUKiGvb6jcPAWFDkzECv2N4gAoMx7CBwIRE6AcKgFRNXBLEL4X7tdwY8aN2IXfzaOuqOEbw0KYlBoheng2vwQGjpBXVZwfgXq+AxwHgk5R8owjX6GPfaZEYYfA4OPKODB4eHYrZgl5+IKfzxKgx/jS+dc+Pn+hTPRQBmgUA48YRAJC5+qOL0FtfoodBl25Dp7nDyywUEgDALHIBsEhwIOOHgD2Q4Zez1uJAa98NkdiNOCGE28oBYBaR9+jfoLp8Fw2uD3JYIQOuglYRg8BFGB3e7DaGU/MtUabHNdAhAOkqFilOhGs+qFzgxYOAF2fuh0qXYugFYawHivHT+66TcQ09OH7BMCIWQnY6y097I9e/bUTpo06XtFcOtwOKYEg8Hd3/U8ThXuuuuudJfLZUTLmRwOfD4fV1xcXPz1119XJiYmRnfrj+D/JDZu3Bj3i1/8ImvLli1V+fn5p2c17knGnj17kiZNmpQbbd2w/faEkPGEkKsIIYtDv5M2w9MZ0cLoAAACGCoYY6CSDCIIUL6pAdW6I2k8D0OSwBiDXLEfTFNBQrmeVANnscDw+0GDJ+61Mbq6wuTxNBAA1U6Azk72RBQ7wdsAHHh72N3r6upw9OhRBLv3YyBy4/CcmQGn6AQhBIQjYa5NwPRsajRyH1Sqmh4xRsMF37TPB9Y3wSY0ql1QqNZNa2TOQVA64ejYH9ZF17rzNfnuQhWiG2GvJ+M4EFWHGiDYL0xD14DqPb3UdCjt4/Izq7S3W+PxesxVqLUURPQMEBWPxH2CA2ILbvSdgWlKOhgIRKZC4obHRMYYcMDnRJXPCcngIgzALiEZCqygjIAyQDYIDAbUBmw4HDALjESOIcGiYZRVBUeAMc4gUlM5FB2twfhtO6DFOKDFOnF00dkwnLbubR5fgc5hazG2uecBhAMxDCTvPgxbhw8cIbBzlqje676wdPqR+GEZtqt7ThGl+wi+73jjjTfc+fn5JTfffHPLiKE5gr647rrruurq6spHDM2Tg2GF0QkhawDMBlAMUz3oIgCfAthwymZ2uoBqiKr4SQigKwiU7QX1esDFxEA9dgxiqplzTDjODBNrGlgwAFgsIEwzw++aBFhFU2e6qQnWEwilU0UBVTWT9lBVwTQd1HsC9V+qH1B6CpnQWgXIwxtHlmX4fD5YLBY0Nzdj9OjR6OrqCufmdcld4DkebksPIblGtYjcvd7GJk/4fhrpki6Z7ZmBzi5iplD2MVY0poNQM9Fepir8howkuOHsqEDqwZdRM30tdN6KJsVjErmHqqJ1CohCaOMgCgUVRHxDi8AsA9xapKfinBi0n4ypaqh4LqUcZyrZuFCKNDZdzIqLA+OQpxqIQRzErgBSXi3DZ7Nnw4gdPqWdSjlwYHDw/c2wZKsKYgsZpS7EiRqyHTJot1XMEyDV1vPsjRF0cKoOS4odhiUtnIvJB2QQxqC77GDDld6MYpTyAQXpZTXwxySAc8fBxovQ9KHtglbDiuaC83Bp+2Ew5+lTjX68OJ29mgDwX//1X/3y6YaLBQsW+BYsWFDee9mmTZti7rvvvszey7KyspQQmfmpxHex7aamJn727NkFfZf/+9//rkpNTR0xwEdw0jDcnM0rAEwCsJsxtpQQkgLg+VM3rdMIRhTORcB8m+sKjK4uGP4AxMxMCAn9c6mNjg7T82lQ8EQHQLuNzRhwVhu0lpYTMjaZLIftHCMQAHQNeke/1JTBQbtVceTudCfFD7TXmBKQw4C327i1WCwIBAIwDANNTU3Quj2shzymSMPUlKnhPjrVwREOjV0SJElFntsOSF1AsAPEGd/PsxnUuj2mmg5NAUQr6VcEZDCGAFORKDpBGSB1S4n6kqZAdaRgl+pFLu9Au+aDrVf4lugU4UJvQsxcTINCVIMw7A7o0W4v0n3curkmI8poGINTDWKdV4MLDeA4B5rFrHBagpUGsa5lC1p5Dvcln4mb24Lg8iyQRw0vfK5SgsMBO9JsChIsWlihJ2J6oWuCAak2BTGCDocwsG+QDyrAF0fQOjYdzsKsMBd99ubtkJNj0ThnCoaj824WLZvtnIYHk6VPUWmbho6YVHy9dDZybKMgUj8cnAVBooCBDZ6TGmuDVRXhtGSASacna8MITj56K/b8X9h2amqq8W0pUo3g/zaGG0aXGGMUgN7NtdmCkeKg4UHqipSq7A1dBmezgnq9piezHxj0pibTKPF7QRQfwFvNULWugFgsEcTvxwOm93gAqd8PIoowOjpNzs/hwlBMz63sAarfB/ZtMivth0gDrqqqgsfjgcfjgcViAcdx0DQNiqIgEAiEjU1CCIJ6MKIISFd84DqPINjVBEnRTM+m4gVaKsApPqh9NOd9qg8c4aArKggHCKKpo24EzZzEFsUDCgq/IcFCBHCEQO32jlLRCSk2DxoYvIYEP5VhCZGch45TRCIiAdEMnM+/g2KtDAwMQdInAhNqT83czR6lINP4jFc7cZYcxNlSDVK0o7A3diD7je0AADs1i2zXx2bjC1sddLcP7lIGLXZ4IXSRMKiUg1/noxqaIQR0DhVeFxy8AZ2RsMZ5NBgOK5rHZqFJjIH9YA+7SOtZRegcnxu+FoaTwtujJM+BMAqu2wPNBAG8KCLdGocE0QULJ8IY4jqNFQ3EujtRY22DOhJIH8EIRjCC7xTD9WyWEULiADwHYCcAP4CvTtmsTicE2wAhCs8hgSlZyQDLAJ5JIlqgNTaBiAKM+n1APAOsDsBbDzgSQWIyYXS0o5vP7rimxXrlZ1K/H4zjAEpBg0HwwyWKN1SAtwCBNsDXDMSkA7wA+FsH7RYIBFBbWwtFUeB2u0EIga7rkGUZsizDZrPBo3ggaRJ0qkOjmsmjqcvQW6tAFA+cQUC2jYGmGd15sQRcWw20uLER2+psPgKbwSB5JRBi5nXqbR7IHZ2wTRyHw1IrDEYRwztACAeOUXTXkSOmeTtkVzZUasCjB7uVJEOuvwEMGMqw334GAnwM/m07hI9tNbjOPxV5em8Vve68zZDkTq9l5RYXdrrOxWguAZTwiKupBUCRG9iHWkcx3oi9AeMMhjs9CtpVguYBNNR1Cvh1AU7BgEAYjklWxIoGimP8Dl6rBwAAIABJREFUoEPkUNp5ilhRh0swUO5xgQCYGNdPnKR72gTJaQIKyqvgz00JL/aP7v7/46g/DIXbg7wbn7rnAYzBdbgJ7vYucGeOgiiYXmULEdCodSLJ4h7Qu8kpGlI/2YktU/3IsZ41/EmMYAQjGMEITjqG5dlkjN3GGOtijD0DYC6AJYyxpad2aqcJgu2AECWszImA4jU5NQfgV+PdbhieLhCBg2DRQZzxgDXW9G4qHtMbSumg5O7ejz6KMCxDYLoOBjNCqzU0hI0eGgj0azsgDFPVCLEZQHwOIFhMlRdm9Hj++kDXdWiaBsMwwl5NQggYYzh69Cji4+MRHx+Pqo4qaFSDwAnQQkVWugKDqiCOJBiEhwAdimqYoXyrC5wWhNFVC6g9RVOdX+2C8/MDCHZJEEVTAcgISKCqhkDQh0DQB51SuLrPEUcINGqAGApSqzbA3bYbFAwSVcH1ul04TxB9LSkmcCCyhiO2QrSJ6ThXHoMfSfnI1eOx21KPY3wPuwoxokg2MobPhcP4R/x+MBAUBr7CxJSdcP2Qx2RtO5L1eoBwiDU6Ma/+Q4x9+WPE7T8W9ThrjENt0A6/zoMQwKOJOBywQzIG92qaxwDIdcrgCDDOFUS+e/AiNGqzoP2MfCijeuiviGHA3tAOwXcc1IV9LpmMf5Yh471dSN1dC76X3CtPOFiIAD2KWlQIHipiz/jZmNNVBBsd2DM7ghGMYAQjOPUYboHQBgDbAGxjjB04tVM6jaCrZvW4IwqvLS8CWgBQVRBbdG5kIorQ29shJLghxDkBobudzQ0Ee/IrmaYBtv4GLQ0GQT1e01sZG8mDyVQtbCtpTU3gExJhdHVFNUwHBDXMMaLJCDIDHsUHv+pHhjsjvFhVVXAcB6czMvQbMkKTkpJAGYViKPBrfsRaY6FSFU44TWMTDGZ5iwCeSdAUDUxXQDgeHMdBba8G2r8BRDvUuGy0B1UgYACJKggx9cSppgGGCKW5HbbWTnSOjQ/PgwMHHQYYZ8GhGb+DAQ402IhOLYBRvQqV+E4JzBp5+zCbCMMmQqQKKDSAc+FsJRcMDG85KnGGkoUsqTu/klIQnUZ87hEG3NXSgKOWeBQEy4BXWqFPoeiMj0XFtmyQyzQU2crQKqQjydqCg9NnIpAdXVXHylHkuQKQDB4GA0pi/NjnccGjCXAJw8/7dw6SrzkYiGYg+80v0XxWMTpGZw/dngC9czsn7X8fskrQeN5ENI1ORFEvzz3fXZU+GG0bL3KwxwrgEjPBy6cmZ/PAFw1xQa960kidHTEWvfCs9G+du3MEIxjBCE41hpuz+RKANAB/IITUEEI2EUJWnbppnSZQ/RiwOILwgK6BKgrAD+x5seYXgHf0yfnsVp4BNb2TiEIXxHQd/m2fwujsiEqPxGQJhOchJCVBSEwCZzXDsfKBKkj7Kvq1jwpmDFz7QQ20BFtQ3laOfW37wotVNTqLhGEYYeNBNVQQQpAdkw2+0we5sQEB2QPaXgO9m9qbcjwsugTKAENVAMLDKjjQ5W8CbakEmivQ0dUMaBQaA4hk0jMRQkAVDeAJqGHAIQNZfC+PHCGgjMEAg26Nh9bNx5kgOk0ieQCgDETWwAY4b2Pkf+OhuM9QLpo5jAQEK71nY440rmc7lAGKDtbLYwdKkaIDYw0rOrgU6EWx2JnzQ3TEpsObm4Y4ox1jlX1oE9LwVvz1aJla3EsSstdpYcABrwNtiog6yYZKr0lzVBLrR4r122HxoFYRxy6dDu/YtKEbA0Af6netHmAqg7cgE4TnQXp90CSJbsQKdhiDxOgdAkWcsws1tiZI5ISFeQZF0KsKrnibdrJ+wzFceZ6fVlhYWJyXl1dy0UUXjfH5fFGf4eeee+64tra243Lphvq0tbXxDz300JDaoG+//bbb7XZPLiwsLA79Quorpwp33HFH+qneRgiLFi3KzcjImFBYWFhcUFBQvHnz5hPe7pNPPpm4ePHiob+6hom77rorPTk5eWLouN92220ZADB9+vSC3Nzc8aHlF1544Zho7QsLC4vb2tr40DksKioqzs3NHV9aWlrwt7/9bUCFjtWrV6eG+oeuxcLCwuK1a9cmT548uTCk6KbrOgoLC4s/+OADZ+9t5+Xllbz88suxg80p2nZ9Ph83f/780fn5+cV5eXkl06ZNK6iurraE+iUlJU3qPZYsywQANmzYEEcImbZ7924bAHz11Vf2UJvY2NjJofM7c+bM/KqqKovNZpvaez5//OMfB+KwA9BzjRQUFBTn5uaOv/zyy3MPHz4cfmFnZGRMyM/PL87Pzy8eO3ZsycqVK9MlSSIAENpeUVFR8ZgxY0omTJhQ9Ic//CFiexs3bozLz88vHj16dEleXl5JSA0stO3k5OSJofEaGxuFjIyMCYPN97vEsL7KGWNbCCFbAZwB4DwAywCUAHjiFM7t+w81gAGT1ggHpskmyfcgMmXEkICOGtOwi1gBwFBAQKIW9VBZhtbYaMpaen0Q0yJf+lSSTPUgng8bu4TnwRQZUnk5bPl5IJYhiLOpEVXLGzCphlqCLfAEPPAoHuTF58HKW6EoStT8UpfLFVYNUmmPQeRsC6CrrRrNQjsyuupgcCJERsCIAMEIAkyHoSgQnDZwvAhqj0PA34RO2YlaTxWgGdAIZ+qQu2JMSXVNRYA54On0gzMM8BoF7bWrBIC9sxJ2pROtyTMAAli4HoOfaLpZec5Ft7RrrPmYoDYj1eh5N8XRPt5rVTc1wvmeAiGqqHg2pgBjuBTE2mxomZUTbt48ewKaAVSxUog+CfamTvhyU6JSLDEANiiwwcBop4EjARvaFAtynLLpPh0mNEOHyPMYTjV5PxCCYGYSqMEBw8zM6D2z/XN/CNEbROZbX6Jh2hhgTI93nCMcrLwIpg2+L6kffY29uV3oSps6aLvvE6xWKw1VD8+fP3/0Y489Nuo3v/lNmNCcUgrGGLZu3TpsXey+faqqqiz//d//nXzvvfcOnnyNk6PBPVzouo7f//73J0x1dCJYu3Zt3dKlSzvfeust94oVK3Iuu+yyfUP3+nawbNmy5mhk9hs2bDj0gx/8oJ+HYaD2vc/h559/br/yyivHORyO2ssuu8zXt+26deua1q1b1wSYggG9K9m3b9/u+v3vf5901113tT344IPJkydPDsydOzfwr3/9Kza07V27dtkuuOCCgquvvnrPYHPqiwcffDA5OTlZe/PNNw8DpjxmVlaWFtr+QOT+f//73xOmTp3q37hxY8KUKVMapk+fLoX6LFq0KPfSSy/1hBSUqqqqLFlZWcrxVueHrhFKKX77298mn3feeQUHDhyoCKkWbd26tTotLU33eDzctddem/PTn/4057XXXqsFTGqrysrK/YCpw75w4cJxlFKsWrWq/YsvvrDfd999me+//351YWGheuDAAcvcuXPzx40bp5xzzjlBAOB5nj355JNJq1evHvJe/a4xLM8mIeQjAJ8B+DGAKgBnMMYKT+XETgso3oHLcDkOTJWHrp/QJFOFiO9TCMJg6mqDRfdsymalu5iSCuXgwYjqcwCg7XUgfZPkeB5MkkB9XqgNw3imD0iuzcAMHa3BVrQ2tqK1sxXNfvMZEAwGwUfxCDocjrCxqVM97OUUDQJJ9kMJdkC1OMAIB8ZYD3ejrkFXdDOUTziAt6Ix2Iqmdi/aO9rBDAqOarBQBeBFiBI1i5EMCikod3uY++9HTMsOJNS+BT0KxQ7RKQYzwHR+NC6Uz8Qo2pMqUCt04EtrjyIfp/T1thG0ax68llCFWqEDlnZv/7xXavJyOurakLZlDwQ5upeSI4CbkyAyFbGijqKYANLsxx9K9hgSpAFFCYaGtc0LZ91wBXf6a6MLfgnO+nbwUc6PgMGNYMngUDb+B5ikjkeSPqTs9/cSs2bN8n/zzTfWqqoqy5gxY0quvfba7JKSkuKamhpLRkbGhMbGRgEAfvOb36Tk5eWV5OXllTzwwAPJgPliHajP3XffnXns2DFrYWFh8a233pq5YMGC0X/5y1/C/Frz588fHfJORcPWrVsd+fn5xcFgkHi9Xm7cuHElO3bssL399tvu0tLSgrlz544dO3ZsyTXXXJMdEnF47bXXYiZPnlxYXFxcdNFFF43xeDwcYHqG7rnnnrRp06YVvPDCC/GLFi3KDXl3tm3b5jjjjDMKSkpKimbNmpV35MgRETC9e8uXL8+YMGFCUW5u7vh3333XBZjG6i233JIZ8jT97ne/Sx5snN644IIL/C0tLeHlg237hhtuyJoyZUphXl5eyccff9wv9PDXv/41duLEiYVFRUXFM2fOzD927JhgGAZycnLGNzQ0CIAZ6cnOzh4fOoffFmbOnCn97Gc/a/jjH/+YPHTrSDz11FPHHn/88dSysjLb888/n/zEE0/U9W0zdepUmed5NDU1Hdd+NTY2ihkZGeGH0aRJkxS73T7o69Pj8XBlZWWuF198sfb111+PH6ztyQDHcVizZk1LUlKS9uqrr/a7P2JjY+n69euPfPDBB3HNzc39XoLFxcXqww8/fOyZZ55JAYB169al3nXXXY2FhYUqABQWFqp33XVX08MPPxyuxLz11ltb/vSnP6VoJyLI8i1juGH0vQBUAOMBTAQwnhByej7BTyYUr1mtHQ2EBzRlaKeR4gdsMeYvyvgEGNCzyRjAORwwfD5I5RHcxWB15SBqJG0SEQRQWYYwKhnSrl1Qjx41ZTEHQl9va89ICGp+KLoCu26Hw+/AvhrTISBJEgRBQEALIKBFd3mFidlVHZxuek8NXxeCjMLW5AXfGEprYyBEgxRk4bzReNGJXbofDUoHuowOMHAQOAM8BbhWLywHmwHNALVbgIAEiQFGLx7G+EADzq7/CAdy5+GVsVeiXmlHP++0ZvRf1g0/UeAhHjiNSM7SA2IrqsU2MDAwnoBEKZwZLSn467EAZrVIGP2PTxF7oOdZnfGvMmS+vQMA4M3PwOGrzoHm7n8LqpTAp/GglMKgDGCm6o9liKKgaBDI8emR90XC1zVI/XTvsNuHPiBch5swbssnmGH7GFXXz0Ewo38ky8IJg85NIAxuFwEdnQ6RnX4FQpqm4b333ouZMGGCBAC1tbW2pUuXtldWVu7vrXiybds2x1//+tfEnTt3VpaVlVVu2LBh1GeffWYfrM9jjz1WF/LwPPvss3U333xz60svvZQIAO3t7fzOnTtdV111lQfo0doO/SoqKqznnntu8MILL+y64447Mm6//fbMK6+8sv2MM86QAaC8vNz5xBNPHKuqqqqora21btiwIb6xsVF48MEH0z755JPq/fv3V06dOjX429/+NvxCtdlsdOfOnVW33HJLWHtbURSycuXK7M2bN9dUVFRULlmypO2ee+4Ju791XSfl5eWV69atO/bAAw+kd+/XqCNHjlgrKir2V1dX77/pppvahxonhE2bNsXOmTOnazjbDgaD3O7duw88+eSTR2655ZbRfceaO3eu/+uvvz5QWVm5/4orruh44IEHUnmexxVXXNH+/PPPJwDA5s2bY4qKiqS0tLQBc0CeeeaZlNBx37RpU/gFsXjx4jGh5bfeemtmtPYzZszIH2jc6dOnB2tqaoZHltwLOTk52rJly1pmz55ddM899zSmpKT0e0Fs2bLFyXEcC+3XcOd0yy23tP3hD39InTx5cuHKlSvTy8vLo9Nw9MLLL78cN3v2bM/EiROVuLg449NPP42uQdwLoY+s0C/0oXI8mDhxYrCysjLq8UtISKAZGRlqRUVF1PUzZ84MHj582AYA1dXVthkzZkR4qM8888zAwYMHww/+nJwc9YwzzvA//fTTg4b7/zdguGH0OwGAEOICsBTAiwBSAQx5wv9PQ1dNozIaCAca9IMgSvEQYIaoOR5QPNENVpsbaDsI5iru59n0ffIJOIslHK7m4+Oh1dfDyMsDEQRwAgfq9wAxORH9CM+DSjKElFQYHe3wf/Y53OfNBtetatR/jgN4NgngVTwwdAMiE0EoQX1TPXyyD5IkweFwYF/rPvg1P6alTINTjCwWUgwFHOHAN7aC8wbB2QDLkTb4MgHeq4CnBuC0maVCVIKiAobOwPGA5AVkJQ4SFMhSJ5ymOQ4oBgSfB9Rphe4koAYQjHeCqkFYZQ2hszS2dSdyO/Zhk+KDT7CDqlEMYm0Aon4AuywN+MBxEFuP1OEz92IY3bycRWoypjDBTHuwiOA9QVBX5O3DqRSjDDvaLU40XDAJUmrPteHPHmV6NY+1IuPdnTj8k3Ojes39Oo+jQTtSiAQODJQycPwJhMEBCIQftAhnKLSdkQ+mH8e2uzcl+CSQRgW+6fFgFhKWB+0NkfAQCQ/KGLgox0HkGBKdPhzgWjBGHx4P6fcBiqJwhYWFxQAwY8YM36pVq9qOHDkipqWlqRdccEG/i/Xf//636+KLL+6KiYmhAHDJJZd0fvzxx+4rr7yya6A+fXHJJZf477jjjpz6+nrh5Zdfjr/kkks6Q1GIgcLoDz/8cOOkSZOKrFYrffHFF8Mu/QkTJgSKi4tVALjqqqs6tm3b5rLZbLSmpsY2ffr0QgDQNI1MmzYtzLW1ePHizr7j792713rw4EH7+eefnw+YqQCjRo0Ku3euvPLKTgCYOXNm4Gc/+5kFALZs2RKzbNmy1tDcU1JSjB07dtgGG+f+++/P/NWvfpXZ0dEhbN26tXI4277mmms6AOCiiy7y+/1+rm8e4uHDhy0LFizIbG1tFVVV5bKyshQAWL58edv8+fPH/frXv2554YUXkq6//vpBwwInK4zeF/8v9/y9997bsnbt2oyVK1e2917+zDPPpLzyyiuJTqfT2LBhwyGuO3VsuHOaOXOmdPjw4fI33ngj5oMPPoiZOXNm0datWw9MnTp1QLqLV155JWHVqlUtALBo0aKOjRs3JsyaNWtQao0TCaP3xVDHb7D1vdcxxgjXJ8UuWt81a9Y0XnbZZeOuuOKKEyPd/pYw3Gr0FQDOATANwBEAL8CsTh/BYDDUAWmNQDgYvgBAo3j3GQUadgEZ08wwOhfFYOVEAMzUV+9jbBpdXaCCANJd9ENEEXpHO7xvvw1rXh4cBdmgAR/4vvl7hIApMgjPg09MgtZQHzVE37MhLXqaAANagy3gDM4kXTcADRre3fUuMrgMGJoBv+qHyIuo89WhICFSLU01VPAcD6KoMGKsIN4OCLKCoK7BqhtgGsBRAIQH0Uz+TK/HAGOAIlNAF+DTfYhpakEMXGCEglMNABzAE2iagRa9EzpjyOcPQfKlI6DEgXEcynLnYVfydIyu/xC2pKk4xBuI4SM9iJyi9cq1jMR4LQUpPh01trERMo05hnmedVAIPAfqtoIJvc8rw1a7D3uFKRjDpQB5keN6SswPA8EnmUZnfTu8BT3Kdo2SBSrlkO2QoVslkO58Rp0BQ2TeDggOpJ/v0BvUYLcIEIWhjUgt1glq8MPO2bT4A4g7egSeomx0TcgFCIFOdQhRDHtCCJy8FX5DhjWKaEJAlxH7ZQVibC1omDh+eBP4HqB3zmZvOByOqF9+g73YBuoTDVdddVX7888/n7Bp06aEF154oXao9i0tLXwwGOR0XSfBYJALGbt987VDtGezZs3yvvXWW4ejjeV2u/vNkzFGxo0bJ3399ddR2VFC+XKCIMAwDNLdB4REPvSGGmft2rV1ixcv7vzd736XfP3114+uqKioHKpPtH3sjRUrVmSvWrWq6ac//ann7bffdoc8r+PGjdOSkpL0N9980717927nG2+8cSja+KcaO3bscIwbN+44OMt6wPN81Jz84RqVgyE2NpYuWbKka8mSJV2LFy/G5s2bYwcyNpuamvjt27fHVFdX21esWAHDMAghhP3pT3+q62vAnWyUl5c75syZ0xRtXWdnJ9fQ0GCZMGGC3NHR0e/F/sUXXzjGjBkjAUB+fr70xRdfOGbMmCGF1n/11VeOSZMmRTxRx48frxQXFwfXr19/ylMF/l8w3KNuB/BfAAoZYxcwxv6TMbblFM7r9IChDeLZJDA8ARBLnxcl1QCpE9CCZn9NNlV5BoIaBLrqw38yxsCCQVMVyG4aSUSXwVoPw6ivhrKvDNTfCSgyCI0MkXN2Oyw5uWYfjjON1La2gbk3qRad9ogARzvqwXwMFrsFNpcNzMLQ3NKMZn8z9rbthUN0wCk60SK1REhMMsYg6zI4cCCyCmbIMHgVRKOweVTYIYACEIxuz6+hQBQBn9dAMGBA0xgE8ODAkGBYTR1zQgGNmcT1AGyciIAhQ6EaZmEXzlY/Bn+0A0KTGZ6PpRomtu+Bywgi1RIHZ1+eVNUA+Mj9NkAhQ0M8taNAz0O9ZSxon3O/3XoU/xn/IVToYKIAEIJ9YhM6uCAAgg+dh7DX0QJbS5dpVPaB4JeQ8PUhNJ9TgmCa6fUM6hwaJQsYCHjCQAgQb+lF2D9gXu3gYDCFAvq+N3TKoA72AdJ7vj4J7m/qwQ0znyh9724k7K4BMYyIj5honk0AsPMW0AFC6RLV8XXB2Rhln4LR8vDkPI8XjhiL7u+UxZP1c8RYTnrZ/Pnnn+//5z//Gefz+Tiv18v985//jD/vvPP6FX70RmxsrBEIBCIO+rJly9qeffbZFAAoLS0d0hC5/vrrc++7776GK664on3FihXhr6Ly8nLngQMHLIZh4NVXX00455xzfLNnzw6UlZW59u3bZwXMyuO9e/cOGjWbOHGi3NHRIXz44YdOwAxtl5WVDRr6nTNnjveZZ54ZFcpva25u5oczDs/zuP/++1sopWTTpk0xQ/X529/+Fg8A7733nsvtdhuJiYkRN4zP5+Ozs7M1AAilJ4Rwww03tN50002j58+f3yEI32q6JgDgyy+/tD/yyCPpt99+e8u3vvFB8P777ztbW1t5AJBlmVRXV9tyc3MHzPHauHFj/MKFC9sbGhrK6+vry5uamvZmZmaq77///nGHxYcLSinWrl2b3NraKi5atMjbd73H4+GWLl2aM3fu3K5Ro0b1e4hWVVVZ7r333sxbb721BQBWr17d9Pjjj6dVVVVZQuuffvrplF/+8pf9DNk1a9Y0PvXUUwOEIP93YLhh9EcIIbMAXAfgRULIKAAuxljUL9ERdENXohtj3TACMkhMt0HibwZEO3DsK/NFa2imZ5TqAxuszOxH63YDecWALQZMlsE8raD+DghFEwFYTAomfwsEGwfmF6DXHTIJ2I3+RSNcL/5LwvFQ6+pheDxw/eAH4eUhvXGbboa7+8KvaGjo6ILTkgKL0wznG4oBjWroUrpA7ATWXqpKPtWHBJtpPLXL7WiVWuEWXSCKBsYUEI5Cd/BwBSiYKIApKgRNhyxawQwNxCLAYuVgaAyCAFisHNJUEeAYaGIs0OUBJ+vQu2mCrLwIDhxUxrCZnA+eOcGpOpK4RqTXfo6q1LNQnXIm2lyZUb/SiaKDCeZ+b7MexvuOg4g1bEigdhAQ3OibAhf1QCJOaFzPfo7REpCnRabW/MtRhUlKOi5ENp4+7EKi9SA6Pu6EEuvE7tlngQBIsfU8U+MrjqA5oSS8L/WSFQFDwKRYX4991sv+MuiJhcQYY+BAYPTxjBkMMIzhjWlv7kT6x1+j85Js6LZBQtmMgTCGw2fOQpy1AdRmgdPw4KzAe9htPQNd1ugKWxYigA7gueNAYLepMMakwKr2N9xPBr4PnJizZs0KXnPNNe1Tp04tAoDrrruu9eyzz5ZCL7BoSE1NNaZNm+bPy8srOf/88z3PPvtsXVZWlj527Fh53rx5EfscytkM/b169erGQCDACYLAli1b1qHrOqZOnVr45ptvujmOw+TJk/1333135oEDB+wzZszwXXfddV08z+PZZ5+tvfrqq8eoqkoAYM2aNfUTJ04csKrNZrOxv//97zUrV67M9vl8vGEYZPny5c2DGcJ33nlna3V1tbWwsLBEEAS2ZMmS1l/+8petwxmH4zisXr264dFHH01dtGiRd7A+8fHxxpQpUwr9fj//5z//ud878r777mv4yU9+MjYlJUUtLS0NHD16NPyQ+MlPfuJZsWIFf8stt7T37TdcLF68eIzNZqMAkJCQoH/++efVQE8oO9Ru8+bN3wDmOSwqKiqWJIlLTEzUHnnkkaPRKtFPBaLNqaCgoJ8RWV1dbVuxYkUOAFBKyZw5czxLlizpl14Rwj/+8Y/En//85429l1122WWdGzduTLjwwgsHkEPrydkM/X3ttde23X///YMa3vfff3/mQw89lCbLMjdlypTAli1bqkKedQA499xz8xljhFKKiy++uGvdunXh6ttjx45Zi4qKihVFIU6nk956660tq1atagfM1IEHHnigbt68eeNUVeXq6+st77zzTtWkSZP63RelpaVySUlJsKKiYsi81O8KZDj5GYSQNQBKARQwxvIJIekA/sEYO/tUT3AwlJaWsrKysu9yCoNjz/+Y6kFC9Oe6592PgLHngCMa0LAHSBwDtB4EQE2PZvaZQOPe6KTwACB3QQ8w2LPcsOWkAHk/hOEPwPPCo+DsVvA5E4HEcaYhW7cD0CXougtikhtaYwuE9BxgVAFgif6xp3d0gDAGWETQH52DGN0Cee9eHC2IA0941B36CNNhhdudHu4jqToqa2qwXZERl5ANi8Pc9065MxzSswk2OETznvCrfiTbRmG0mAQuWI96PYCDNIhEWGHZWQHKBUF1BTqjsMIJ5rDA2x6AarfClxaLGBJErN0C2COL//jaOvCyHTQxGeisNfNeexmOrV4ZPPNCpU64eR4xuoG0uGaUSF/hn+NvBxvIwKcMln11oE5zvK8sx/Ceoxoz5RwkUSd0UMyWHLjAtwk7HOeh3hIpnxkkKj6xHcYsORdeToFMNBhg+Mp6DAt9AmZJbagITIFBCA45k+HXeRS4g2GWJVtTJ9R4F6hVhFfj0SBZke2Q4ehFvq7pDJ1BFTwhsAgEbnv/MPNQUAzNlPZkBhxDDHohAAAgAElEQVS9PgxavQp4jiDBNXRwnlM0EB9FF58O3jKwh1UMBFHy+hs4fOYsaBPdJtUUlTFB+gLVQj5kWzYyrP3vAYVqqJGa4ejL1ACgSwtAg4FaWxdyfA4svf7/g5ie3q/dQCCE7GSMlfZetmfPntpJkyYNt7z+tILP5+OKi4uLv/7668q+nrrh4u2333Y/9thjKd8WVdJ3genTpxc8+uijx6LlTA4Hn3zyiePOO+/M2rlzZ9XJntsIvt+47bbbMnbu3OncunXrwd7G7P8m7NmzJ2nSpEm50dYN109/OYApAHYBAGOsgRDyrRDrfq9haIBl4A8NqurgeQIE/WY4PNBuKgtZuxWCdGnwanXeChgeUIkAXgNoPQDqVQDRCj7GDcgeoHkfIDpNQysmA7y3FdrhGjBXChBoBWQvMHY2om2I8DyozwfoOsoavsIZRgbY3i/hjS9B0CnAp/lAxcgXfUDW0BqgADSwXl61eJuZTuLftQvW/Hyg2/4RORFSRyOkym1w5KcjSDTY3aPA1R000wmcVnCCBRZDA7OZBo5uEWDzSwiqLjCR9q+KpxR8hwKaFGPygDIWYWhSnSKOdWI2tkPhrNjNTcF4Uo09/LmoHT890hutG0Dv3EqjuxK9e7zpahamq1kRmw9yGr5ynI8OIQV90cz78ZntCHZa6kEJwy+7zkOF2Ix2PgiPMBHb7RPRxolItanIIv0dO3KqeRwZM8+YwDF4NAGHAiIK3EGIHAvToxNieiJPBBJV4eStkTSqjIGBwRhCWz0EahWhcxYwiUc/Lcrew3IEzSXFCMbFQ4R5fFXOhp3O86AYGmIGyPbhCRcxP68WBEc487gQHonlR2BvO4J9FwxY5DqCYeCNN95wL1++PHf58uXNJ2pojmBo/PKXv0x96aWXRr344osjEcMR9MPTTz9dP3Sr/70YrrGpMsZYKLmaEHL6lHeeSgyU0wiYRT3UMEswdMk0mFR/pBdUDQ7ICQ8AEKyAHgQMEYjLBjx1YK1+EE4AbHGmMUk4wB5vGpy8FcTmBEmKA2ezAhbRNGoNtT+PJwBwHKgkweAZgrWH4W08BEfjIfi7kuHl7fBrAehiUkSXzoACl8sCi9QEi9EGIJJFJIHZYXQGYDidgNwFwRoDOdAFvcsH3RNA0C6DdyaCdHh6DETRbv66YQBghIBjFGAawCKPMVG7lY2oEcEFWiE24yK/Bza1HcWsArv4yehgcYilXUjjjmGfpkHvY2iKNS3QR48CEzgIRztgpMQgZJi/4ahAJydhiX8auF7GukFENFiih35H6wlY6TkbOjFQz3tRK3RirJ6IAu8oWCHA06HCR0TE8BwE3qQsChg8XIJZAHXQ70CyVYXOCJplCwrcATTINiRatB7N824LjACgJxBG16gOB2eFi7fBw4Jm/iYIzKEIGKP9DPhoILqBnH99hrqiaZDSozNzMFAoNisap0yGbogQWGt42BTtKKghIyCURO3L9flA4gkHgfCQqIoYwYF9WZMxypaGSYHTj/ro28SCBQt8CxYsKB+65eC49NJLfZdeeum3Ep79rvDVV1+dsEfywQcfbHrwwQcj8vFWr16dunnz5gi3/mWXXdYRIlY/lfgutr1p06aY++67L7P3sqysLOWDDz6oOVXbHMG3g+Eam68QQp4FEEfI/8/emYdZUd3p/3NquXvvG03T0EB303SzNpsiRsUlEhWJiHsw5mdMnBCjaMY8ZvNxDGMSnbgk4zhjZKJxGScmqMSNqEGJwQAKyC47TTf0fvvut5bz+6Pu7X3BhSRm+n2e+zTUrTp16lTdqre+5/t9X/FV4CvAoyevW/8ASBOdgcimYYLQoPUAnVEfy+wiVYKUA9EgEArCTmKrOcSPx/B427DboqDpzn5dASc6aMa6ioy8Oai95RnN/smm0HXsRBzDp5FsbyV6oIWAbhNrb+a410XAsjDjCUjFuGNJk7ZQHN2lIzoiiESkZ2RQOgL0SiiKZVsQPo7qziIRDoOmYIYhrkUJ7PoQtTniTFX3N3bSqfMWEizhAq1n9FgkUyLvVtI5D0BMGDwT2MI+Nc7Vbfm02bPZq0zAlgLblhjeQmy7J3lRglGUUBz1SCt2YQZKOA5ujfQbQIWRzzOBLTQqYUbYPQP9PiuEW8Zo0/pqI6fF3mPC4L8Dm/hmx2kU2l4+3/Fr/rxvGtJdTGN5CVFLpdQXZ3/Ex3h/FK9qE7VUkrbAo9pk6CaqgNG+nmlqkq4CH/NjhDZNaVOkZ5LryiBmG1i2jaaondFUUsRzAAOlHvA3NJPr28/RAchmzDYgmcDXTyrH5NifCdgh/uDtv5pcEUpK9igVyxWCfD2DY8l2Sj251PmCMDYHd/JjzWgOYxh/c3R37Pm/sO/Fixd3LF68+BNJDw3j7xMnWiB0rxDiXKADmAD8QEq55qT27LMOe/DCUmlaDrFMdDhEUKgguxUDKboTtexViZ5saEbNCqD6UsWP2WMwIwmMliNos6qw2tcj3KnqW92LozEZAv8gVsf2AE40Hg+eSTXs2fFHdAkNepioEYZgOxPHVNFxYCuxSBzOc3SLQzHH09xSFPDkoh5vRjSpWONLHVklVQEbRCSGtn0vZn4SEY3iau7A9rgww1FsJY7W2I6dFUgVR/Ui67LLQ1uxbJJ6Brh7see44VSqmwmwkjSqUXJkFlMTxWzwNjAyNoKx5ihUIRBCYtkQ0nJR4l1V00okgXa0DakIlFgSOuKISALFtLFTeag1RhHfbZuPp5+f0eTYegJ2O69nLhlw2MsjmVzRPIrcbC8qJvX6ONyTMiiKavh8CWKWgl+zKPHGCWgOaZ6cFcK0BaqATH2g+oku8iWRacmXAfvRHUnLQCI7K/DdQiNixwGVriCpdMjmEG1JTWXH0guJGnlo9F+RriAo37SVzMYWti681Ol3isy/7D6LBArTjP1IvQp/so4OT09NKA0FW4IQEg2FDM1Dh+VGQyXfHWeLu4FR4Y+sTz2MYQxjGMP4FHHC2gopcrkGQAihCiGullI+edJ69lmHbTFYwqWdMBwdRivpRDShJ0HVfRA+5kyBpyAtm8bHnkcvzKXoq18EQHHrmO0h7FiC8OYPEVoRQlN6tqP3zRvtWLeZxKF68i+egzAHdglKWgahZJgCimkxPsTGQGtugLoQ7qPNWO7iTjLTFk7g1lVCMuHQBcNC2BG0PYcQpkWyZjyoAkwTNRzFdttgB1EjUYzsTFRTogdjSExQNefTC105esLxFu8ncKdEE460kB0jFq3noYKNnBMr55LoJBbEJmDFBGan3J5DbqQz5wyWDaqCaI86UkleDRkMc9AfZpTfg5Yi+R0izlZXA5OTxXhk337u8kzvdzxNG/ZFfOTqBqc8+zrF+ZnUnycxNRdbfXOd6KEfXEhcikMwC9xG57HHLJV9YYdcT8kKDziTLbr9tW3oxyG0DwzbJGIn8CseXCkxel1RsVPR0a6hFv2Oe39wByNUvryGQ/NOJdRvgY6gbXQpkXznZSgdPbWlxNSyKbSamBR+BSP6FrodZVfe9cT1rhcnTVGxpI1AoCsqLkWnzFOAEILcfcf53PbtvHbR6BPr7DCGMYxhDOOkYFCyKYTIBL6Bk3j3Ag7Z/AbwbWAzMEw2B8IQkU0rFHG0Gm0TSOUYdid9igquDKeaHeh4+31iuw+Rd/l5JOsaCb65kayzZiJ0Db0gBzuWINnUiupyoRUOre2qeN2omQGsuAmH96LVFKdyTNXOaKJpGxwN1aF4PejRBPluPyEZQW1pBvJRTIntEdjROEZrkNaDLWSPLcYIJ/Dvb0G4dUSoEXwFoGideotKLIG0DIibKEYHSa9GQtjoto2WUJCBgXUR03FNQ7EJ2SGE6QLp6ZE/KGJJRzBdCaBicWl4MsVWBsXGEVRpsoOeBT2O5afzL5E0kV6XMxWvKki3Rl2OyS+z34Ns+H7bfFxoNKoRXvV9yBgzhyyrb+QsqOX3WQagKZCjG8QshfqzpznRR03FbUdJJjV2hjPI1ExKsnvWYbQnNY7G3BhSAIJSb2xAotmdCErAlnAiWYtSgkdxkaP7OiOhGkonyZSyS9XS0e8culXT46GtdDSmZ+DoYkdpKZa0HaH+FE02bJNszU+Or4hd7mwMvRCf0UC817iqQiFoRvEr7k5x93Tft+eU4ZpWyGntJ6gqP4xhDGMYwzgpGCqy+QTQBvwZuB6HZLqAi6WUm09y3z7bsM1BK8mN5nYUtxtk0nnK636we+nAdvNDt2NxEAJveSnxfXUYDU09VlW8blwj8sGyEQM4JEjTwk4aqD4PgRkTkbVVNPzsSTxji8itnAkNm51K+CInR66+4zD1h97C8hYggjZCtZEuLyIURG80sDQPZtKg4y/bsbMzMIIRFCEwg2H09hgiW4dEAtymkw4QiYOZxMzWUOJulEgMJdmMqkuiloE3gTOVnTkIiUmxnTcLDvJ+VgNLjteiWCOxixyCqkQSiISFdOtIJC40phrFAIxLrON9d5J3MkzmtpRS/fp7xLID7Jk1obNWWiRMpEdHJAza9SR+FApkgDNaRtKSYWMIm+NKO1tdDdzafjoB2b/2tJA2heZRYoqfDrWnbE+hxyHdMb+Tx6jEk5yeXE1jqACxs4TIhGLI7pkDGrVUjFQhVE1muKsYqL8h6llCfsLE0MYmoLrJ6WYfqihKZ3u27LqkTzSyaXg9HJo9F03tfxpdWBaeaIJmj8AlXcRtA4GJjSRD9aALjbi7DICQe3zXzlOE0kbiU9xE7ASBXuL7WZkCw+9GM09OAfW2P/4hOxps+9SUt31ZOeakM88ZVLtTVdUZFRUVMcuyRHl5eezZZ5892J/DzhlnnFH+3HPPHcjPzz/hg09vA/Doo4/mfuc732kabP3Vq1dnXHnlleNLSko635LvueeeI4sWLTppRUA333zzyDPPPDN0MveRxuLFi8vWr1+fkZGRYUkp+clPfnLk4+pPPvjgg3kbN270P/7444eHXntoLF++fOSvf/3r/NzcXBNg/vz5wX//938/Onv27AmNjY16WmezrKws/sorr+zvvT7AunXrdq9fv9535ZVXjh81alQyFosp+fn5xq233nrsyiuv7Nf6sHvR0IcffuitqKiIgaNH+Zvf/Cb3vffe26UoCqZpMmnSpOqHHnro0Msvv5yV3rdlWeLOO++su/rqq4MD9am/azYUCilXX331mF27dnmllCIzM9N8+umnDyxcuLAcoLm5WVcURabb2rx5806PxyMff/zx7GuvvXb8e++9t3369Onxv/zlL96lS5eOBWhoaHAFAgErIyPDys3NNVeuXHlw6tSpk8rKyjqT4JctW3Z82bJlPTRP02PscrlswzDE6aefHvq3f/u3o+l+p3+jpmkKVVXllVde2fL973//uKqqnb+Zwcb73nvvzf/FL35RBOD3++177rmnLl1YN3v27AnRaFTZtm3bTnCksm677bbST1KY9tfCUDfKcVLKyQBCiEeBZmC0lPIfuqLwU4FtDlpJbraHUP0+iKV+V57MHuRSWjaim0tN9nmndvv3Kf3m4Cm93Yi6Qdo2x3+5Cr0gh+zzTkXxuRGKQs5Fn0P1SGLrXkPzmOj5mVBYjYXkaPAgoXgbXt2LlVcGoUakUMDjR7RHEIBVmEFdexJDJLANAzMYJll3HOlzIxImStLGcikIS6I07HHIp1CQUkMxFEh2oLrcJIWOyPJhumMMpgqZfqrWeR1inh3TkGoCUipDSmsYqSnYSFYGNjIlWcyspFPcuN5/Hm94dvG+u47Z7aNprCgho7EdbOkoJKkC7WAzdq4f2zB5NH8jRVaAa6jlHFkDEWfMf+/ZxQGtlUXRGrwtIfI27MFX30r9ebVERzmRNwnMjvyBA+6JbPOe4vRdwuGoUzkeaTXw6TYlrY0Uv76FvYsnECwsQuTk4NPVPpfOSG+Ckd4ElnQyEQZD922FUDAsibufQVWiSbBt7ICnc2z9qgdNdN0WFEsiLAkaPQTUe4u9D9yX1DU8QPW6v62dSa++zo7PzaW9JEDETqBIE4/qwt1PGkVedBNeo5G6rAUAjHLnkrBN9sWO4e9V5FbktuhIJuBT9+VxEA22aRl5BSdmj3QCCLU0DSmI2t2ucuHChWPvu+++gjvvvLPTBtC2baSUrF279oS1LHtvs3v3btcvf/nLwqHIJgzsjX4yYJom999/f/3Qa356uPvuu+uuu+66thdffDFj2bJlYy6++OJtf839D4ZPyxu9+zl85513vEuWLCn3+XwH+yPW3YuGfD7f9O7WqevXrw/cf//9+cuXL29esWJF4bRp0yLnnntu5OWXX85K7/u9997znH322ROuuOKKLYP1qTdWrFhRWFhYaLzwwgsHALZs2eIuLS010vtfvnz5yEAgYPVu65lnnsmtra0NP/HEE7nTp0+vnz17diy9zeLFi8suvPDC4HXXXdcGznV/ot7o6TGOx+Pim9/8ZsmCBQvKN2zYsBt6/kaPHj2qLVmyZFwwGFR/9rOf1Q813k8//XTWypUrC955553dxcXF5rp163yLFy8uX79+/c6xY8caAC0tLdqzzz6bedlll/VxKfp7xlA5/p03UimlBRwYJponCGvgZ5BtmEjDdMikbTuf9HdJg/jBepr/59XOZVJKbKPriZkmmtIeWLuwO6Lb9nLs4d8QmFVDYGY1Lf+7hub/eQ0Ab8VotIIRtP7uD0S2peTdOo4SNSJYZpyRrhxybRvpVUAIhBDYqkAknP6btkW7hOaOGB7TIrLvCB0iieb3oiQMzLwAUgOpg9LU6oyLtJ28TAOkLxOh+zClha0qThHRIEhTnMsbp3PjgZnERJLNah0iYaDVtSAiCdAUkljk2z4M0fWSrIXinB6fwL+8VkLti+tpGTuCA3NrQHGmiqXXhR1ws0Zu46nc7ZwVH8/nYxPSg877rqP8zreNxZFJ3NRxGgoCPRgh42Aj8YIsbL1b9FAovBW4iN1uJ3ezPanxYdjXWU1+zJ2F3RghVphN6/RxHPFOoE6MJOHxOPmmA2Aootl9jAA0AQmzn+skvUzSGaaUSLReBVkikkCNJMCysW2JIgSKEJzgpQdSMPG131P29rp+v074fdTPmUOssACBQJEKQgh0VHTRdxxcVgjdjnRqq2pCxafoFOiZ+NWekU3v8SATVr2Lp/Uf85Y1b9688N69e927d+92jRs3ruaaa64ZXVNTU71v3z5XSUnJ5IaGBg3gzjvvLKqoqKipqKioueuuuwrBebAOtM2tt946Ku2k8rWvfW3UokWLxv7617/uzG1ZuHDh2CeffDJroH6tXbvWV1lZWR2NRkVHR4dSXl5es2HDBs/q1aszZs6cOeHcc88dP378+JqrrrpqtJWyPv3tb3+bOW3atKrq6uqJCxYsGBcMBhWAkpKSybfddlvxjBkzJjz22GM5ixcvLlu5cmUOwNtvv+2bNWvWhJqamonz5s2rOHTokA5O9OfGG28smTx58sSysrJJr7zySgAcsnrDDTeMqqysrK6srKz+0Y9+VDhYO91x9tlnhxsbGzuXD7bvr3zlK6XTp0+vqqioqHnzzTf7JMw/9dRTWVOmTKmaOHFi9dy5cyuPHDmiWZbFmDFjJtXX12sAlmUxevToSelz+NfC3LlzY9/+9rfrf/7zn/eV0RgCv/jFL4787Gc/G7Fx40bPo48+WvjAAw/U9V6ntrY2rqoqx44d+0jH1dDQoJeUlHQ+VKdOnZrwer2DvvEGg0Fl48aNgZUrVx783e9+d1J8wz0ej3z44Yfr6uvrXX/+859767xQUlJiPvroowdXrlxZaPdz0+w93vfee++If/3Xf60rLi42wXEAu+KKK5rvu+++zvOxbNmy4/fcc8+JO1T8nWAosjlVCNGR+oSAKel/CyEGZdVCiFIhxJtCiJ1CiO1CiG+llucKIdYIIT5M/c1JLRdCiAeFEHuFEFuFELWfziH+jWAbDBTatGOJriiP7NKCjO06SONjzxN8/S9Iy+6cvjTbOqj/ya+Ibu+SGgu9u42GB58mWT9w8EFKSXx/HSgKilvHN7kc9+gRBOZMIuC41wGgeNwUXnMOWefMdfrTvAfTSoAZQ9HdCNuCUEOqTZC6ihI3sFSd5qSFJSHHMtG9LpLJBJauIhQFM8fvVKYkwkjDqey2PTjHK02UpIXUVUTKFtHEQoohImbSEU0P60l2BBp5oXgnq3J2srduB1ZzEGHaSFXBg8bF0RrmJsYgDJPMYCPj/ueP5B09hqVrNI4tJKk5B9SUPMo2VwNP+Tez3d2IP6mSabmoTZZ0yhQBbHUdY6vrGCoKXuk8d8Ljitl/1ZnUXTSHeFHP+1lQy++0qwwaGglLoTozQp7bZJKrDf8ID7uVPHZMmkir6mJ/h4eWxk8ehnMK9lMiRYrAsmVnkU8aStzALM5C6mpnuFjIvj7kiqqRLMxAiRlYqeCkEAxoE9kf2kaPoaOk/3uj4fUSrq4Bry8laSVQEPi1/tMTGgJncCDn0h4WrkIoFLtz+vR9tyuPN04/C3kiGk2fMRiGwauvvpo5efLkGMDBgwc91113XcvOnTt3VFZWdk5rv/32276nnnoqb9OmTTs3bty48/HHHy/405/+5B1sm/vuu68uHeF55JFH6r761a82pT28W1pa1E2bNgUuu+yyIHTZVaY/27dvd59xxhnR888/v/3mm28u+cY3vjFqyZIlLbNmzYqD443+wAMPHNm9e/f2gwcPuh9//PGchoYGbcWKFcVvvfXWnh07duysra2N/su//EunI4LH47E3bdq0+4Ybbui0J0wkEuKmm24a/fzzz+/bvn37zmuvvbb5tttu6xT1NU1TfPDBBzt//OMfH7nrrrtGpo6r4NChQ+7t27fv2LNnz47rr7++Zah20njuueeyzjnHSXEYaptoNKq8//77ux588MFDN9xww9jebZ177rnhzZs379q5c+eOSy+9tPWuu+4aoaoql156acujjz6aC/D8889nTpw4MZYmHf3hP/7jP4rS4/7cc891TostXbp0XHr51772tVH9rT9nzpwBnQ5mz54d3bdv30eWcBgzZozx9a9/vfHMM8+ceNtttzUUFRX1mQ5/4403/IqiyPRxnWifbrjhhuaHHnpoxLRp06puuummkR988EH/N4huePLJJ7PPPPPM4JQpUxLZ2dnWunXrhrRyTL9kpT/pF5XBoGkaEydOjG7btq3fMauurk7ats3Ro0f7Jdjdx3vv3r3e0047rUdUetasWdFdu3Z1tn366aeHXS6X/eKLL36mjHUGfbuQUn4SNWQTuFVK+V7KbWiTEGIN8GXgdSnlPUKI7wDfAW4HFgAVqc8c4OHU388m7IFTpWQi2ZX0ZluQyrHUcjNxjy0hY84ktFTOnp00iO85jG9yOXpRl1aht3I0ViSKXjiAlSWQPNpI89OvknPBPIqu/2Lnct+EkdArCqSXpO5Jej7E27DNBCQiSNWL0F2QjHA86UW4Evg0lWTcpD0jm46YSbaeJGC7Uf1eDN1CpHUNNQWkcMTqbRvpdTtFUJoCCljZvm5ijZJ2M9JvMqCrLYzh9+BXwwSljw1Zh4hrBrt9jfhMjQuPjefXIz5gpD/A2cExVCojSWDiRsN3uImRa94ncfZIcsaFOeZTODyhmCdHbGRK1MXF6yUzN3/Ijf+k4VMySAqLuUoFmH0JylXhacjuLxCpqWEj5VOermTvPEd2mGLjIEf0Ckb7wJQCNRInd+sBmuZUkXDrJCOC46YHC5XTN7xDMjdAYkSf59NHguwjSySx+pEqkgEPtEada1DVQNDD6z7tj276dWhP9nCEOlGxeFsqHK+qRlX7/z14wiH8Xh3L7SaOiSoUBAKPGGBGOUWiXWYbluLGUgZ+fuRnaNiuKAlryOfFZwaJREJJezfPmTMn9K1vfav50KFDenFxcfLss8/uUwn1xz/+MfCFL3yhPTMz0wa44IIL2t58882MJUuWtA+0TW9ccMEF4ZtvvnnM0aNHtSeffDLnggsuaNN15/wMNI3+k5/8pGHq1KkT3W63vXLlys48xcmTJ0eqq6uTAJdddlnr22+/HfB4PPa+ffs8s2fPrgIwDEPMmDGj07966dKlfTywt27d6v7www+98+fPrwQnFaCgoCulYcmSJW0Ac+fOjXz72992AbzxxhuZX//615vSfS8qKrI2bNjgGayd733ve6O+//3vj2ptbdXWrl2780T2fdVVV7UCLFiwIBwOh5Xm5uYez9EDBw64Fi1aNKqpqUlPJpNKaWlpAuDGG29sXrhwYfkPfvCDxsceeyz/y1/+8qDWqJ/WNHpvnIiF9UD4zne+03j33XeX3HTTTT3yHNMe6H6/33r88cf3K6ln3on2ae7cubEDBw58sGrVqsw1a9Zkzp07d+LatWt31dbWxgfa5tlnn8391re+1QiwePHi1ieeeCJ33rx5g4runug0em8MNWaDff9xtr3jjjsaVqxYUfzjH/+4T/T47xUnLUQvpWwAGlL/DgkhduJUtV8MnJla7VfAH3HI5sXA49IZ2fVCiGwhRHGqnc8ejNjggu5p+PMdi0pAL8wl5/NduZlSSqRpEXz9L2SeNRM9v6tKW8vJJHv+7EG74B5VRN6lZ+Mp7yb9YpsEDj9EInc+RtaMrsXxJOGNO/CMLcGVo2IlI5hmkhZyyddMjFicuOnC53KBImhBxxAaAVUjYoUJeVzkAHFp9IwwCeGIy6cjuaoLTOf+IF1dl58hLdqNKIFeJFgYJiWvbEK1DLIyO2jMLWHEKcW0iijfOHwq7rY4bo9GvqXzmxH7aFJCVAh4KOsdvvGqSlEik/DYIlpyx3F0TBU2KlooyQgjExvJT2ft54zsAP8vVEuG6aNODfKu5whzEn3lcvTuRTZSUvHYawQrSmj83CSytx+i8E872HfNfCyf89KdabUxJbaeNrWANq0IXUi8x9rI3XKAlunjcXtcTCqgzDEAACAASURBVMyMkrPzQ/Le3sehy0/H9A35wj4kZJ+Iuui3SEimqu1F2CQVqO0xjS4tG9XtwtIsJGBK5z0BOZj5ZP8QluVISfXK2xz/zgZcmovw5z+fUhoQqEJBVwZ+z/UYTVS1PMpx/yk0ZJzVd1/SIiOxnxHuEcSsKFj/OJHN7vlg3eHz+fo9JYM9yAbapj9cdtllLY8++mjuc889l/vYY48dHGr9xsZGNRqNKqZpimg0qqTJbu9ccyEEUkrmzZvX8eKLL/Zr09hfAZSUUpSXl8c2b968q79t0t7RmqZhWc4FkJJokx+lnbvvvrtu6dKlbT/60Y8Kv/zlL4/dvn37zqG26e8Yu2PZsmWjv/Wtbx27+uqrg6tXr85IR17Ly8uN/Px884UXXsh4//33/atWrdrfX/snGxs2bPCVl5cPSOIGg6qq/dYTnCipHAxZWVn2tdde237ttde2L126lOeffz5rILJ57Ngxdf369Zl79uzxLlu2DMuyhBBCPvzww3XKAAW0HxemabJ7927flClT+s0n3rFjh0tVVUpKSswtW7b0+b77eJeXl8f+9Kc/+RYuXNiZ+7Np0yZfbW1tD5K8cOHC0J133lmybt26z4yb46c76gNACFGG463+LlCUJpCpv+lchBLgSLfN6ujtdfhZgpnoI8iehm2YXQ9dV6DTvcdobsdOOi/Ijb9azdEVj9Hwsycp+NIXyDh1Sp92rI4IkQ8+xI4PJO4N3gllqdxQE61jC8KOY2RMQ5hBlEQ3cwhVoWPd+ySOHAMBRtt+bKkRsxzR7Jiei6V5MaWXDsNLPDuAR3PsFP2am4ZkO4Y0idpJtN5EofvNR1FT0+ip/0uJsCxsbFSh9tlW6hqBUyXtZ5YTavER8wWoiWTzuY7xeFQPVk4WdsDPeHcpN7fNY1JyBBGR5NT4aDKTGramcmz+VIxMH7bQOoXOP98+gamREka4SjDKKnGrXlQU1nkOstq3C4PBi3iFYdE6ZSwdVU5EODoih/aJpVieLtejJq2YlzOvolUpoCHmQttyhMy99Ry+aI4jzZRCaNQojs+fguVxDZqvecLoVYsjANPuFZFFdko7ibgTaZcS1O63BNNE9/vwubzELaNTT1UoA0c2bSlJdM9XloLC3TuZ9tQzKEbPGcGkNGicNo3QtJlOu4BAQRNKnynx7ohr+RzKuoBG/6lkx3Ywpn1Vj+8DyUOMa/8N+W27qV61icyDn+gZ95nG/Pnzwy+99FJ2KBRSOjo6lJdeeinnrLPOGjSJNSsry4pEIj1OwNe//vXmRx55pAhg5syZQxKRL3/5y2Xf/e536y+99NKWZcuWdU7lfvDBB/5du3a5LMviN7/5Te7pp58eOvPMMyMbN24MbNu2zQ1O5fHWrVsHfeuaMmVKvLW1VfvDH/7gB2dqe+PGjYNO/Z5zzjkd//Ef/1FgpCTYjh8/rp5IO6qq8r3vfa/Rtm3x3HPPZQ61zdNPP50D8OqrrwYyMjKs3n7yoVBIHT16tAGQTk9I4ytf+UrT9ddfP3bhwoWtmvZXTdcE4N133/X+9Kc/HfmNb3yj8a++80Hw2muv+ZuamlSAeDwu9uzZ4ykrKxtQIPqJJ57IueSSS1rq6+s/OHr06AfHjh3bOmrUqORrr732qU5zJBIJsWzZslHFxcXJOXPmxHp/X19fr331q18dc9111zX2R3J7j/fy5cuP3XHHHaOOHTumglNA9NJLL2XffPPNffLlbr/99oaHHnpoxKd5PCcTJ/1qFkIEgOeAm6WUHYM4mfT3RZ8nmhDiBuAGgNGj/47Fms2BI5t20uwjTyRNi8ZfrsJfW0X2uafgn1aJ2R7CVZSLa1RRv2+LycZW2l54C+3LF+Eu6ZnPbXZEiGzagX/aBLScTNT4ITxNLyDVDJI583C3/AEhDRJu51pVdI2Rt1xNTNWIx1qJGSEs1Y9hKRi2IGZpeDSJaQts6dglprukCAFS0m5EiVvGgPl2nbAscDnr5G3aS8a+BsTC2ejRJFIY6B1RImVFYEu8MsT47L3EPdns+fLnOSv4G8bIvbzOF1L7BhsBqsCNzqr8QxzRgtzYcQqJz42hCYHbjjI19id2u2sJqs69XZcaOnBOcAJmwiTnaB0UZHF50VRaYpGeUcxuUGMJ8jd8SNukMbTM6koxSuZl0nh6l62i3hEle/thgpUjsXJUGhMusvyZ5HnbiZV0PV/cdpRsTwvHx5cMeL18VPQOAylCYHXP2bQddx+EwM7yISJJRDiGZpvgsVPhSycC78rOYIwvg0PyaDcC6xB2y5JYWGiKiiIEhmUSsuOoKJ2alxJBJD+f+qk9X5ZidgJbStTSsSSFhrATqcimQzSVwcZCCNq8TnuqjOGy2lHsBHYqPzbkGsPenKvYGMnjwHk1zGnqNwD1ieHLyjFPpIL8o7T3abWVxrx586JXXXVVS22tk6T9pS99qem0006L7d69u38vWGDEiBHWjBkzwhUVFTXz588PPvLII3WlpaXm+PHj4xdddFEPaaZ0zmb6/7fffntDJBJRNE2TX//611tN06S2trbqhRdeyFAUhWnTpoVvvfXWUbt27fLOmTMn9KUvfaldVVUeeeSRg1dcccW4ZDIpAH74wx8enTJlyoBv0R6PRz7zzDP7brrpptGhUEi1LEvceOONxwcjwrfcckvTnj173FVVVTWapslrr7226Y477mg6kXYUReH222+vv/fee0csXry4Y7BtcnJyrOnTp1eFw2H1P//zP/tEa7/73e/WX3nlleOLioqSM2fOjBw+fLjzhnnllVcGly1bpt5www0tvbc7USxdunRcWvooNzfXfOedd/ZA11R2er3nn39+LzjncOLEidWxWEzJy8szfvrTnx7+uBJPHxX99WnChAl9SOSePXs8y5YtGwNg27Y455xzgtdee22f9Io0/vd//zfvn//5n3vMil588cVtTzzxRO75558fHmi7dM5m+v/XXHNN8/e+970+xHvp0qXjXC6XnUwmldNPP73j5Zdf7kwlSae6pKWPLr/88pYf/vCHnW+8g4331VdfHTx69Kjr1FNPrbIsSzQ3N+sbNmzYMXLkyD73hssvvzx41113nSStjU8f4pPkZwzZuBA6sBp4VUr5b6llu4EzpZQNQohi4I9Sygkp7/U/Simf7r3eQO3PnDlTbty48aT1/xNh7+sQae4hZ5RGdMd+kvXNqJldEXBp2cT3HUHN9Dt6mScAO5HECsfQsgOIXhYxsQ8P0/Lc6xRd/8Wu6Xcrhvf47wBI5M3H1rJA9XIk3swody6mFGwPGeT9fg315fkcHz0SRbjI0E0ipoZLsXvPgnYiaZkIJAGzCcuVjykGfJb1gO9IE/7DTdi6Rt7mfdiaipo02X3D+ZRvfxf1vXaOXjKLcCCXoIgz9sgm1jeFqZtWTm28DNuWCAE5KR/1Nz37SGBwUePozlzKPPMYMyNv8KfAFwgpWTSHkujdXJaMpMmpz71FsKqUptOq++1nGt6GVkpe3kjdF2YRH9GzIEhYFr66FpLZfqSqUPz6Ftx5Bm2nVNCsjkDS10+8JLmPWdE3eTPwRYJa//7hHxXt0SS2DUpqZ7YtURRBti/FiwwLIQRGZeql2LRQdxxF2haj7ABaTiaK24UZiuCvHktIs/nw3b9gdVjITC9SU0iaNllejRhxBIIs3UfEjJOheQmZsU67y2g0G9tSUZSeFDhixXGjMqYjiZWVTcSlciyWwO1tJcMlKXHn4FJOnMcFEgfR7RAgCbqrsBUXR+MJ9oaDjLJiLPzq99H7dTDqH0KITVLKmd2Xbdmy5eDUqVMHzaP7R0UoFFKqq6urN2/evLN3pO5EsXr16oz77ruv6K8llfS3wOzZsyfce++9R/rLmTwRvPXWW75bbrmldNOmTX/3uonDOLkwDIMlS5aMtW2bVatWHfi0p/9PBrZs2ZI/derUsv6+O2mRTeGE4n4J7EwTzRReAK4F7kn9fb7b8mVCiGdwCoOCn9l8TUhNow8c2ez9nVAVvJVjPtIuFLcLmTRp/NVqAjMm4p9aiR1P0vjY82SfP5eR37oKxdstyqh6iRVfBilJGSklYSvG0UQbRa4skraKlBKrI47WFGXc7s0YBVk01Fam/KcH7oumqChGKwtiL/GhPZnt3hOr7YqWFhAtLcDVFiaZGyA8uhAtlmC0sZdsbzuJkRAO5IEQvOM9wh/8EZb/AeI52+kocFPPiB41RfNDY3AFI5Q+v46Gc6YRGVNIizaCVzOvcCKHdj8ZjarKjovn4sobeoYlVpzL3uvO7fc7YdqUvLKRltpyWmrLqVswg883PsXhNhV5JEzrtPF9BrFRG8XbgQsIqQMqyXxk9Pf+2P2lUtgS6en209dUYuPz8QaTaHEvdiKJNC1UnwfhcaPZSTrG5KLURfAlTCzNkScyLImuqXT5mQtGunPYZyWxpSOTJO1UVbxlOVP1qalBVVEpNDQKVz9L+6mnE6mqdNqRgkJXxkcimgAloTV4zWYksL1gPP7EESZYIZpc2Yj4P07O5t8Cq1atyrjxxhvLbrzxxuMfl2gOY2jccccdI/77v/+7YOXKlf3mrg7j/xZ0XWfVqlX/MNfCyZxGPw34EvCBECLtNnQHDsl8Vgjx/4DDwJLUdy8BXwD2AlHgupPYt5MPM9FJ6npDJo0egu3SMIls3oO3Zhyq76MpTqgZPlS/F5HOAVQE0rRI1h3HM85JeVXidbhb3iBRsADb5fhKK4nj+Ov+k+Pei4h6NCxpk7AUFCFoXHw+x5IdVK55F9NxcEfr5Vjjag0ROHicYFUplken5I0ttOZ42FAzj6PuARUsurZvC5O3aS8tM8pJ5gQ6PwCWDuObtrB71Azqx4/tJGizEqPYn+1j6xdzuEi8yhsigAA8VojayDYONZSiHw7RPKuSaGk+kdEFjg2k8Dhi9PQvRiWAuN+DazA23WODnuvJdMGMW+fwolORisKE/3qFo+dNZ0fJqTTvtoh0CDJDLYSyekatDcVNi1J8Yvs9QfQmm6L3MtsGvefLjulRUf25ePUCzPYwdkcE16hCR/NSqFhuFdPnxh91ZrhUAYZl49YFPtVNwjLQhYomVNyqjmGbKKnrX0smmPq/z1I3cwZNE6tSnQTF46X5vC9gZuegOI7oALg/ItEEOJS1CEP1o9lRTNVPbugDXMnjTPjDCJKFnx6R/7+IRYsWhRYtWvTBJ23nwgsvDKWdUP5R8UmcXFasWHFsxYoVx7ov6+7Yk8bFF1/cmhZWP5n4W+z7ueeey/zud787qvuy0tLSxJo1a/YNtM0wPhs4mdXo6xjYsPHsftaXOL7r/xiwkqD3Txxt0+wxn5o83kL7a39GzfTjnfDRopsA+ZefB0DwzY1YkRgjvrGkK3JqJ9Cie1ET9UilW5TTiGEp2YTiUbS4i2SmRWNSwaUI0DVMy6LuotloMYO8/XWExo+k9+nM2XYIYdlkFoYRsRDu0gKOekaBlAT2NeBraKVpTpWj5ZiCMC20cAy9I4q3oRXL1fcSdIcj1P8+gDI9BNO69plv+9HiLixN8qK4EIlgiv0BR2QBxcYhWhp9aHUdHDtrCvXnOTKttZG30GWCtzIudhqRfS9KIUCNG+Rv3Ud0VD7Rkn7SGCyHCJW8uon26tFOTmkKjQkXDXE35YEosjCHYzGd0Mxp5Erw2SFaSkYRLfGTGTDINY/TqnVtW2gcISk8tGsF/Z7bj4vex9jDVciSWN6eebVSSjRFR3G7cBXlQlHXM0YTKrZNz/OYIpt+NDIUD+1GhDzdeVlwC42ENFL7FVgunfppU4kUdDtGAULTSZSmrndp0FUi9NEjkXHdaTsthXQkcwH7Yxab5yvMqD85OZvDGMbJRnfHnv8L+168eHHH4sWLP7L00DD+/vH3nwTwWYWV6CE83QO9CoRcJYWMuHEJ7rGf0BRAURzR7W7yE2riOO62tzEypxGUfqIp55iklU908rcx8y3K5QGaEjYJW+JSBLpqowkTgcBX10zx61vQQ9FUCM+hLcncDA4uPo2WGeNxvXyMrJwwycIABe/tYsIjL5N1/Bjehla8x1oBp3pbjSbw1rcy7pm3kJrC/qvOxPL3JeSxQCaN0yfQmt8lRhARSfZpLSQw8DcHmfjKRnKCzUyytpFPG69kXE7rnHKMS0p6RB4PuqrY5+4q3EmTLsXu6fBkair+I82o0X4KHG2bst+sY/SqP6NFE32qqnNcBgXuJH7VIm4r2EJhb2UFHeOK2eWdgTe3gNzcAJlWK58Lv0im1dq57eTYeioSW4c6sx8JnRKuKbMAR4S95zqGW6XN6MqTl0jUASK7TgGYwFYV0jRWABY2KioeVUcCvtTLjC407M6RdlTgj0+eRDQ/r3NfCgK9vR3X8WOOIgGi+xafGLbiJsflJk/vIFYysBbtMIYxjGEM4+Tjr6+t8H8BUoJlDlyNbpio3SRyhBBouX0LiT4qss6o7aOrZ7mLiI78EpariPqojSKgMqCAaWLl+Mg+0sRIjvB6NIYUYTK0fGJ2F+EKjynk6IIZGFl+1FiCsU+vpf6c6dgejfGBXeyXkzh+WjVWwE08JxuXEcd3JEF4sp9gRg6lv9/A/ivPIG/TXoxMH+3Vozn2uUnECrN7CKB3h4ZB27RxPZYd0Fr5n8BWro7MIDMlD2QbgvfU6dTX51EUPMSoquOUyEPIpMqE+Pu8mfFFGlxlPdqRANJENePYLo00tbGFoGH+VLJ2HkFISUdlN9UtRSE0bgTJnACh8pF95qldiqTEmyBuKewJ+Sj1xSnxdiukFU6sLqjmcsBVhdntZ/dO4HzEp1ykJwETm7idwK94OtUCnC+dvwkXmN2MB2wk+kAvRwBSIBUwMTFslZiMo0odXSi4FZ0M1UOm7ri1aYrSeR1KKRDCRlgWWjyB4fd1kk3/rh34du+gYen1qaimBCkQn0JVvtdooCCxnzptJJo1/E49jGEMYxh/SwyTzZMB26KP2GEKaaH29Hd2IknwjQ0EZk9Czxs6t8xOJFOSSP1XLveRSFLcRFxjaE1aGLadssKWSARxt8o7mXNRWyeTKSwM6UTsQmask3hIl0ZkTHraV2C7NPI37MHbFGTcZQ20a4UcnTy+c3cdBUW8v3ARCIGnqJ3GU6swAl4U08Ly6FheF8HqQSSrpOTcjmc54ipnm/eUzsWVRgFLQ7VkJH3Es1V2LJiNJxhBe6mdwkyDrJYgW2s/x34xCY8dI6jmURV/jz3uqRiKp3vzqNLCUlydDkDp8pZkbgZaJE7gsKN0YasKiYIsTJ+7h8xR9/MaMlRMKcjWTdyKTaE7SUDrInF7w14CmsUi80UUbN4JLOhxuDFlaMexpGV2ygudCKSUSGHhV9wkpYlHuJDYYEuUjhh2jh9LAUV2kTAbiTYo2VSQKiRsAxsFr3ARw0BTNDShMs5b2ClXpKF2Tds7dUOMfmc9/qYmdlyyCFs6+wpPmkJsjJOTK6Qjp+RWPr6ofdKW6AKSEvKMBkaE11H67hQ0W8D1H7vZYQxjGMMYxifEMNk8GbBNBpwMNB0ikiaFRmMbka0f4p1QdkJk02zv6DsnOhCsGHrbOpq9s2k2vZ36i0YkhpCSmAox4cFPFClsTNtCSpuIlejUSeyOPO04DVfOJP/AIY7ZpezNOTdVPtQNnZ7vNomCDOKFjuxSOocSYFr0bdrVfA66J5JlNhPU8kFKMu1WOpQcdnlqiSl+LGwOaG2MMbPRUagw82mSic5dWLqKvy3M/mnlNJ01FU3TCJNDWM0hqmRwbuhZEsLLXk9vQXwJQkVIiUx3NzWkjXMrsYWg7IUNhMYVk7/xQ5JZPurPn0l/aEnqRC2VbN1ECCj2OlHhozE3qpDoQqIJSYtWRE18I2eGfkdIyUaXSdrVfKJKgAZ9TA9CnEbcSuJSdJLSxLDMTjmhoSCRKfKokZTpKX8BsSR4dML5HixpoQsVW9oOSezHF707FKkghURXVHL1fCJWnA4r3qlH2l0XUxEKFja2dGKYYNFSPr7THz0dRbUCfqyAQ7ZV4Yi5uwcwQjgRtBk2uhAYUuLxTmGvNpm1cyxqjn7IrI/d6jCGMYxhDOOTYnh+6WTANgbkmtKyenznLi2i5J+vPeF8TaFpCJfutDMElMQxtI7NJOPHSdiO3SBSkmwNoegaUctAaApT2cbEyHpsaROXJlYqh647XHaMWZE3qEh8wIz8d4mPzcU2BLbQEHEDkejKY9TtBJ8Lv8gI40jP/kiT2ZE1jE5+iMeOUmQc5qzwKjKtVsoTW5kf+h1uGeeAu5pj+hjedR9htW8naz0H+LP7cCoiC+kBNHwe3r3mHNqLc7F6TclH1Qxey7yMg+6qHss7jYuEglP9LFGkgbCcaW/LrSG9Xg4unEl79WiaZ1fSPrmsZxuyi5yO8cWpCET7BLENW2DagjH+OPlug8OuSva7qvFbIXKtRjRpUGTWURt7G7fsq0Nt2o5FZIcZxaPodL9oImYcwx5Ay7fzPUTgFl3bKYaFNE2SI7Jo0ZOYto2CgiW79C8Hi5xKW5AUJm50vMKFS2gI+ieoqhBoKMRSYyoEhItH0DbO8Xy3pUNavfv3onZ0pHoL+XoGWerHd1/ThXDyjoVACg2fplHoCpMoyR5644+ByMbj2R1/PJL/aX0iG48P2VFVVWdUVVVVV1RU1CxYsGBcKBTq9x5+xhlnlPf25B4K6W2am5vVe+65Z8iKtdWrV2dkZGRMq6qqqk5/Vq1aNXSo/hPg5ptvHnmy95HG4sWLy0pKSiZXVVVVT5gwofr555//2Pt98MEH85YuXfqpuZAsX758ZGFh4ZT0uP/TP/1TCTg6n2VlZZPSy88///xx/a1fVVVV3dzcrKbP4cSJE6vLysomzZw5c8LTTz89YNTj9ttvH5HePn0tVlVVVd99992F06ZNq7Jt535imiZVVVXVa9as8Xffd0VFRc2TTz6ZNVif+ttvKBRSFi5cOLaysrK6oqKiZsaMGRP27NnjSm+Xn58/tXtb8bijd/b4449nCyFmvP/++x6Av/zlL970OllZWdPS53fu3LmVu3fvdnk8ntru/fn5z3/eZwoxPcaVlZXVY8eOrVm6dOnoj/pb630uf/CDHxTBp3t9l5SUTK6srKyurKysHj9+fM1NN900MhaLdd7kN27c6DnllFMqy8rKJpWWlk665ZZbRlopXvHggw/mKYoy49133/Wm16+oqKgZzAxiKAxHNk8GBiICOE5Bfauh+z7kbenku6m9JIeEEAhVIXG4ASXgQ8/N7pJRknZnnqi7+Q/YdoKt2V8ioubhFaBhE0taiCw/is9NWzKGqij4vCaeaBtKMk7E1b9ph4LNYVclda5xhNRsjKiCkEmkcHQbsW2nWlkRWELFEhpWr2lZTRqMNA6xzTOLvZ6pCGmzwzODmPBxyFXlFJ0IjZgw2OJqIMv2UGgFWOvdzxgjm1Nj/dyrFYGwRT9+4P1PUadzCW1FR7USYJsI6ZBOaZnOuVE1pEvD1D2EMzp/a9gSopZKXdTNKE+UgC4Rto2u9r3PlPnjPQLQCcXHVt9cPkjpj0qhIuIGfiVIxA70ti0nKU3y9AyakyGyNR+NyQ6SlulEOaWJtEHvNwqYdhh3CnXSV5ZiWbQVeDADEg8uktLCLwQ2Esu2MGxr0CpwRSoYwsKVEut3Kzo6Oko/TkuqUPCqLmLdbSttGxHuwHLpoGm4kya5b64hOPtUwpOnAU6up9PexzPFUIVjfqQpoFshimKbaVTzifHR5MROFFY4qWnZbmPoNU8MZntiSM2n7t7oCxcuHHvfffcV3HnnnZ3uJLZtI6Vk7dq1Jyyc3nub3bt3u375y18Wfuc73+ljkdcbM2fODP+1RNpN0+T+++/v13/6ZOHuu++uu+6669pefPHFjGXLlo25+OKLt/019z8YBvIbf/zxx/f3Jyo/0Prdz+E777zjXbJkSbnP5zvYn4tQ9wp1n883PX0tAqxfvz5w//335y9fvrx5xYoVhdOmTYuce+65kZdffjkrve/33nvPc/bZZ0+44oortgzWp95YsWJFYWFhofHCCy8cANiyZYu7tLTUSO9/+fLlIwOBgNW7rWeeeSa3trY2/MQTT+ROnz69fvbs2bH0NosXLy678MILg9ddd10bONd9aWlpovsxDYT0GMfjcfHNb36zZMGCBeUbNmz4xEL8n/b1vXbt2j3FxcVmMBhUrrnmmjFXX331mN/+9rcHw+Gw+OIXv1j+wAMPHL7kkks6QqGQcsEFF4y/++67C3/4wx82AhQVFSXvuuuu4t///vf7P42+DEc2TwbsgaOO0uz5XXjTTjrWvd9nvYb2DA42Z2PZ/RAATUPNDKBoGla7ExlSEg1k7P8RauxQqmo8jo2gXeQCEq8qkC3tmO0h1MI8AjMm0pzoQFdUtky8mLfGLgJVJZgMo/cTrYorfj7wnUqbVsQBdw2oKtLvRm2PYY7MQXpdjg0lYAuNPwUuoFEvdQgwji1jUvGyKvt69nqmOmMhFPZ4pmMoHgzFzYeeqZjCxU69kd/7dpFje5mWLGaUmcmSyJR0+l8fKEKQMHqbNA54BtCiSZSkRLWcdAJLD5Bw5SDT5Ejt/+UtYqrsDfuQUtKeEDRFYX/URyLRP984HPWwJ+TruXehIlMkXMSThDMKEDETrJ5kWUqnunukO4cs3QfCIaCqUHqQyL5Hl/4rcQmtq8Jbgu11kZAWXsWFhkMILWkTsZ0XDGWA24GUElUo2AJ0VQdpo6PjEmq/BFUTKmO9hWRq3s4iJC0WZ9rzvyfr4CFm/G41OVu3cPySy4mO78qFdXJn+7YXt2Sfwrf+oAjITumHqlaEovA6sjcepuy1zUNs+dnEvHnzwnv37nXv3r3bNW7cuJprrrlmdE1NTfW+fftcJSUlkxsaGjSAO++8s6iioqKmoqKi5q677ioE58E60Da33nrrqLRt39e+9rVRixYtGvvrX/+6z8HtFQAAIABJREFUM+q6cOHCsenoVH9Yu3atr7KysjoajYqOjg6lvLy8ZsOGDZ7Vq1dnzJw5c8K55547fvz48TVXXXXV6HQk5be//W3mtGnTqqqrqycuWLBgXDAYVMCJztx2223FM2bMmPDYY4/lLF68uGzlypU5AG+//bZv1qxZE2pqaibOmzev4tChQzo4kacbb7yxZPLkyRPLysomvfLKKwFwyOoNN9wwKh3t+dGPflQ4WDvdcfbZZ4cbGxs7lw+276985Sul06dPr6qoqKh58803fb3beuqpp7KmTJlSNXHixOq5c+dWHjlyRLMsizFjxkyqr6/XACzLYvTo0ZPS5/Cvhblz58a+/e1v1//85z8vHHrtnvjFL35x5Gc/+9mIjRs3eh599NHCBx54oK73OrW1tXFVVTl27NhHOq6Ghga9pKSk80Y7derUhNfrHfSmEAwGlY0bNwZWrlx58He/+13OYOt+XHg8Hvnwww/X1dfXu/785z97d+/e7aqoqKhJf/+DH/ygaPny5SMBtm/f7j799NMrampqJs6YMWNCOtraHd2v75KSksm33HLLyOrq6omVlZXV6fXr6+u1uXPnVlRXV0+86qqrxowcOXLyUNdJVlaW/atf/erQmjVrso8fP67+13/9V97MmTPDl1xySQdARkaG/fDDDx/+xS9+0em1fvbZZwf37Nnj3bJly8dPpO+GYbJ5MjBYZNOyeogeJuubSBzsaZRkSwjH3ViWgmV3E39PTSMrLg0t04+rtAjhdpFsaMJOGEjFgx7ajLv5JWKZ59KSMR9SWXMOBIquIbICmMEDBCMduFLRsVy/ZLz7AEYshq72vG41mSTD6m1DK7Fz/M4n24ftdyF6Eb4xid3MD/2WivgWFnQ8hdce0JKW40qoMzpZmyzhG8FTGWllUm0U8bXQKWRJT/+K7ICqQsK0sK2hCYltSxQTRFLBUr0gLaRQsIXaNTfeT74qgEe1GeUKUZkRZZTPAF8uqu5CFf0TXU1I/Fr/Lx6j4nu4kGfIyo9jFWehxPpKLqlCIUf3owsNt6JjSxu3ojtT1wNNeUuHaAoEKhpqwkSJJYlbcUI2qAjcioZPdVGoZ5G0TaQEt6oPOI0uJahOa6iqBlKiCMhVsgctKsrTMrGQSCRxr4v9p84hkpdDNDcb1TQxc3Kxfb3IeK9T6Lhc2RhDnFqZSv2Y4NdQhSD2/9k78zA7qjL/f86p5e69ptPd6U5nXyEJkEwimAgijAKCYVW2sEhYfkZAUcFBZWRwQUCf0XkQFFllnAGjgI4OyzAioiiJAUISEgJk604n6b3vWss5vz/q3u57u293Egw6an+fp5Pue6tOVZ1bt+pb7/t9v685nrV1n+N/DjuWzfPmjL7yXyFc1+XJJ5+smDdvXgZg27Zt4UsuuaRz06ZNG2fOnDlwMj3//PPRf//3f69du3btpjVr1mx68MEH61544YXIaOvccccduwoRnrvvvnvXypUr991///21AJ2dncbatWvj55xzTi8M9kYv/GzYsCF07LHHpj/0oQ/1XHvttU2f+MQnms8+++zOf/iHf8gCrF+/Pvav//qvOzdv3rxh27ZtoQcffLB69+7d5le/+tXGX//611s2bty46aijjkr/y7/8y4AZbTgcVmvXrt18+eWXD1yEcrmcuPrqq1sef/zxNzds2LDpoosu6vjMZz4zYCHheZ5Yv379pltvvXXnzTffPCF/XHXbt28PbdiwYeOWLVs2XnbZZZ37G6eA1atXV55wwgk9B7LtdDot161b9/q3v/3t7ZdffvmUoWOdeOKJyZdffvn1TZs2bTzrrLO6br755gbDMDjrrLM677nnnhqAxx9/vGLOnDmZxsbGEW8md911V31h3levXj1gZ7JixYqphdevuOKK5nLLL1myZMTOG4sXL06/+eabB50OmDRpknvllVfuPe644+Z85jOf2V1fXz/s4vfss8/GpJS6cFwHuk+XX355x3e+852GI444YvbVV189Yf369fslQA8//HDVcccd1zt//vxcVVWV/5vf/GYY8R+KwkNW4afwoDIaTNNkzpw56ddee23UObvssssm3XnnnTs2bNiw6bbbbtt11VVX7VdWMW7cOG/jxo2bLr300n1f//rX6wFuuOGGCccee2z/xo0bN51xxhndu3fvPqDUdk1NjWpqanI2bNgQ3rBhQ/ioo44qiX4fdthhuWw2KwuSACkl11xzTfuXv/zlQ9J1ZCyN/m7Ad8v3DAS0p0o4U82p7xu+upKQp14ltUBKIy2T2BGzgrRk/zbs3WvRma24/hSSUz6L3fozPOL4qQwpJQnZYWL5PuDSNpGGpL23g7fdOH7WRYYCglGd2s0/ZF6iT1SR0lFA0OS+xezsH9lpT2dO9o88mzidPqMWkXbAU6jKCH5dAoRAR21ERz8acPH5VfgtDhOaOq+aPdZEDO3hDumXvs3spt6PkxEu/1b5O2r8CMdmp3KU00SDKpMCH3HCBQKBp2G/3zrlo0wLPxRBGArTTYEw0Jgo30cIyaYOqJFRGkyflHJI+znq7AosqRlnZSFSD9KkzrTBy0Jf+T1riuRG5IT7VAPbw3MAgUqEMfb0DTmi0sx6WFj0kyGS766T9QNu4PgudhE5zhsOYQoD6ToYBOeSYRmMjzYSCynq7Aoc5RI3QsFZJiAsrbJyjsKYmmAZS8pA6iqDNP1oHNCWFrYEpXP4QqPHNzL7qSd546QP0ZByCG9/m+ykonuxGP4ZB9sVpPyg0nykfYQgsikK7gJCYAhBUyiFbnznOtD/a8jlcnL27NlzAZYsWdJ/zTXXdGzfvt1qbGx0PvCBD6SGLv+rX/0qfvLJJ/dUVFQogFNOOaX7f//3fxNnn312z0jrDMUpp5ySvPbaaye1traaDz/8cPUpp5zSbVnBOTdSGv0b3/jG7gULFswJhULqvvvu21F4fd68eam5c+c6AOecc07X888/Hw+Hw+rNN98ML168eDaA67pi4cKFA0+mK1asGPqky6uvvhp64403Iscff/xMCKQAdXV1A5Gvs88+uxvgmGOOSX32s5+1AZ599tmKK6+8cl9h3+vr6/2XXnopPNo4X/jCF5q/+MUvNnd1dZnPPffcpgPZ9nnnndcFcNJJJyWTyaQcqud7++237eXLlzfv27fPchxHTpw4MQdw1VVXdZx22mnTv/SlL+299957x1188cUdo30uhyqNPhQHkkUYCTfccMPeW265penqq6/uLH79rrvuqn/kkUdqY7GY/+CDD75V6PN9oPt0zDHHZN5+++31jz32WMXTTz9dccwxx8x57rnnXj/qqKOGC97zeOSRR2quueaavQBnnnlm10MPPVSzdOnSUXvWH2gafSj2N2e9vb1y3bp18bPPPnvAusVxnP3ai5x33nndEDwAPPHEE9UAf/jDH+KPPfbYVoCzzjqrr6Ki4oBbyA5a0mlR7lo69DiuuOKKzttvv73x9ddff8dazQLGyOa7gdGq0YcUCJVdpCSaObiw9n2EZWLE8jrC9lZEx2/xzHqQBn4yTabqfcSmN2DqKKl1b2KFB9cXhgRbkXRdMkYC3zOQ+aF2Vc+mz6+Etn5O7HuEreF5eNjstibRak0lK2L0ycAcW7g+Kh4JNJoFC6dYODhmpTGl5FV7N5IJTNBBs6i+SKmxdpdM81D8j6zoP4oGP8FHUnN5KbSTV+3dHOUMCywExz/6tJHKulhRCyHLT7DIOFh7e0nFa9DhEJaTBq2CyCYGWhroeB3SlWhpgXLwlI/SNt2OSdo3aDSySGmCWfjujZwcGM2pyFUh1jX/IyoeDdpHChGk0o28GX8yC5kkelw1QgjC0kIKSa0VJ6d8dqpOlNakVC5oKVnQb2pQyieS0eiIJttSiycEbjZFnYwyJz6Y/VRa0xSqIWrY7HP6MEeoRtc6IJbVRgKMTMmD1GjXWA1IAj2t1hDK5sCyiYVixF/8A9JxyE6agtYaf2C80klTGkwhiBiCrNJERgik5vkv5P/XWtOUep60iNFGeZuwv0YUazaLEY1Gy4bXR7sJjrROOZxzzjmd99xzT83q1atr7r333m37W37v3r1GOp2WnueJdDotC2R36A1OCIHWmqVLl/b97Gc/K9sHOpFIDNtPrbWYPn165uWXXy7bHiocDmsIok6+74v8Oggh9MGMc8stt+xasWJF91e+8pXxF1988ZQNGzZs2t865Y6xGKtWrWq55ppr2s8///zen//854lC5HX69OnuuHHjvCeeeCKxbt262GOPPXZItHIHi5deeik6ffr0EUncaDCKGooU40BJ5WiorKxUF110Uc9FF13Us2LFCh5//PHKkchme3u78eKLL1Zs2bIlsmrVKnzfF0II/d3vfneXlIc2oet5Hps3b47Onz+/zTRNXSiSAshmsxICWUQikfAOlsgWncfa87yB8/idoLu7W7a1tdnz5s3LHnbYYZnnn3++JGq7ceNGu7q62hs3btwAebUsi1WrVrXffPPNDcNHPDiMpdHfDYyi2VQ5Z+DLqDI5On/yLLkdpR3BAp1mfpnim69SSLsoxTvjH1EnfoNsy0Wkc1MRpiSxaAHWxKmIaIi0FpjF33snTWzKFDAjOIaN8osIkZAko+PIEqXdmkSPUceO0Ew2RJaQNKrYHpo1uLAhUU1Vgy0xASyD3zZ08B/hdXyz4nk+nJnDB7LTi/ZdD7R8BIi7Fkszk6lSETyhCGuTChXm/OSRI87daN8xUwqynsIb5fYpfIUfNnAjcbxICDPtYKZyA0ID36pA2jFmN0RpTBhB8RDQnatkezpCt2PipX2MrtRgyPkdXLiEE2TGdMQaGENVRpA9qYBwKo0QEisRQ+e7FVVaEeJGGFMYhA0TrRW9XoqwtFHF5A+QWQcrFEE3jENGoji2wI9HhzkMSCGYFq2nMVTN/MSkEXuSayAuojSZdYFmoYRsjs42JQKlNS6QmdDErjM+igpH6TzxZLqO/yAAWa1I5qUnQ4dTQNgQNIclntbkRrD90gzwdKQItJ916ZeIbmpnxk9fRGUyI+/n3zCOP/745C9+8Yuq/v5+2dfXJ3/xi19Uv//97x+1P3llZaWfSqVKTuwrr7yy4+67764HWLRo0X6JyMUXXzz5xhtvbDvrrLM6V61aNZDKXb9+fez111+3fd/nxz/+cc2yZcv6jzvuuNSaNWvir732WgiCyuNXX3111DTp/Pnzs11dXeYzzzwTgyC1vWbNmlHTmCeccELfXXfdVee6QRByz549xoGMYxgGX/jCF/YqpcTq1asr9rfOj370o2qAJ598Mp5IJPza2tqSG0J/f7/R0tLiAhTkCQVceuml+y677LIpp512Wpdp/vljQb///e8jt91224RPfOITe//sGx8FTz31VGzfvn0GQDabFVu2bAlPnjy5TLu3AA899FD1GWec0dnW1ra+tbV1fXt7+6vNzc3OU089td+0+MEgl8uJVatWNTc2NjpLlizJNDc3e11dXWZ7e7uRyWTEk08+WQlBCru5udm59957qyGIhv/ud7+LjD56eSxevDj50EMP1UCgde7r69tvJXxvb6+85JJLJp144ok9dXV1/uWXX9750ksvJQqV78lkUnziE59o+fznPz+sQGnVqlWdv/nNbyq6urr+pBNyLLL5bsDNjhjWUjknuGETkE13TxcqW/qdKaTRYWhkUyEKvcTdDFgRjJoGIrMT+L1J4kfNwYgHshRtmigxaGfj9fYjpCQ+7T3QupYuy8D3zaASu2DgbgZawFejx+z3EHWZ7j+dMZ9WI0VzLkGlCq69Kt8tRiZzoDUqHgY04X6XD6Sb2Fvpc3vlr5niVpOSLlnhYemRvzsjURshBaYUw9/3FUZPGr82uMZ4YYtUfS2mZSPkeEJdDmYmRyiTwY2FUFGFbUi6sibtqVpipkO1SBLWkmoyICV+Yy2yJ4lKBHKDg4KvEY6PN208OjRI7lRtHOF4yHQOHxD1VViJapzdHWBbmMJkaiTQ7AstMIWBJUwsaZDxcshUcD/zQ4GmUrQ0QSyB7Tn0+kmqZLyElB4MAj1kHlIOMEIBA20pfV2u3aUgrX10vl2mQGAaEkcpME38xKBUIiSMPHEdHtm0JURNSVPYoC3rE8pHrrXWOApChkDrgGRCQDp9DevHX0dHcjOhqW2jh5nfIYy47R1IBfnBjHeoxipg6dKl6fPOO6/zqKOOmgNw4YUX7nvve9+bGc3CpKGhwV+4cGFyxowZhx1//PG9d999966JEyd606ZNy5566qk9xcsWNJuFv6+//vrdqVRKmqapr7zyyi7P8zjqqKNmP/HEEwkpJUcccUTyuuuua3799dcjS5Ys6b/wwgt7DMPg7rvv3vaxj31saiG1eNNNN7XOnz+/vDUGQcTnP/7jP968+uqrW/r7+w3f98VVV121ZzQi/KlPfWrfli1bQrNnzz7MNE190UUX7funf/qnfQcyjpSS66+/vu32229vOPPMM/tGW6e6uto/8sgjZyeTSeN73/vesGjtjTfe2HbuuedOq6+vdxYtWpTasWPHALE+99xze1etWmVcfvnlnUPXO1CsWLFiajgcVgA1NTXeb3/72y0wmMouLPf4449vheAznDNnztxMJiNra2vd2267bUe5SvR3A+X2adasWcNI5JYtW8KrVq2aBKCUEieccELvRRddNExeUcCjjz5a+7nPfa6kGOIjH/lI90MPPVTzoQ99aMTigYJms/D3BRdc0PGFL3xhGPFesWLFVNu2leM4ctmyZX2//OUvtwKEQiF93XXX7V68ePGc5ubmXHGE+Ec/+tFbK1eunHTrrbc2ep4nTj/99K6jjz76oJ+Cv/71r7edddZZU+fOnVt99NFHJ+vq6tyqqqqyEa5jjz12ptZaKKU4+eSTe2699dY2gHg8rn/605++sWrVqpZrr7120p49e6xrr71291VXXdU1dIxwOKwvv/zyvV/84hcnHuy+FkP8KfqMvzQWLVqk16xZ85fejeHYtRb2boTYuGFvJddtDirCYyM/1Ozrj9KTjqAUNFYlqci3PsztbCd6+HSi0xrhxxfD/I/B3NPQrkf6jR3E5g62eMymMvz+6XVUVsZQrge5LNaEcdgLT4LUPjZnO+hp+yNRwx4siPEV9oZWVHx07bVM5nDmTABrkBTu9XtwtUdLp4Wxrx8Vtfmf8FbesrpY2bUw0NGFLFQ6wz01f2S8rOSk9onY8Tg/ib7GvMx4ZnrjB8JTaU/iaoEEbKGIpDPkQiY9OR/LLBNN1BrX9akyDax4USvQnIdM5fCro8hUjj21NnsrZmKFQlhOP/1bO6lULtrT9JshtBBURU0ihqa1z8cQimnsIVpdgUin0RWV+DMPw1q/FVURC4hX9zawDkxPL9IOujqKV65ft+tjb2rDUR72rBamRxvIbNkeGK7HS8+X1mwXEWkRMix2du0mXFOJioVgWwd7c1ka5y/CljZ7vC72+N2EsJjIBA5rqjxo3pVzfbbsSRILmYi2PYj+FIRD5DyfRMgiErZI+hpbQCwfSpeA6xts6hIkSWIKaLCrqDRM+nyPqBw8d9LKx5YSx4eIIahLDMqqUp6iLmTQGDbo9xSb+j3CEmKmJONrsiogwr6GGkswPW7xZsrDURpbCnak95LtS3H65TdhTTgwL1sAIcRarXWJk/8rr7yybcGCBaPq6P5W0d/fL+fOnTv35Zdf3jQ0Uneg+PnPf56444476v9cVkl/CSxevHjW7bffvrOcZvJA8Otf/zr6qU99auLatWv/ZBudMfxtIpPJCNM0tWVZPPPMM7FVq1ZNeic602I89NBDVZ///OcnPvvss5uLiwUPFq+88sq4BQsWTC733lhk892Alxm5L3o2hyjjy1iMrGtiSIXSBgX5h/YVRiJGdNYkcNMw/6NQHzyACcssIZoQRDYREq0UKpcjNL4SuzFfVBarI5tuwzDtQC9YcCk3ZBDddPOaU2uk/RzUFkIQYXos9VveF56HtiMUdrpaRWj0Eviui6ypQIdNcv297Az1s5N+5kdqmKrinNUxC5lx0KFcPvIJva7JnlxAepuNJOGwCWkHLcvvk5XMIXMuImJBxBrYP+ErtG0iUw4IiW8YuNs6MKY3gGVgRxSRNDimJCw02jKoCJtURQzq/G2kBRhpjV8VgVoTKiagi6UMQgQ/unx70qEQSuEnRnjQyPuUKl8RjcYxYmFi86aT3vgWyvOQRWm1WhlFSokvQOjAGUBbBtLXOBELM6/hNIVBQkSZaI+nr0uyY7sgGoVxdfqASWfJ42hJGl3gaY2nNVEJPtDvBe9ZAgwNppBo5WNJE6U1MRmQzZI5ERASkqz2YYhmUwN2/qWwFFRagnTedcBTmogk37BADxjMi/x641JrMNwUmzhkXtp/l3jssccSV1111eSrrrpqzzslmmPYP/7pn/6p4f7776+77777ympXxzAGgK1bt9rnnHPONKUUlmXpu+++e9ufOuaFF17Yc+GFF/bsf8l3jjGy+W7Ay8EIpEjn3IFUeHLNRpy2fdScdmzJMlnXxDZ9PF/i5YuFtOtiVOSraq0ozP3I8LG1JpXziIWCKmEZDaEyTpBKjtol0TfHczCNCLjd4CQBAdEadNhCdqXAMlBlyKZMO2AaJVpFD58Wczw+Kngvnwo9ymniKJqQXhYvFkLFQ0Tbw3x692KebNnDRMZhdKdRlRGUHXQiKqA+7FBpefhaEM1mUTWVkB4W4R+EAD9i48ZsrJyLjuajm0qhcRDYeBNr8Z0MfgiSyQ6MmgbMaZMwXt+BQNCAIlE/6I6hhMRAYSDxLIlhGhAJB6TcMgMNqiEDGYJSwZzsl8GJoLBqBKhoCAeIWAHRFqaB1VBLbuceZGLw62r0ZwNZRU0sIKhRG4TAi1pkY+aAZ2atUUGtUQEI3JyBEdGkUwK/GswDTQAXs03LHPBOlQT9yMebEqU1ORWk06stQZ8XeHvaQlBrSKqsChwEYWlgiEDHWZB4aA1hadAr/FKNch52/sHBkoKmsMGbqULLV2gMGeSUZkdWlWo2NVTk3sRU3hjZ/BOxfPny/uXLl6//U8f58Ic/3P/hD3/4z5Ke/UvhD3/4wzuOSH71q19t/+pXv1oi4L/++usbHn/88ZI0yEc+8pGugrH6u4m/xLZXr15dceONNzYXvzZx4sTc008//ea7tc2/NsybNy+3adOmPymS+ZfAGNl8NzAK2VQ5ByMSEAmVzeEnS7MtvhIoJZHCRwg9cPPVjocd94Lio70boW72MD/It/f00ZXMMn/yOJQCIxrG7+giMmsSRkQGJDUPRzmEYrWQ6wM7DvnWgjpiI3QqCDCVi9YpjTdpUNP+h+xm1jtvc1HiRExhoP3SCLzIeexJOMSjEsuQ6MootX1wVnwZprEPHdO4M+qR/VnMbYMNS6SAqKnQvqZVxQj5NlUENFb4CuErlGlgZF1UyMK3DFK1CYQliXX2Q9ZFOD7ggSnQhsSL23idDlRHMCtCeU2rjW9buKEQuq/UfignBHVGhKTM4BoisCLKR890JITIOWjDBisCTirQ6moVzOdorR9HIZve5FpyXnrA4gjArK7AbetAuR7SCr6ywg58MVXawakKE8mT//YpFeiSUypfaKZA+2CYgSGC7x842Swx6zLkAPk0DEnS9TGFRkqBbUBYCcbZkn7Pw9OBUXxEGsQMmwhBK0tbSDytSgzhbVG+f5GGAY0mBIRTo8nk7WqrbUlOwa4isln4/62aj9KW6YTevmHjjmEMfw0o7tjz97DtM888s+/MM8/8qyNSY9g/xsjmuwEvN1B0U0B2Zzv2uGq00gPV6BVLh1dee0oGISHybjiFDkK5PiKb7wHveHjzWXjPJ2DKsoH1fKXp7M9AvvpXaY1RmcCsrcKsqQS3b6Azjqe8wPg7FIe6WcEA+zYHHpSVEVRfOigD9lTZVLqKDGoiQ8IiIaMD5t56iJ5yl+jhrpo/EkquZVnkcKj02R7dw8d0IzpioYwgGhisFxyr60NPWlJpe4QcF9eOke4XVCII9aUxLBNlSkLJNBgKkRZkayvwKiLkBNDZj5vTWJKAEFbXok1FJq3obg3BRAgbUTzlYssQvVOacT2fqgIp0Rq6elCeTyJqoaXPHhxcN8l4Ah2pqq7A3N6GDuUjxrn+4DMPVwW/l9Nw+oUqFg88D8zh2lgtBEhJuKiLkbRMrObxONt3B5HF/EyJkI3o7cdtihIBfOXjoyhXkK+8/ENL/iebFdihA0ulF8u6tWEMtsDMF/5opQjl96sxJDHz1eCeDur8LWkwzho8VksIHBUchNZBAZkpguKuYl9+lS86sor2sfB7TmlsGdjKGEJjCLDloF50MNF/6AuDxjCGMYxhDAeHMbL5bsB3hpENp3Vf3nB69IIsXw06Wws0Skm8viS4HqplGXLyMmhaCONmlaynVL4ntgiiWEprZMgkdlhey+kyQDb9Ymumgl9kuAKyfehoFHdmI+auLkRfZiAKJwqRQkMGP3ksCE1lQahIL2rkb/VaY3SnaTKinCyO4Bf6ZXpVigozSlzEkULi11cOXw/IZjStfoxYtpuwAS0TDXRFCO9lgTIkOmKRiVk4RIglDOx0D17YDozdDUHGlGzyahlPEtsK4Vc2Y3udJHt8IrWaVNQkblXT6bRhEwpabyJwQzayP422TNI2JNwIlq+oQhAyDCp0jKSXoYIEqroCtueLHc1wENE0QsE85ooiaVoj+7KoRBjhekHxVa4/eJJwMxCpohie9olKe0B/ODA94VDRkME8GZEQynHREU2n04+vFQkRLtsJyPfFgJZRAH29EImAHYLWzhSNNdGROwgxSN7KaZF9T1ETy7eJzI9hCshoqDWjJEKlhc+WkOh8/3NFYFtlCUlEyBJrIz9fiV7s2yeFYHxIkvT0wD6ZIrBHihmlZLMyu5nqzBZ+Lw4ve1xjGMMYxjCGPw/GyOa7AT8L9mDXEu0h0hn6AAAgAElEQVQr/L4k7j5r0ATd9ej44S9IHLOAyKxJg6uqwQifEMGNHBNiixciJ3xo5E1qNUAmlNb4qshGxneClHso6GjmlWunGR8P6byThFaoiIHZPXhDF54PvkJHB4+hQHpKTHxlQEaF46MjNtLzWWzPYGFkLo72CMsi4lGUHtWWiYqHkWmHSq2ZOw3s7fnipTzhVVLiRUOomhg9aZusYeJOriOW3I5nxRBKo5TGrAtR25ajusFmT1eEnrd6KPTjCTVLbDtCwqpiX3YX2tD5/kPQM2kCNX1pvJ0pvGkV1FZVo3ZuxohFWGBV0Wc4vFE41oKhvdIgTUg0BjlqwwZpBXIHaYDng2kEWlc0/rgEGC7Y0VJSWvQ5Ro1Q8Jl5OQgF9kAiZA18Fn4yjRELYyRiCFMi6Cencmg0k+xGMrky0WhXBJFEpbFDgkw62HWlNCHLwPUUoRHS+1oXGRINsbwyhCDn+mVsjwIz9qi0StLgwetBn3UIUvRmXl9aYZrsLuozr4BwmXEnhE18rfEKD2VCEDcEoQLZlAKtFWFvH1XuNtBjZHMMYxjDGP6SGCObhxpa57sEFXUBclxU1sHrTSHsgGzpbA5hW8Nu3q5flEZH4+c87Em12PXVo1Y8+ypPDHVAAou7GOA5EKsLyBDgKnf4AEY42GelINsD5CitDBFgynynoAC7/A7+I/krPhY/jolm3eDxWiYimcVrroGoHRQdCUlYjNLxSgpUTZzevj4sobDjNiJqQTKLMiWt2xyIV0FUETZy2JWVaD9GtiODhcYSaTQmvrTQFWEap8wEK0STkER2dZHe20lVpJcdoTrCwiZsxohbVeRUhpAMI7TAExbu+PH4u/egohBqOQz6s8iaCiIyiaOCdpbBdAh0OBR81tIMyGMBdjSIXkoDmfPxa+MY3YFhu4ra4LpQMQE6h7ujKDQhaUA2GTwguFmwwkjLxKyM43X2IuNRItNbEKYBVGH2pJBCEjVCRESIDMMLhn1fIKQqTHWg3VTBQ0nYMnA9fxSyOfjQEfSEDH51NfhC4JRx0pci6MNeDkZRiFXpQIcJEJMmGnegeKjgsVl+DFFsiEBLdPBSFjUEHrA79l5eNQ9H9r2rRZZjGMMYxjCG/WCMbB5qKC8vqBu8E6qcg3Y9VF8Sc3xQ3GckYtSdf9Kw1V3PwCjWbLoKs6YK/nAX7NsCp327dHNK09aVojftDDjwKKXxfDUYOFR+kOotbEO5wzu/SAGhWL64yULFLLTVj8i66HBQSaJD5mDXG8AWJjOtZqpkae9pLQTCMlE1sXx1+gHClOxSceLSo8kwUBEL6QUtOn0/hzZNhJdjT3uMyLw6DMDZ3Y1TnUCZglRbFjcDXtygudbClAHdqZ1YS21DFNJxnB5BPF98U2FVsyO5B1fmCKVjyD4Lr8nEq6nFj6YxI1FUPIGsGgc6GaS2ix8ioiFEXyqoTId8lFOAGYFsIWqpUdVRtG0EnYfQgbaz0F7Sd4Mx8wVlnlaERH6OE/XQ1zogyQhPbcatjGNWxPJEM4AlDQxfUmVGsJSJKEM2lR5Mo5P/f19vmnhMEo9YOG4pYWztTNFQHcGQcqDfOpA3dQ9+dTXEpcD3RyCbIzwYybzcA8BHY4vBFHy1DJH2U8TNQHtsvYMOTVFDEJaCpK/fVcXmyy+/XJVMJg/ZNTQej3tHHHHEqMzYMIyFM2bMGDCCPuOMM7qGVjAfSjz88MOVGzZsiLyb2yjg29/+du1NN93UXF9f7+ZyOXHxxRfvu+mmm95RJ5vNmzfbH/7wh2e88cYbGw7Fvv385z9PnHvuudOampocGDRL//SnPz3hhz/84biampqBdNFvfvObzS+++GK0eHmAr3/96zuXL1/eX/gMPc8ThmHoc889t/OLX/ziHqOMJV5xdfaOHTtC48ePd8PhsKqvr3e2bt0a+d3vfreppaXFA7jgggtaWlpanGOOOSZ17rnnTmtubnZyuZw4/fTTu+64447dQ4+heJ/KHfP111/fsHr16loppZZScuedd27/2te+1rBz585QOp2W3d3dZmGs73znO9tPPPHEVFtbm9nS0jL/a1/72o7PfvazHQDz58+f7TiO7O3tNbLZrKyvr3chMHA//vjjZ8ViMb/QQvI973lP//3337+zeD+K5ziTychZs2Zlvva1r7UuXLgwC4G36d69ey3btpXrumLZsmX93/zmN1sLbRf3N99PPvlk/DOf+czEZDIptdbiiiuu2PP5z39+X2Hb3/3ud+u3bt26vqmpyQOIRqNHptPpdQdx+oyBMbJ56KG8YW1uvK4+hJT46ex+b54Zx8LIR6C01vhaBF2BZp0MkeFG4Kmcy67OfowCCRBBGt311WB6W5eSzYyXQZbzAQ1VQuqNIA1cMQGv0cXankKHTEDjN9UEkTng5dybhIXNR2JHDx8nbOFXRg6OaBJ0JZpLF15en+g3VOHnrUFbptp09GXxUjmEFUGlcxixMHZTDU7WpX97NyLiow2BtiRi6DxbEXQijOptx8yTzYRVw/SKI+jM7SbjZRC+jZcEZYdRuJimhbFgASISIbt5WzBOUUpYRcKYXX2D2sG9XahoCJSLzrpoLLRloiM2OhpC1cTzn0VokLRmewj6Ogbpd22ARZ58Jhqgd9fA9oQU2HXVw+bNQCKFYEa0kc5+r3zw2wdEEKHMej5dSY/GmIXne3l9qE9f2iFiB/KAsGWglM4H3oskGYUbog7kB+Ms8F2Nr1WJzlQCUlM2Eh9oNgdlGBV5VwUhICos3EJ0nsA66WBhCMGkiEFr716mp55jvZ6+/5XeAZLJpFlZWVkmTfDO0Nvbu19/gJF6o78bcF2X888/vxfo/XNsD+DUU0/tfvDBB3e0t7cbc+bMOfz888/vnj59+iGb4z8FixYtSpYzpB+p7/dIyxd/hq2trebZZ589tbe31/jWt741rFVgcXX2UMP4b3zjG3Wf/OQnJz7++ONv/+Y3v4n+4Q9/iP/gBz/Y9PTTT8cL2+7r65Pz5s2bu3z58t7R9mkonnnmmdiTTz5ZtX79+o2RSETv3r3bzOVyomBBNJJB/4MPPli9YMGC1KOPPlpbIJuvvvrq6xA8TKxZsyb24IMP7ihe57nnntvS2Ng4aves4jn+/ve/X/3BD35w1quvvrphwoQJXn67b73vfe9LZ7NZ8clPfrLppJNOmv7SSy9t3t9879ixw7z44ounPProo28uXbo0vXv3bvOEE06Y0dTU5K5YsaIHoKqqyrvlllvqv/vd77bub97GMDLGeqMfavil10WtFNm3WrHqawhPHbQP6/7v39L502dLV1WCnGdiyDx9yeWQFQnMyjjUTIUjzhu2OcdTGFLi+QpXKUDjKU1Hf5awXUT2zMEUdtpLD5h+lyBSCZFaiI6DeD06EgqqxD0/0FQmwgNp/xeyG/hZ+kV6VWrYMN7EGvzxFfubqWHQZhDVtSL5/TbkgJ+nEALhpXHi44nMacHIp/PNiija90EKjHEWVl07iRYbo0xKOCh00Rj5yKEhTaJWBQmrGnxQhsbLEMg7PTAwkLEYjtK83ePhuKXlXboiFqTRlUI4btC+0vPB8ZFZF5nKoivC5LQ3eDxqCNk0QgHJD1eC9gOJqvIC2YNVGjEeCSEZ2CAZIvC7lHI4QVNFIc1kzqM347Cvz8U2JSHLQGtBOueSzHo4rk84ZAysEygyBgSSaNNE52UaBcP1ocHNxrBBrW2XLYgzhCAiDBytsKUsKUwyhUHEEDgaPD1MZXLAMIVA4FLttxFmxK6HfxPo7Ow0Jk+efPgrr7wSAjj11FOn3HHHHeMgiMKsXLmyee7cuXOOPvromW1tbSbAhg0bQsuWLZtx2GGHzVm4cOGsdevWhQHOPPPMyZdddlnzkiVLZv6///f/mr/97W/XrlixogWgra3N/OAHPzjt8MMPn3P44YfPeeqpp2IQRH/OPvvsyYsXL57V3Nw875Zbbhlf2Ld/+7d/q505c+bcWbNmzV2+fPmU0cYpRkNDg9/S0pLbuXOntb9tL1++fMp73vOemZMmTTq8cNzF2Lx5s71w4cJZc+fOnTN37tw5Tz/9dAxg+fLlU374wx8OVOiddtppUx5++OHKoeu/m2hqavLuueeebffdd9/4EunTAeC6667bt3379tDPfvazxCc/+cmWf/3Xf90RCoVKvnAVFRVq3rx56c2bN4/eFm4IWltbrZqaGi8SiWiAxsZGb/Lkyfsl/Y8++mjN7bffvrO9vd16++23D1kr12KsXLmye9myZb0/+MEPhkVfwuGw/u53v7urra3NLtd7fOh833HHHeM/+tGPdi5dujQNwXF+9atf3fWtb32robDOueee2/nEE0/U7Nmz5+CiJ2MowRjZPNRQXmkKPZVBuy7CLCV3RiKKUREvec31ZWkGXuWthzb8dERD83TOw5AC11f4+Whmf9rB9wMSCgRBqSLfxqyXLU82DQvqZkLN5CCyZkXQEROZ8waKdLTv8bvkOpZbR5LWOZ5Krz2Y2RkVfUlFh4wOpO2HQmuNb8WHvW41ViOmVyLsKCEMhFW+Q48GFGrYsRvSRCiBFhoqHDAUeJJCaqc75ZJyfHwzXhK11rEwfuM4ZH8akcnhTWkCaaAr46iIjXQVXtRmn9OHV3AAGCCb+Q9ZCBg3A2qmgWEhlML0cgHZNO1gWTdb6j80BFHDRhKQzXIp7YGDz0e9M44iYguUJ7Ftg1zGYO8egSmNgeIy2zDyRWaFAqFi/yETz1eExKCnpa9K9y9hSmxGvjaHpYGrNVaZRHeVKelxFA22JG68s0S4ISFl1vNC5Qo6xfj9r/BXglwuJ2fPnj238PP973+/ura21v/Wt76146KLLpryve99r7qnp8e87rrrOgAymYw86qij0hs3btz03ve+t/+GG26YAHDZZZdNuvPOO3ds2LBh02233bbrqquuGnC+f/PNN8MvvPDClu9///u7ird9xRVXTPz0pz+957XXXtv005/+9M0rr7xycuG9rVu3hp977rktL7300qbbb799Qi6XE2vWrAnffvvtjc8999yWzZs3b7z77rt37G+cAt544w07l8vJJUuWZPa3zqZNmyLPPPPMGy+++OLrt91224Rt27aVXEAmTJjgPf/881s2bty46T//8z/f+tSnPtUCsHLlyn33339/LQSEfe3atfFzzjlnxChuoQ/87Nmz515//fUDZOSuu+6qL7y+ZMmSmeWWnz179twNGzaUJXxz5851lFK0trYeVKbRMAzuvPPO7RdccMG0qVOnZk866aRhPb/b29uNdevWxY444ojMwezT8uXL+9ra2uzJkycffsEFF7T813/91/AL7xBs3brV6ujosN7//venTzvttO4HHnigTE/e4Tj22GNnFvbny1/+8gF9WY888sj066+/XrZHsGmazJkzJ/3aa6+Vfb94vjdt2hRZtGhRiXh+6dKl6a1btw6sG4/H/XPPPbfj61//ev2B7NsYymMsjX6ooXyKGYm7r7wEq+K9Rwx7TevAsLoAoTWG9NDrH0VUT4Zo6Xd3a1sPqZyHaUgitolpSJRSZBw/SKE76YCoSFliAJ/xMkTMkXuzDyBSjQp3YHR6qOog+LDXaecpdwMnRxdzafh91IUb9jPIgaOvV5M14lTUlX8I12i0HF52orXCNMOYwkBaNegRIoI67+FjiCFkExPhC7SElJtG+JK4P3id2tufI1k9h76qSkz9BkqpgIgKgT+xAaOzFzSo6gTe4VMDD02rG3o83KhJVEK708N4uwIblffXLHrOE2bexb4W9r2O2TwHYvlrbqIR9m4CO1JWRgFgS2vA59TXUM4evVBb5imFr1S+y6ZB87gETq9NLptB+YExO4BtSnJeQJA9pUpHtCw816Oy6BB8v5wnqxipng1bCFw0lhi6jiZhGdSFNONCxoh2TPuDQV4bqgW8q8rNPy9GSqOffvrpfY888kj15z73uUlr164d0ClKKbnsssu6AC699NLOM844Y3pvb69ct25d/Oyzz55WWM5xnIFJOuOMM7pNc/it4YUXXqh44403Bi4cyWTS6O7ulgD/+I//2BOJRHQkEvFqamrcXbt2mU8++WTFqaee2l1IkdbX1/v7G+dnP/tZ9fTp0xPbtm0L33HHHdui0aje3zonnXRSTzwe1/F43Dv66KP7nn/++djixYsHCITjOOLjH//4pI0bN0aklGzfvj0EcMoppySvvfbaSa2trebDDz9cfcopp3Rb1sjBuEOVRi+HYRr6A8QxxxyTmTFjRmbVqlUl2tY1a9bE58yZM1dKqa+55pr2RYsWZX/+859bB7pPlZWV6rXXXtv43//934n/+Z//SVx00UXTvvSlL+26+uqrO0da54EHHqg57bTTugEuvPDCro9//OOT//mf/3nYvAzFgaTRh2J/83Wg72utEULsd/JvuOGGvQsWLJj7xS9+8S9isP+3gDGyeahRVOmtHJfMlu0YVYmSRYK0ryy1DILSVn3aD0zW7Th64WWIxgXDNtWdyiEFxMLWQCVxKuuScdzgbycJdTMg3jBQZOIrH095GCN0OCpBqAIdNYPUqW2C1tTLSj7X8iksBGbHm1Cuwly5QL514wg94suhaZKF51olusiSYRWIMvvtax9bhmiKzWWvbEZRvqagQOSNIQRHCgPhC5SpEZhYpsRUg4S3L+NiRytJ+iYZFzqSSSZUxLDzvczduVMRbhDRVvF8VXo6ihofxVUuESxCwiTl53B8hxCDFdhBsVD+90gNVDZh1c0ZbAdaNREyvZDtHnHeTCGx85FrVeJTlD9uBeQT2hk3H2EVAcnuzXjIbBghIJsR2FYwR7GwSW86qCPwiwzYNZCVBoavCBV9tOXiqb4uLkkahKcU/ekYnlLY1pCdFQJbCGbE/7RLkxACU8DE7CuE9CguCH8j8H2fLVu2hEOhkOro6DCnTZtWNuUphMD3fRKJhDeS9jMej5cNj2utWbNmzaZ4PD7sQy1O3xqGged5YqQb+WjjFDSbzzzzTOzMM8+ccfrpp/e2tLR4o60z9Do69O+vfOUr9ePHj3dXr179tlKKSCSysPDeOeec03nPPffUrF69uubee+/dVu64321s3LjRNgyDQgHKwUJKydDiooMhuiPBNM2BFqPz58/PPPTQQ7Wjkc3Vq1fXdHR0WD/5yU9qAPbu3WutX78+NG/evEOuY3n55ZejCxcuHG7nAXiex+bNm6Pz588fpoGF0vmeM2dO5qWXXorltckAvPDCC9F58+aVjD1u3Dj/9NNP77r99tv/dtIkf2aMpdEPNZQ3kPL0uvuCJ6chF4Lkmk3s/vZ/oLKl30FVFIWpdP7IbHU7tu5DTTl+GGlT+bRlPGKXXFyV1qRzHnahOMeOlxjMe8obdjEeEVYIHY3iNVagqqJBpboVJWJXYJrxvFXS8MpnMj2Q6SqqyC6PZL+Pkxu8rwkhsOyR901r0MMiYaDwsYSNadhIGQoIV7n1VVCdLIakdw0d9JLXQmEKm+pIJdVGDY6nyDgenlKETElf1mVPn6KtJ0VnarAtpw7buLFQ6dO0EZBzTytiRpimUDVVZhxLGOzN9dCd7QbEYFU6oE0bEvWYxTIAMwzjpo0anKs0I0wIBdIzXw3vClSoJpdC4HgaQ0qE1BjaojvlkstKpKlJ9QuUayEFhO3BCI+nFI7r0ZfK4ufbhMKgXhPKZ/m1Gr7bWkNHX47WjhoyPU3YQwu5tOZQ1ZCbEraHj2CfaDwk4/1fxs0331w/c+bM7AMPPPDWxz/+8cm5XE4AKKW47777qgHuv//+2sWLF/fX1NSo5uZm5957760uLFNO3zYUS5cu7bv11lsHbra//e1vR13nQx/6UN8TTzxR097ebgAUNG8HMs4JJ5yQOuOMMzpvvfXW+v2t88tf/rIqnU6L9vZ248UXX0wsXbq0REje29trNDY2uvm0c63vD16zrrzyyo677767HmDRokXZ/c3BoUZbW5u5cuXKSZdccsle+Q6cF94tvPLKK6H169cPPHGvW7cu0tzc7Iy2fDqdNvbu3ftqa2vr+tbW1vWrVq1qf/DBBw8olX4wuP/++6uef/75yksvvXSYtiyXy4lVq1Y1NzY2OgUJRjGGzvd111237z//8z9rC+dTe3u78aUvfanpxhtvHEZUb7zxxj0PPPBAne/7fzupkj8jxiKbhxpFmk2vsxdRJi1jViWIzpuGDJemiwvn8LjMM9jubvrUDFy7tuyNfCRCFQsNRjkRDOufXtZjczREq/HrVL5oxuPVUAa/bx1HVhwZ6AqTeyE0RM4j7cCM3BkmIRqA1ppdbzvEKgwmTrbp3Ofh5BSNzSNEoXTQhlGUiZQq7WPJgFALJGqEpIgOFhjUshZ2VxkgNEr7SGHSmJhAJuny4ludVEXzxUSGJJd2QJvEw4KsW0qy25JtVIeridtxenO9eL5DrTBQWlFvVzLOTjARcEWE9bEq+rxMQNaLWlYqrbClPdwpwAiVCxAOwJImDXmyqXTQUWf4gYMhBTnPJ2wGxT9SSXKOJqYEIVugfUmNVcPEiT6eP9gR3VcarcA0Jb7SmOEQEl0SgC53PuohafSca/DS280kIh2Mr+wkZzoDtkcDOISXcUOIUeftT0U8HvcOpIL8YMbb3zIFzWbh7+OPP773yiuv7HjooYfGrV27dlN1dbX68Y9/3H/DDTc0futb32qLRCJqw4YNkcMOO6whkUj4P/nJT94C+NGPfvTWypUrJ916662NnueJ008/vevoo48ednMuxve+972dl112WcvMmTPn+r4vlixZ0n/MMcfsGGn5RYsWZa+77rrdy5Ytmy2l1Icffnh69erV2w50nJtuuql90aJFc2+55Zbdo61z5JFHpj7wgQ/MaGtrsz/zmc/snjx5srt58+aBC8m1116798wzz5z22GOPVS9durQ/EokMPOFOnDjRmzZtWvbUU099x2asd911V/0jjzxSW/j78ccf3wqD+sjC69dff/3uSy65pLvwGRaseD760Y923nTTTftNNx8KjLRPQ5fr6+szrr766pa+vj7DMAw9efLk3AMPPLB9pHEfeOCB2pNPPrlknI997GPd55133tTbbrtt92j7dOyxx84sEO05c+akf/rTn24bukxhjjOZjJw5c2bmySef3FyoRAdYsWLFVNu2leM4ctmyZX2//OUvB6K6o833pEmT3HvvvfftK664YnJ/f7/R1tZmf+c739l2yimnDLt5NTY2eieddFL3D37wgzHt5juAeKdakf8LWLRokV6zZs1fejdKsW8LbHseKibQv2YDfjKLES2rUx6Gjv4IXckIs5w7cdwobZGzUE2Tmb3Awh4iY3Q9xctv76MiOkqKMNMFLceUdDPqznazoXMDlaEDLLrMpWHfpqBgqHoqP+x6Ale7XNJ8SdBucd/mgS43QBDpdNPQMA/a1wfbLkMQtdbksppsRtHfq/B9jdYwZcYIek3fo7WzD3fcwHUST3sYwiDt9dEUnUGFXcO+ZD8ZcyNNFeOwjdK5ybk+r7btZn7tQsyi97yUx44db5CVWSYkxjOnfiJ9PVnekkFVtkBQEbXY1ZWm328nzdvEzVrmTgjuLzkvR5/bR8SIEDWj9Dq9qN42apSiV2gWxCdRYUWCsF6mG2/Ksfxuz++p7GlDxMYF3Zvy49iGzfy6+aUHrxS89auA1I8if9Bas3F3H2HTKIle+x70ddgYtiKV8whbAkNKYlQSrnZoMGpoTe1BCklTvI65hyuU0mzc1YVSmp3daVIZD9MIDN1NpTDf2kFzVSAZSOY8mioj1MRLP7vW7gRZ18Q2Fa/vrmNiTQ/bO6qAfTRWZYlELMJDjiedM5lS141tHlxlbjlsS3nsziRJ9Xfz4ctuxJow4YDXFUKs1VovKn7tlVde2bZgwYKOP3nH/oz4W/cE/PSnPz0hHo/75TSTB4L+/n45d+7cuS+//PKm2traMmmaMfw94Wtf+1rdfffdV/fCCy9srqurGzsfDhKvvPLKuAULFkwu997/nbj93wo8Z4AQqKxTYr5dgPbKBzB8LRESdiSuoM04LWhHaFllI3VKj55szLo+nq9L0rTwDiKbdgSqJkHtdIhUcP6E87lgwgX5N4emQPPdhww7mINIdUBIy0AIQTgiicUNshlFda05ItEE0NrHH3IsPc4ekm4vaIEtg3UNIXEcyd5U17BjLVRMG0PG0Y6PJS0U3sAxuUpjS0HOV8RCwWfYUBmmJhYiZlWS8wclED25HkIyjFKKpJukKd5EVayOTrcfT/uE8p2b0D4YNqZpEzEi+KFYYHuUR87PURUq7ZUOBPrNigngDLeZKoanNL4arlnz3MCDVQKWoci6OSJmEEHNpIL3DCmDJgKBkxNSCsZXRujqz5JzFVLm20AqMGwL07IgF2TVBAK/TAixuOFVdyrCzs4qZjbuIWwnybiCV7dNYvPuIU41YuCfPxmGhLC0qDGj+194DH93eOyxxxIzZ848bOXKlXvHiOYYAD7/+c/v27Jly8YxonnoMZZGP9Twc0HRBwTG4xVDuut4Hq23PkDl8f9A4ujSCJbhdmLpCrQOo6VJeNIEUmk54GlYMk5xC8Ey2NmVpkY6VGKgPIVtBiQq5+VKbWz2ByHoDhn8tuc5llYtpdKqxCp0uBmqMXIygRF5PF+hHq2DTPnCln3tLvEKg0hUMn1OaFQdqVYK7To4ZkXJCWti4WsXKewBsmlKC+1GCPm1pJwOqsKD5M3TPqawhqXilaswTRPlKZTOk01fITSMTwzKyUxDErfi5FSClNMVGI9rRcyM0dln0et2Mqk2RlO8id25frq8DUSsGFah+t33Ia/HjFkx+mPjMa1gvzNuBl/71EZqKYtINfTuLP9eHjlPDftklQfpPgPDCs4hTwWWWKY0MKUik5ZE6qElUoPn+ygn34FTQmU0RF1lhPb+HixDYJsGrvCprYwiJ9XD1u0Qsn2Gs+MAACAASURBVJECfH/42Vhc8PaeaTtQWuDldbMZxyTrmsxuLG1eIrQYzeXpoGAACEFEvit2f38V+FuOagJ885vfLFsEciBYvnx5//Lly9cXv1bcsaeAiRMn5gpm5u8m/hLbbm9vN4477rhZQ1//1a9+tbmhoWGMcI3hkGGMbB5qeDkQEu354KthnWy00lQcuxB74nDZR3X6WRq8Vt4S1yBDdnDHF4wc2RyBnymlybkeImLwSmsfhpQcMTEgXRkvU95jcxQ81fEUr6de59W+V3lv9Xt5X837gjeKSZvWQeSu4A8JJUbyxfA8zd72ILobiQ6vygcg1xfkf6M1ZPb2Y8U1rlVZcsIKIfG0S43dgMwfk2VI6uyZxCxFVpRmPD3fw5TDo6fKU5iGjfACbSJa05txscvIH2JWJREzwb7M70k5aSzDJGYn6FQWyVwbYVlH2AyTiNUTqWqhPpsZtO/RPpjBw0fcjtOV7SJCQD4d5TClcgqxEWyblLbAEyOmIrTWdCdzwwr5B6KaBQ95EaTQpZSYBlhhhRAaSxpYhkEqTzYtC0KWQWNNjDVvd2IbFnVVMXylCNsmlMyNKFuNHrTIHGy9agiN4wVaTykzLJv59rDPXjP6Q9TBwJCHjriO4e8DxR17/h623dDQ4P+5OlKN4e8bY2n0Qw0/B9JAZZ2yN01pW1QsPYJQ83Cyucc6kS7rPWhPISODpEiXuZMrPXLtg+srfDdHzojRm/ZKvAozfmaY9c9ocJTDm+k3Oa7mOA5PHI6niyUARaePmwmib8WV1IYZEFLfBc8NwmyAaQpmzwtTU1dEHZUP/XsCGYKTBgwwQmjPxc86KBFCDY1QCUHEiFMXGdTimVKS9XxMaSORJRXijvKw5PACWuVpDMPAkAZKSxxfkXMV9ggWTFJIEkYNSTdNzs9hiQgGBkp4oIPPLRqupKF+AVMrWoJjgsFWlUDUiqK0wk9rtBfs42jep16Xwu0ZWWaQdRXdGTdoN1kEX5UW6UgRmLcX9y0voXf5VPrg8kFafnx1DMuUAdEE/j97bx5sSZqed/2+JTPPete6tVd1Vy/TPYtmWjMjjSQMM6HxGIyFRMggsGWsEAgFSJYDHICtMEEEAQTGfwEBgS2DQyiCxZZlZCFLhDbLY0szEuNZNEtrprfq2qvuerbcvo0/vrz33HPvqaqWXN0t4XwiKqrqnDyZX+Y5954n3/d9nodjPoxCzN0RFhDisSdFymsPNqitwh2zZpqUSfP4iRuy8GTa6DFk9YnCe+9bJWqLFi1anEDzu/Ghw/ZtZfNJw9YgFNXNu4gl6Se+qhFSIpLTl76Q56g7W5DPkIeVo3AYF7iI8LCZzXKMK0uELdnjCtY77DH2cChCeRR26h1ccJzLzpHKlB9/5sfxeJRQi/Y+h2QshEgW+0ssyIbnYXwbEGADB3mPwVChT/or2gq6a1CNIFuJ+7I5Yf8evqpw6RU4MeoqkXT1gEzNq4FKQGU8IQh6SfS5PDxf6y2JOEHYfAAXkKlGCoVzYFwkROFhsnbgbOcaWr1B5WYMk3WkGCORyEOyqXtcW70GxsD+dWAQybaKhDKVKcFI8nsQNkqKrCB5VLs3SQmP4DnTyjRm7ie8W+2Jh4Sgn3YWFO/hWPQ5AUwN9A83lyTqGMk8Wo8+eo1gOdl0QaBEYFpl3Nxd48rGqJmbjf6bRa24ubvG1nBGqp98pKSUy8Iy/6nwle3t7fdtbW2NpJRtzbRFixYtiERze3t7FfjKw7ZpyeaThqtBSuz+FNk93Yad/ObvMPnsl7n0F39g3mL3FcM3/irdzp/Ddp6OCTVZJEgBiDcM8bvN+UBRWXwIp1uEPoAt8aZCCU8hB0gklZunJdS+pqMfrY7/jf3f4IuTL/LxjY/zYv9FzmfnUY035amWt1DxnHUaxUQnl9Q9g8yGYAqmt25w+4Zh60zF2bMekka4IWRsma9dhrwL61ejwMjW+GmO9yVGnN63FIorvecXH1OSi6tdKudZkSm5yTm01XTeo+Ui0T4klFLIpuIrqGw0iAxL5hBPnDyr2Sqp7KFEQU/3MfbEj1Q2jKbsgVgCTOLxE5ng9iXKQ5FXJL3k0eMNSoHoEEyFSE5XOPPaRbX4CXgnFlvrAYZuSlACr7LDh46QZnDvrmAwDGgdW9FaS5QU0WigkmQ9D1odj0tfKhAiCASeC2sTzq/G2cxJGVBC4HxgkM34+Iuvn/YFfUKVzSfdtrHW/tC9e/f+53v37n3gbdh9ixYtWvxhhQe+Yq39oYdt0JLNJ42mjR6qCpGdriB2nruM7HcWZjmFneKSLTicwxQCoeLzgibBBXj55h4XN/rcH+UMOimnmoRmCiuXqIubSOEY+ZR+pqhN3IELjkB4rKn7Jzc/yfnsPL89+m0EgvPZIyIppYqRmGtPcZI1jB+Mufnlmzz3bc+RpX0GPcsLz9TINInekeUBiASSFN8ZsI9nc/PafAc6xQ8uEPoeZxwsy9peYqukpaAoHZnKmJpol2a9xftAdqJ6GJoqpkTFJCEhKeo4ehDso+13rq08x2a/x87Yo2XCcyvfBE5zY3fG5fUeUoqYSa/S+bVpjq+lJpSCkFmSukumLVo84sfReUJnnVC+sZRslsajlrT9vRMchriEEJDBEvQAaQ9dAhavaZLAdCrY34Ots/Gzcma1hxCCslCMHqSsbtVkfRBaI5xDIJZW35vgImB++raJylRSUlhLv3P6nJ9UyVCKJxtU+ZGPfOQB8N1PcJctWrRo8c8E2rvzJw0X2+i+NrEadQLZlfMMv/UDx7YvQCgml/99JupYla557eHIY2ksRW2ZVZZpYdiblKcrm87AYIsKhUwypkbQSRWB0GRiu7ekRB/oAR9b+xg/9tSP8fGNjz96YyHjUGlyuvLYXemyfmkdIQVV5SHpo4dryPWrsPEsrF+L3pHVmDLtY709lWnrSotMMly9xLIphKU54EIKPAElNM47vPfsT0b4SpGciNcMLg6/SiFQQiGQTMqYN+8fU9lMZZ+O7lBaj5aSjs4ojefuqDzKFUelMcHpcJmNyb70ErzES0uXHh3ReXQb3QeCzGBJ1c/7QGUXyab3Aeeif+khHw8EtLcUg6tMNj6IsgXLAiXTBPLGZcmF+c2JrQTOwv69lPGOhvUVKKoY07nM1D3ET9ur9ze4N4rG/4fWTFoKitpTGs1vvvIU2+P5KEQgtvZv7q0wLX//UZPtL7cWLVq0+IOBtrL5pGFrggKW+B2GELC7I/T6ylHlMpl+jc7OL3Bw6ceAebKXaKyKDr0PZ4VhVhqmRY2xntp6aus4Zc2uMvYGL5L3NE9151/gzgdssI8lm1+efBktNO8dvPetna+M2emHyvMQAuWkJB/llJOSCy9eIPjAa//kOpuX1ti8diw6MNmKbeYko1Ypfd3BB78gYHJ5iUx0zJM/fi0Jce7wEVVaJRI8ntrV9PY36LoV/AmFua99rCQLiURGgZFxrKQaHkM2bVNyroxDNUKaw/zx2vmoM1dJFAXZummjx9EBaz1aaWpXsJZ0eH7lOU7G1X393phUK66d6RNcQCgNS+Y2D+2EDhmtD4HSGJwNVFaQNtGTIUQ1ukuG2HRIEDKS2BOnqRPIm2Tgw1lMawRlrkg7DqmgmCQMzpwlebCH6J2e2TRORjW6gL1ZL65tdYrznkTKJunUo2RNL6vheIR2EBR1wsGsQwjQy+pTKvu3Aime+MxmixYtWrT4faC9+X+S8B6Ci76QS74c/azg/l//GWaff/noMdt7hvLMv4xTxyNkwxEZlQKsg3sHOVIKKuOwzdzm0vQglXDAAJUuGlnX1h+10R+F3zr4LT4//vxbPmWCj4SzMS4vpyXXv3Cdu797F1vFHHapJDrT9LfWT78+6cDaVYROUFJhvT22a4+ra2Sq8fWiOiiOAzxaVS+Ilc3t2Q6p7yJ9coq0uNohlEAg2OxcpJcmDDuRQD9KIKSEoGza7JXzsWXeoDCO2h5mRCYx31yImFPfVDad8WQyw/nGUP5E4dZ6z+39kjd3Z1jv41qUjsTwBDsszeLEpLWeQSdj2O0sOBEE4ryk1T1AYpMB0tenqslSgrWCqop821aSnZsZdSGjwYCIezuYrXO/uIyzmnE+5N6oH8eGnaAy8/vYb33mFs+d28UHHy27vINZbOP7EHjp6l22hvnRuxaAgzyjm1pmVcre9OGm7I+yNloywtqiRYsWLd4FtJXNJwkXLW6CsUvrhyLRrH/3v0B66SzJ+Atku79CtflHMasfwZvjvF8gDtvoAmrjyb2l30k4yGus9fQ7mu5JhTBgRIJxBf1s8blpZdHJ4yubP3jpBxltFwQfEG+lnNTdhMF87Z1Bh3PPnqO31qMzmFcRr3302kNnRUMIhBBYzVY5qOYRxb6sG2GNxFlztHYfHCaY0xnip/YrMN6wLs+w2hly78AgT9gU+4ZsAqhmZlIKGf0eXViMwTkGKQV1k49eW48+dq2M9ZTGAlkk4uvXYPcVWJ37NdeVZZgNqHxOR2V4tzj0WNT+yBtzf1qj9iu6PQ2q06ja5y33Ue4WrIy89/Q6mkR0uM8kOhcIQQg+Vlmbdr1Nhsh8/JCLB2++LumdgfwgIQ2QZPM1ph2PsxLf6VJMKyZuwMGsg/OSaaFBKBI1v9ghBOwkEkwxKyLB1QnWWATRGunC2oRUWUqjmVYZWWJJtGNv1mW9X6BOCMCnZcrOtMfTZ5bHWkv4fVVEW7Ro0aLFk0VLNp8kmvJUsMuDF2SW0v+mOJeZ3PxthC9JRp/DDD8UFeciVvNQ8kj4IiSUtQMN3TQSzKVRld6DUJT+dLUvVZIbuzlTs4/uLRe9PKgeoIRiXWyQzvr4tajheSwG88Sbm1+5SZImnH/PaUHRo0RJLji6usswHXJ/dh/jDMN0iM1LhBRxBtMdWocrxiZWyVaSh6TtHCJIfPAM3SqpSnAY9PFqpQsEE5Dd09fscL3Bh6UWVkqII5V/bTxZI3RZyTRKCCbVsUrs8Bx0VxcuaDk1DLt9MnEJZWN60dGyQ6BoKrmZlrx+f8KlUUWSKZJshWB2CD5BJpAXnts3Ye3MsXMQgjRRhFqQSI0PHuMMwltEsjI/fdVBBL+0OtjtwegAXAa21PRX/ALnFgJ0EnDnVymv56A8PsD+gaZjD0g2VpAC9mZd7h0MeWb9Lr4oQWaEhkWroqSyNclGyv6sx0a/IFWWUd6hMppuGq+BD5FYrvbm9kj3R30mZYZxEufFKSIa36O2ddOiRYsWfxDQ/i5+knAmtl+NXfoFbrb3cTs36Tz4Ocqz38306b+AWXkJaEQaIQ5oynRetTqsbB6HFOI0eXMldNeix+SJ43ZTxbSy7BclhTlNhEMI/NLuL/GTt38SUzpcCf73aHsYQjRGl+r3/pEqTMFGd4OzvbNsdjdRQmF8NHM/ypknUJgRU3OAEkk0bZePbqNLkZCSEiYa3dXRb/TYHKZ3c4Pxh57XQwTpSgpq63De45lXgaWSdFPFpDhhCnrYSm9QFw6dJAzSQTOXO1/XgwcPeLC7hxKCbqqZTg15aTHG4/wKobKYPYnzgTe2C7yViHD8uodG4CQao/p4EsaZBSFXUBmSwOlPTNSndbow3hcgHp5WpYYpbn0TbXLSpKIjC7SaVxSrWnKQd5BVCZ1O9GONEUJIKalWV1HljG9/7jrnVqcYryitZtidfwBVXTK6M4uiO8BYye60F10ERKCyyz8HQsTEpUd7CrRo0aJFi7cbbxvZFEL8TSHEAyHEV449tiGE+GUhxCvN3+vN40II8d8LIV4VQvyOEOLDb9e63la4+GXoarMoeGhw8MufZff/+kfI6g5B9Qmqj1n9lhhvGaIuOLi5xybE+bmyto/SwUTYCrqbjEuDPrGxEILNQYaQFcEvvuW79S65y/mW1W/hhy7/EJQqKuCPkc0QAg9ee8D2G9sA1EXN3a/fPWp/O+MYPxhz4cULnH12ibH7MQQfcFW9eNlwnO2eRUvN+8+8n63eFi44vDHIpqrofUCE6JM5TNbQQi+7xIvnHVL6cnjsOMAx4h6sf7zPzkPmNpWMWeRuCZPRUlCYSEQfuls/J3BCCmxlsXW8ERBCMMkrkoa4d4WgtA7rPN5qfKXxpWA2cxSVRwl5lPpz2DJXUmJrQaoU1ju0kKgA6Pn8YxC6uck5sbjyAIpdtPaMx5Ike/RFys5maExUuwcDWse55cpwVt3nY5e+QbreJ3Q7cx8vLVHBk68MoZuBjeRcEvAnKpXS1djeGqEhm6XVKBnItEOpwM7k4TOdQsDpxPgWLVq0aPFO4u1so/8k8D8AP3Xssb8E/GoI4a8IIf5S8/+/CPxx4Pnmz8eA/6n5+w8XXA0h4PPyaObyOFY/8VGCseSXz5+aA2wSpAnOIzpzsikEFLWlIx9zXxACdFcYbRtSvXzbwo/ohUWLop/f/nlGdsSff+rPE0JgNm3GAo+RTWccs4MZ3ZX42tn+jP3b++hUs3drj+GZIaMHI3qrPZLOI+x7ADOaUNzdYfDMZVQnPRKnHI9qzHQWhUK1IZc1wQVmdobwKee7T6NFwoF4gHyEQEgJQWUdzw6fZzQqo7+jEvhqXtm1M7O0RX4cDzN2l1JinI0G8CfRvLel9fTT0++F9+GIFB5ubirH9q0pF55ZRWvNrKzoiRmkK2gHNsAst3STBHKF9zCaWBQSVMCZuC/nA6mO18VUiizVTAroplm0Okr7R9zSNybyCwIhV8e5TpWRuoruCtTFY8hammDXV3EHM7QMyG43ztvWlu4LV1HDHgjJwWt3kN6DEoQ0RdSWoCSFkOzurlKT8dy53VO7t96Smx6+tiigMurIOzTTjrxK8WH5fKbiVPBUixYtWrR4h/G2kc0QwqeFEE+fePh7gE80//5fgV8nks3vAX4qxG+9zwoh1oQQF0IId9+u9b0taARCPq+iTc0JpBe3HvrSw8omzqE689k+IaB2bkFVfArju9HPMR2S1wd0tWRmxiQyIW3iEY2r8FQ4H6tAv33w20zdlD+x9Sc4MFFgESzgQDRk85AQ6VRz7SNzs/W1C2t0Bh2SLGF0f8TWtS1sbR8rKArWUW7vE3wgWAukcV5TdVHHWuId1cFZiwohqs4RECAJipU0qvZ7yfAhR4mQUjTCnRQpDXcPSjzR6ig01TWbW2Ty6Fb8oxTpAIV5OJWxy8qeAH6xLR0rmx6hIgkdVx4bJFLE/wfjkUowKWoS62HSpRKGcsWgSAg6YI0EHN6Ho2hJUwsyrVjr9OmnHVJqxmnviHwFqTlUfx/B5LD+VLzj2H4Z57O31P5wZzcQOOTBAbLbweclyeUtvvT1VTa3Ak897TFSRbKZJNHMUyvSLGE8FtRWUQa9tILvgTpJMVaQAFVT2ZwjUNYJvey0F6uSLdls0aJFi3cb77RA6NwhgQwh3BVCHPZcLwE3j213q3nsFNkUQvww8MMAV69efXtX+3tFNY0G10WJ0Iskxk1ywhu/wWD4BtXl7yMkawvP+8O4FSFOvdY4i1ySnvPV6U1e6F1ESwWbz1F6i3GefqbZK+4ySNaOyObE7iGFPLLkeVA/YN/s852b38mZ9AwAwcxTFUMALHjp8c6jjynfhRBHVc5nP/YsQgiufujx74XNS4J1SCWjEAqOxEDHkciksZECJVVM1hGSDXnmscc4hBKC2gXq3CBCiIIdEUlrebeAREQv1McR5Md4bebVcjEYoclYXwIfWDBnF1LgbEBn4Jxje2rodTroJME7B9aTaMnUB2oJWaIoZxVdMiY+jlo4F0XqPniyROEdBC+QSjBU81jQcCyu0wsNJ82wvIPeJnHCJmBd4HFFdQAhFH61R//iJocvCAHMG3GXAFWIlcYgJZw7Q9hYJZGSWRBsZW+ytrX4M3FYcXUuYBKNIWP6YELNKlLOibz3gnujAZc3RqT6GMGf3icJfZ586nqLFi1atPi94A+KQGjZN/7Sb+oQwk+EED4aQvjo1tbDK4XvOOocbv2/0FkjVObIlP0Q5eu3uPd/36AMTxH0KSt2PPNYQZI5sXO+8SY8UfJxwXNgc3aqfUj7+PWn+crOy1EMEgK5m1LY6dH2+9U2Xd2lsrH6811nv4s/c/HPLO6zWuzuuxp2b+7y9X/0dap8+Vf246IvF87RukjuBPhGqFS5is3Ooqq8q7t458ltgRZJbLFLyUA8fDbvJKQQ1JWl2ilI9gqU9ax0EoQSmMLiK/fYFjoyem2GEPjSvQq3pMq5M30IlRFgHlbZDIvCJCGi76YQgllRMfOKbidDpx2Cs2Dj+58mirH1VGlC8J5qrKMmranyGSMJARKtcG5JshIBfzwbXmo8c+JPNY6CrGwl+p8imnjJx7/HUopIro/HsAr42Hc4rj3rgUDdJAqhVSw5drKoas8SZqVrLk2Yk8zRFD+a4rsZJuswvfohbovnmR44KPKj4wQEkypjVh0b4Wj8WvVJA9MWLVq0aPGO450mm/eFEBcAmr8fNI/fAq4c2+4ycOcdXts/HbyJPkVJN6pmT5SDuu95ijPf/8cJT39qqW+jP0yGCQHZVDZ9CMzqurFEWtzeBkftLePqAPpbGG/IbYEJJdenX6N2BbmbALGFXruCRKZ8sf40n93/LHCaKPqYtBmfk+ByWD2/yta1LbLeW/FBejSCtXHHUuIP288C1ruLZu+Zznhu5RoQ6CU9EpkghCaY+vROHwIlwb0+JuxHMqgaoihTRdJPcLlDJI/++AsgOM/r+4b//SsTfvWNfOH5lY6msp7VJXOqSgiKennV82TajhAC56K10GhWortDdJKQdvs4a49ESkoKaucZO43WnlDLIxtQKcFUMbEn0RJvTwRRNhsGebyZIXCHvp0QP8PnPxgJp0pBSqx9zAhHAynAuIdUeYkpR0E1ZPPEiEnWSShsyhfePM/9keL+pIyrU5Lu+67hn7pEUI681Gy8sMWZb7qA0rIZxYBBp6af1eT1MSJtS+iskrRks0WLFi3edbzTZPPngB9o/v0DwN879vifbVTp3waM/tDNa/pjlRnnEcfJZnBk9e/QvdRbfHwBDTk41kafVRXbkzGEwzY7FK7Gh4DxLsYS2gqGFyLZNCXb5XUqX9DVA4yvsd4ws+OFStqbxY3lp2DB2saYHks1NqSdlLPPPFph/lbhjQUpEDIShRACErk0E3wtWSNVGZnKSHWKkAm+Lh8dGXMMwgWS3KJ8wAuBPPY6IQXpWsZe/fB97RWWncrzmQeGcwPNf/Tt63zqmcXKqpSSfqaXtuJVo0hfNvO5zE5psBmjGffzmm6vz/r5KyRpJ5q9H9u9llCFSDaVms9+ShUwpWiU6AJ/srIZHE5lR8d2Tfvf6m50UfA1IKAXZ2Jr6/HJCri3FhUZk64Wz/XObcFnf0Nh6uY5KeOGJ6r+otvFrw+xBqwXFFWj5DclUgtMCAQZSPomkulBB9nrHvnZCgFa+kULJFtDd71NEWrRokWLPwB4O62P/g/gM8ALQohbQoh/B/grwKeEEK8An2r+D/ALwOvAq8DfAH7k7VrX2wZvIylwp41WZHWf6nP/EHfn1Ye+3AWB8B6h43yidY5pVTKuShKlCAFKX/PFyZvcqfbJXYVCUAYH2QrGGwpTUrgpzltS2YEAtSsYmz0SGSuTLyWf4F/Z/JNL11BOZtx84xVmkzEH+zvceP0bmOr3Vxny3uNPWP94axFSRpN2Y/HBk8olkZuAM4bLw8tsdjdYz9ZZyy5B8Hj71tYTbGzdytUEj0CeIHhfH1t+4rWCmZ0TJGU9unbo0vB3b1T8j2/W/OKdmlnt2eorhBC8vPPWqqtKCurSUt+anF7bEgIqEFhTU3lJv9dF6YTECdTMkpXziqFWim6a4IVCqYBOGh8DEauHmdYIIbBGLJBEX3te/tx5Jq+OCT6w+1sP8MbjVA9jaxjfi2lHUmGc43Nv7rFTCRrDqMdCCoE5WbE9XHMCxnuCVKA1dE5UyQXI80Pef/UW3Wobax2z0mBNha9GWOuprOP6zozCOIz31EodCb3i8QPGqkWnqu46SoY2RahFixYt3mW8nWr0P/WQpz65ZNsA/OjbtZZ3BE0rMjh3ymPTyS3ufHadFR1YeeohL/exzSwHkXwdFAX7RcFKp4Mz0epmYnL2zBQXHKnUyOCpVYoXYLzBB6j9jNRH8Y4UgpkdUfkcTaweBmLuNksER0nSo7+yQpJmZJ0uiewgjIbfRwf9Xn4PLTRn+/OqaDAuWkIJga9KrLck6nRV0zvHdH8PrROkkHjPkUAqmBqS5QT1OILxiCZzCMJRR9mFwK/eN5zvSIaJ4Ld2De8ZKi73FEnt0cahXOB7NxTWeDoDzVY/Hvv22PJTXxrzH37bGmf7j/7R0VJQFTYSuJNrC4GTE8lCQl0bXGdA1ijkh/drRrsVymenbguDTBAnZkJ9cCQNeXdGHM1yjnYSdt4c0lv3CAl2anCVx4xrkmxIMb0D6z1YuQDAzqRmWjnu1IHOw1ztT0AKgT0RPnDhUuDCpUhWjY1jAmFzDdZWTr1eSEG4cgGbZnTfvMdkd8qe7mInM9LygM3BeSoveG17ykYvZXtiuFjWDPrxsx4rvALr5Fwk1FlBSvUHZjC9RYsWLf5ZRft7+EnBW2ha6KfCJBPN+T/3ffQ/8v5H7ECCMaTnolimsgYpIJEqtigt7JsZG0kfIQQ+BPpCQtptfAhzEtFlPT1/ZAuUqR67xV2sq7F3Dji4cYNPVz/N3fL+qaM76xBBcP7yFdIsi+k2K2uU9x+vyF64DN6Tm5ye7qFPEK3goiJcSEEI4KwhW5KJWeUzZgf76OSQIB9W7ySuzE9tvwydvSqmx/honXPYRr8x83zpwKIF/HvPdvnMruGro+ZGARA+Hu1yR/JMR3L2mEBmtSP55LUe/cfMekKsbBrrCPb0tXuY17upLSu7jtTETHaReyrrseG0CMmrNPbjm90Hb9F2ht1PCdYexZ8CSBnoD0vOvl8xsX/hjwAAIABJREFUfG6VZCXl/HdeINvsoDoDCmOiSn3rRYxzvLE9ZaOXUHqNfpxzfoMo9A+4h5DT0nqklHB2Iw7Unrpektdfybjx4AJcOUdHCtzz38odzpAna6hg6CYKQuCgMKhEk5+aiQ1YL5uUIg1JDyXiTVmLFi1atHj30JLNJwXviDLrxTa6rO7Sv/03STtT1ODhamrnIkU93Cava7pJihAiVqMMjGxBV6as6B593SFFgEyoXc1BdQAhIZGaTDYG6Sbgv7GH3y9iRdF5BIGqiCQwH+XUZWwLP3jlAbu78zHZ7hgGBvDgird+Gfarfab1lFSmC96ZwQfCMauhYD3F7Qdk+jTZtFWFTlOkPjQdj48LnWBm48euQTiPqhwyROIYmBebrw0U//GLPd63qtFS8KPPdflj52M1UITAzcLztw48YxvwSqBNQDYVu0Eq+aPP9JYatZ9ehEAEIuE82TYPh6ta2BxbW/oFqNJGhuxA6xRPtG86Di8zRPBHFkq+zumtrKOMI5nu4l3jbhBguG658tQ2QXfmx2sIn1cdQhDUQVHUls+/eYDxgUQpVgd9Or/Hocfjp/qPf13zxmvxOJV1j5yf1FJQe4uQHr3SwbzvvbhzVwgXPoxcu4xqUga6iWJaGpJhD68UbjzFTXNCZQjWYawEW0BvHRB0E82gddps0aJFi3cVLdl8UjgUCC2xu5neTZh97dF6J+8CMtNRqR0CPoQjFbAUUNuAxS4QuPikJLc5UzPFe4k8NqAmlCT0Fa4jUOeG9AZrfPzGH0HuOu6+co8bX7rBjS/eoC5ryllFr9f4XQbQtUDXDTF8a2N7VLZCS02iYua3EiomAcGpcp6QAlOUpOJ0G70qcpSeV0UPs7uFTvDVokjIjA+oD3bxZj7LKWwAF6hTSTi8lg8RFq2l8qhyGZxn28PvlIFUAlIgnScZL1YWX9ur+d23MLspAWfDKVFTzGRf4kjgPCooVOEQPsaAbvYvoYLkpDtYkEmsfgYP3uKkxm59gNGZlzAiJdh409Mbp/RGKXhBbzr/cQ8+cO9XbzN5dYZTGa+8mvCN1w+orWetmzbHUI/Njj8OwVxp7z0MVgJZE3VprH+kql0rwZkrJdmFEYnLKfsXj55zyRARAtIWSCnYGmZoraieukT3PU8h+11EliBEoNjJsXsH0DtDMIYk7XJOtZXNFi1atHg38U6buv//F41JZTBuoWblswvsXb+A3b9O95sfHvnuao/qxYqkP9H2kxIqE6B7+nVCaLbzbUIIGA+JWCSb4vIQ5wp+Yfa/8cHsWznjujAtGO1brn30GgRIOylX3/cURWM2dSSm8ZCa6IjzOHjvmZopL2y8wI3xDTq6w5nuGb5x8A3WsrU4p3hcVT3owahYSjbrE2Tz8HIIIARP8I7bs8B6KnAPbhHqinRji+75aCwvXSSYXkpcCJgAsqkA/v07FRup5NvPxONWLvAPtw3XpxZc4Ee2FP/ZikA119FqSXqCbP/My1PODzQvnnnM7KjzVNactNXEh9MisrIu0KKL0ilJYal9IJiATjQuTahP8D6vNEEmKDdDhBl5do5MZgShyDtXEPUYnXappoqvvJlx7eqQlTMyjgnIOMqQbXZQmURnA27dS3H725z9jnPz6y50M0y8nBwvg/WeDIWU8NKH5xeutoHeYyrCmZasZwnGZdTd+TpMtsF440Os7H4Rrw9nNAVWSNSwT2/YB0BWoNwm4ZXbmN0JjCN5b9GiRYsW7y5asvmkYKvoT+j9SX0Qm3/yk/jZo3vR3jrSRuzg/WKqi5BgStdEWi4iSzrslrtIFNZ60ix+uVa3dkjOrtJPV0l1l67rUyWG7nufp3Cey1sDsu6c6B063wAIDxDDpjsVzN4C2cxtzuXBZS70L3B/dp+O6jBIBjTOigQfTl0XhEAtESrZukYdEwEdhis1LyI4x/1p4NMPCr6r79GDVexsStOnR1QutnNlIASwwR8dZWQCSszJfCLhMzuGiwlcTSBTgnCMWAVAnBC+/OBLq6x2Ht8U6ErFaGLYOtFGDy6cskvy3qPoIzONqj2yclFR31FIpQni5CSwoOqeJR8Isvw6XnUQMroWFJ2L9GYz0iqjTAMXNiyrvRrpJdp4TPMZWX8pzgfb8hJnPjRm3N9EHbPm8jLBqxRlZ7hk8NjzDSy20Q/hvI+xo4/hq3UhefMrKwi1xtmLixubbA2TrSFdGc81hkHhgkeJuOYkgcL1Wcs0cm0TvXUe+/rBY9fdokWLFi3eXrRk80nBVSBU4/03/8ZNd/8BqrpDcfH7H/ly72EmPKl3TG2xmJ0NWELDuhaRqS5CKZyTwAyBwHmH2YvRmenFDXbsXb6z973I5kuZyi7sKviAmc4N3bUBhMBpkC7GWD4O1tsjc/a+7pPpbFFp7v3Slqw+QTZDCDhrSDrz+cLgF9XbwVqmtUCGSMCFlARv8XWFzLrIyuKEaCqh4HxAAcJ7/vRTnYXjieD5gacztnLDZQHVSXvKxs7qOA7V6Y9DKgS1iXnlx6npMoGQCOBqiV6RBECN66YiKlAywfgaKZYcVyTkK0/jrEUIGVvJrNGVK0BO0sm4umUBifXy1OwnQN3ZQna2WAOqvQpXWHqX+njdI195lsHB148MkELzMXzY/OVhfOfO7Yzrr0v++U9Y3GnJ3FIkmefi5QeIixeXTFkK6myD3uwGXnWOrpkP87VIGUchbLZK7+wF5NpavEF7K3mbLVq0aNHibUP7W/hJwdbRH3M8i3F8DYrdhJ0vCHzx6IRmEwQ7dc7d4oCvTm6fet6HQPBLvrKFJFUpZd2Y/ITA5Hff4HdXvsboTMFt+zq/nv89HrjbJ/Y3/7cr4p8mKpu0ELjDJCEB1POc6odCQKchAWf7ZxkkgyM1eghhqbckIXDSmMYvSaE5/spbpeb//HrJS+czvntrgkrmhNbmOfiAqj2HYmznPdY14U71aZZXH9zlaW24qAVVR51uFx9aTR5bv3GBT79Z8Pr+chYujScdVSSFxQsoKzuPhKQhz8cOExohEzZmmQclkJP5TKgSeun1N77GmBIv0ljRFRKZSvSbU5zewHtDXki8cECGDKdcuRbgKsfe57Yp7uT4pprrdBSs1aXg9mtd/uqrGf/PjjrKO19AgO1Jyc29gl4vsHkmoDXUzr8lL34VKvrnU+z6paXPe91DHLuOq7MMf6JhIKmZJFdQm5vIwSD+zCwj6S1atGjR4h1DSzafFJo2ut0bIbN5C7gYb7D/O9VSu5fjqAgUwXN3dsA4LzHNt7kNjlvVLpWvUUsK0dszg3WBSWXQUoDzJD5h0N0kKBj7A87rq+hjrxWIhdzu4CLHEqIhI4E5GRLxeV8+fO3OOySSropjAKvZKh3dQQpJR3VwwS2QLYizlwhxNEt5iGVk07i5envkU66PHKocY4sZNNVTqTPMbISqXSy9CUDCrHZY7wlS8Mvbhr99Y34iwXtcMUFV9Unby2MLBXxUtx/6WioJv/J6ziu7y0VCqnJkexXSBYIQ5JXlzssvU96PSnrvF7PuffAgFLIY453DJxJ5YDBN0o6WKX6JSqtyJdaVGFMgRTRzl1rQnVoCCRPT5WuvdtmfAaQEBGIZ6T9cd6Y4/6lLbHz0DMEHqp0S11hTfeF+wt79jDM6cM5Ibnx1eIpAaiWpncd5z+ZZxwdfimsujXtLI5/KFuTJOabXZ5jJaSJ/PNddOoF2CnNixKGT1Ew6l8n1GtNcIHTa3EW1aNGiRYt3Cy3ZfFKwFQGBG00RaSRAwuUMPvw8l/6TP4tMTwthjqNuMtFHVYG1ntrFRmLpDSNbMLElOhz70my+6fdLz/03txl/6U2080x3HpC9cJEXz32MrujzufIf8FTyHs7oC0cvFRLsMbLpa44+CUfzmvOtUYCdPnztUzPl6ZWno4/iCWx0N8hNvuAJCVDYgo1s4xQJ9c5yst9eWXuksv/gRuBHtm5g77zBX7u9ya/tNC3VJMEXM2Ru8ALseBvhPaVxGOcJQtAJcSbz6BLaCu9qktLgD2covcObY1VoIQg+0N0uSEeRAEkh+PE/ss6/+FwUpuipQefx/aoqTzkxuI7CdRRCwHR/RLUzpd6eNnGmi/OLwXt8EOjZCGsrgoCZ84hOrMgdrxAfvSYEEpWiZQLBo5NICrX1GOf56qwk7XV45uKEYbdGhIwgeCTZjKcbIy+D9ex89gHVCG7uPMWVlX1+7mzODz5d854UEAFnG7cEVyFdRZ+CLZ1THmjG0zk5nlUW/ZibrUNY2Wf0lX3qg4d4i0IcJ/aCxKujtv3R+oMlO3+Bmzcdt28YjF6Dreff0rFbtGjRosXbg5ZsPinYMhp4B47yz7Ptn6d3639Zmp19HN55KhFwyjOra5SUSC2ogiH3NSZYSm9IFsimZ1Zp6rzGpykkmqI4oNjZ5dXJ5wEYyjU+2ftenk5eXDieFOAqT7odFbzeNG3mspnXPEH2lAT7CC/1EALDbLj0uYv9i3g87oRKH2CQ9vHWYus5sYiVzcUt88qhmmsohCRdWSddWeNsF947jAQwJssHqCuCD3hvwBmcD/QzTZCCPzYQ/KsX5tWx4AzCC0Rt8BLwjnr0ADvdO9pGSIGREtfVkVA2BvfdxthdGk9nvyQdxXP46S+PeXm7JjTkSklBdX+CKAOzB3tUd8eEUXXUrq9NhTGG+w9meFtiywJvfXOuotmHxgdH1bwJIQSsr8lkh1R2SJIe3e5a3NZ4/k4+4xtYQqfP1kpBKi3IDC/FW5qdBJCpYvDcCja37N+QrFUJP/5szEnvbhjS52foJHqnqnqC8JaDgzGlXGP3+gpf/1r8rLrgmZaW9HFk85BI9/uc/fgF+lcGcX73WFSnVx3qbANlZyT1DCWgmLlTIwad9SGrZ3vIVFM7AUu8XFu0aNGixTuHlmw+KdgKbzzHu8L14Fu4/VvnKG+cTuw5Dm88ufTcqfdIEkmiJRNfsFNPyF3FQKRklcVbyezuCFdb8JbtbUW4/oAJwLVz9FY30YMem9048yaE4FLyDKqZWfN7+4TpFCUleipID6BzF0QRuU9nNvfWPIIAFaJI6GSSkPeeylYIIUjk6cptCIFUZlzpX+Hg/t2j6m4IHokkS3scPLjPja9+mSqfxX1au8A1vYfCOBIp+epY8xPX+4xt/Nh+36WCS93jlVGBr2u8d+AdwlUMO8mRv+NhQtDRvp0lUSmhqWTackqwi61xIQ5z1uMeZPPv3Hh+5uUpX7xT8koRKOvA567PMMZzNxxL79GSalyiZYeqmlE9mMC4RjQnOZ1NOJiOsNMJiYR69w52Ml24BkpoMtXlcKe1K7HeoGXC5uASaxtXSdI4W6mNZ5hopkowmmhqG9/72SDDavnYyuYhZCJZfXGN3qU+k29epVxxyEYm9JN3NP/F9ZSdqeT1LwzYyS+zu/HNjJNNyu4m156/ycbZ6Ctb1vEm42Qb3TsbRykapOU2TndBaJJh/Jzs/ZMd7v/aHdxR9VJQDK4gXYWqa4S0OAs39mbxRm/ceHclseIsdEJt2mD0Fi1atHi30ZLNJ4EQwNWE2i2ofSt7hvJ+jZ8uLwuGEKh8oKoNIwyZ0qykXVKpmbmKqSspXI2bFbh8TLk7xRYGV1lwljNXBoirWyAl3UQhpWTj6WfY6l4+fSwCzHJCUSEFqJnDdgNBQjKNhFLYQF0VhGOfCi9BNZ3tcEIinNuc/XIfH/xSsvn69ox//OoO5azHwbSkJs4n2uDIkow0yyinE2xdUefxGlljjip63sON3VkUsgvQAobKs6Ln1zh3gq+OYxVNao3Pc4J18XyPtei3TeC/vO94fTI/iWArVDPP522FLyfIJGNB/SJj5bmxlUc1M4KZgFd3Kn7+esF/e6PmeuX56VcLPrSi+MRWws/crngzd5AqJmbGtADdy7DCNGsLeO/RWlMbh5yOUJ0hQiVUuzsL7ExKxVpni4DHuEiMV9INOskAeZw8hkBae77rzCr/+voKN14p+JXtPl6mcfZSgAzzbfWJuEfp5gb0wgeU9Tgf+Btv3OeXp6tIV6OrA/6N4V1+9JJhs1ORJA6zdQUz3sHMKmrZw11+L0GBqQrMkrhOgGK8h88rVG2QNserjIPNb17YZuXFNTY+egaVzQU+NhkSVEIQfaBmSIK6n1DfAWQGG88cqc91R1P6jGDbBKEWLVq0eDfRks0nAR9bv762Rx6NYfRlbo9uMfi3v5vu+55Z+rLCwxtTw05eUElHp5lJ01JhgqXyFmMNdjpDKEk9rQghsLdj+fJrNb84+U1CltBNFEZU/J3xX2ffbS89VtjehdqAcwjrkAczbF3jNKSVIC2gdjWp01gxJyFBgHLR1PBkxHQIgfXuOkqoUznoAHdGBZmW3NuvwCe8unuPUW4IwaOFRkhJ2u3SGQyYjUcAmKqM0ZrAqKgZV5Z+QzZeGFr+1JVFW6gvjRJ+8X6H0oHQKaEoMPk4ttX9Ism4mgiGzSc+eIerChSKIAK+mhFCQBwmNB0S1aPs8UjMZe2QtWewW/GfP53xn77Y5YevpLywnvCX39PhO7YStITP7FnulR68Y5AoxtqxVzryyRTvA3k+5WD7AaJ0TPKarkoiyZcJZjZFnPAW0s185qEYa6WzSaa7C2QzKyyqtvEGIlV85YLk9UGH6cqzc5FMs31WOIajeRVXWs/KXkkntzE1qfasbxdo5/kLH7rKP3e2T1ruUXc2WR2s8sHujMwccOHDCbovye+9QXHjMuNXK0xni9HgGuagILlV0q/mYwnSVSTVAc7U9Gaawdghg6NON+DEDUsySOic7RJcYO/zO9jc4q1gMngOr1Z4YztlMhUkWrA3KTCiD5vPzq9Zqqhll1C/Be+uFi1atGjxtqGVaT4JNBE7Li9i5nSwDHd+jrXwArujMwx7S6J/gHFteW2/YNUW0Fk9IlFCwHrSJ7c1lTfUaKTUdIRAZgFVGnTquCvv8zQ5Wehy4HbIw4Q6nBZWhBAgL0GnUFaE+zto08GFgAxgVYDKkWQpiUwZhynpof+lIKq7w+nYShccZ7tnqexyWyfnA1kmSToa393Cuh2Mc4QgjyqKabcb5zaruA9TV8hmvu8gN2SNIvvQLehkO/abVgxD7YlaGoFMMuppAUIuiI+2EsG/dUbhJORAvX8XV47RcoMgPN5ULEw0Bg9IzHgb2VkHFwhKoEqHtBW6sAQp0OMxL0gHbHCuG69ZT8F/84EeSghc06JXUjCuHdbtMxAClfXplopxXWG8ZyA78UYlCHxtYq75MUgh6SerlHaGFDFiM4iwQDa7ueUXpzl//+aE/+qZi3zvU5vRX/TwBkhwFNuprEceE4kNRzXKB7q5pZtbir5GW4/2cGnQQdozHHQ/TN09S1LuIu5/gV8yT/Pe9Uts1jOE0GRbB3TOxuQfr3rYUYVnDbRB1TVONwbxugflbYIeYoZPsb918eFuAERLpvJBQbqW4l3g7is1g5fOs5vvM6tr3rMeTfBzVlk99jqlJU53cEVLNlu0aNHi3URb2XwScAYQ+GmO0JoQJF+238PkF2uq63eWeiTWPnCrcOzbnHumRi0RUPR0ylB2GDtF7QO5Dby8V7Ov93nujOZPn/t3Scn4tdnf5ZZ5je9f+Q84p0+30KkNVAGmKeQVsqogBCZ5HQmkAGkCme6iO9kS7/iA9LGNHkKgshW5yXHBMUgHPL9xWu17mJEd1dweLVJS3aX2lhDCQiVUKIWta7xz2KpEShVN7itH0lyXV2ea//obQ+6Vi9dpoAMfWLEcGMHfutXlhtG4uopk8Vg73ISAk3GmMZgKV07QvTV0UDGPvi6iTc7R+j34GI1JaHwipUBVHmE9tq9xmURMc2xd4r0jr+aS/cO4S28sCEiURGuPMCmuLvHG0Es7mDqw3hmSCA0SXGGb6uNpq6OVzgZb/cts9M7Hd0UIpI/t7+60RhvP+U7CN/c7TG7N8JVDCMHrRcWXpgUgGmurQFY7pA+khaE7qUnqmMeujSOtHEnlESHw6fsHvDkp8LpH3T0PSEznDPsbL/Fz9wJ38wpbTBAa0vUSoSuU8ZzNEwrTZyJXEclTrO5retMRXqYUg6sEW1F2zuH1Jp08QFAU91/DFpNT5617mvOfvET/2hAh4PzlPkkQXPvgOu996qDxa3WU0/4pA36yDmaJv2qLFi1atHjn0JLNJwEfCYWbFohEUxpLOZWwvkrodXBLImMKFzAu4CgpvEeq00XmWVHjvOOsNqykgioEtgd3mQZDVp8h2Zd4afAEnk5fPKoWnkQoSigkAoHoriGSDJlo8rKKjkQC6sQjE30kJlpEtD9yFRxUB1RuXslcNqsJ0YT+6PjhcM4xxTiHx6Pl/DhCCEJw7N29QzmZIpWiakjDYa1xRXteWjWsJ8uJQ1cGtmvJyEpU2kNm3UgSbaxq/Xd3LT+7a4EAs0gKZRBIBCiF6qwseF8GVxOCi++t90c3DHagMa7ETEfYuqCiAgGmqvEuHG13I3f8tddLdvMyxpgenovpsFKlXB1cZr1/jr5c5fxMkxDJptQKpMBbsyCgOX6tDpOEggDpPOs7BYNxPM8PDHr8a8NVdu8W1I2S+2e3D/jb9/cb66PYbtcNARuOalZHNdrFlJ8603gp0NYzDfCzt3b56t7s5CroD8/ylz/6DO/vGKq9m6i0F6vJtqY3relZOBAXqdOMJAzIB1eBFaYr76XKzjDrXcKR4pRkcP8A9+bXKXfexNfL55u7tUP5wOrTQy5sZBgtUUmC1UN0uY/JhrgigRNWSDJLsUsiUVu0aNGixTuHto3+JGArgvP4vEStrxDufYbVTYX51MeweUVlHUFIEinwwfN68YAVuYlxDkdNHVJWxCLvr43j3vaUjUFKKuB2+oCnqiu8t/o2nJ2RyFWUg+HGgH+p/28umoQTIok6xLiM5uc6QAVqmCCVgrzCTHMEXbwC6T32/2PvPYMlS8/7vt+bTuh8++a5k8PO5l3sYhGIRAAEYMIEJeYkkbQkU/wgWiyLsljyB9kuS+WyVZL5wa5SWWLJRVomKVAkAAaREEEiEWGB3cVi0+zs5Jmb7+3cp885b/CHvpM2gKZpcj+gf1VTc6en+4Tu07f//bzP8//nOaHIIb3DLkZM7Y+GXUeUVnj06IMIBC/uv/iaXs2ycHQ2RjSWK/jcQXqQKUhAKc1kMsZ59RpRG4D+9g46qYIQ5OV0WjnPCyITs5LAR1de6ywfPDjniI3i506MaHQl2VggpcKGQNnfRjVXeLQimbcDfBlR5tsIo1GvkzUPgFSEIiMojfcWRbhleRSAortLsCVCGzCakBcUNkNFmpB48iLHO8l+4ellOc2D5XUpBEbH+LGjWipGqaYh6+jRBIsiZ2pBJbWg7G8jTULUuu2P+rnugEVjuK96O3JTOI9E4IXAS0HpA5W64Z7HF1B6en4/vtKmdlAhFiFQHZSURhJPLCJAHklM6W9Nqns5FbGJVvwv9x5h2Lhd8b2TphsyWn+B/ZCwKDVCWoItMYXHGkVq6tPqaeGZJBWUPUPUyUhNgSzbKOHIix62t44RlqBK9KTERAVlevc+a4OSMncUscIrgT9or1jvtehuRRx7dAGXBSgcVAwMC0gNwuhpwtKMGTNmzHjTmFU2///ATgilm3psCkEze5L5cIGBE9zA8EKv4FxvwtBlPNm/yHq+T89aJq5ASUHFOzJKegywwXG52MAYycpiDW0cE1HwqdYX+ELraUpZYFXBJJqalRsp7hKaYzugm7/Kaik/MNKUgBOY0dR3kuDo7u1gQ0kUJOO9bcpshB+PudN7xztHKAoyOaI+nEdajRsLHpp/CFkYysLdWjYf7E3obWdcP9fBbU2mgvOgQldRVWJVw5YWeUe1ybtAf2fE7vUuve0SW3pGhYXgiOKU0lr6r2NhE6wn747J9od459FW4ApPeXDoUiqCtwhf8l0tyQNyjC8mmKCJRUw113gCZRbRubxyawBKSIW3OcEdxEwGf8v2KTgLISCTqdWQ1AY7mlYhhZeUtkBIyVoq+bkjBUd0iTj4IhGACMlQFvTdgEFWcnV7wp4vmJjb2fFCJdhR967Kpio9X98b8NnudJl5UuYEb3F761gsZawYS/i7L13lD/f7aCNvXRcrkaGm1MGwV0A5z7a1/NpoxNBIvJLksaKIpq+J1ZKo8DglqCOoKElrN7vbNqrMGV1/nueLKr+0U2fXAkIxN5q2Kjgt8VpijWRc0XgJwjvk7jZ6OKTiNDhLPtgjxAkVXactF1DdDmH9CsE7bNafTseHgPSeeGKpDoq7HB9UkmBqFYTQBAFlVoILiPUh4sYApTX2DarvM2bMmDHjr4aZ2PwLEEJg/ZUuk+6A4G6LhefkD7D5m5b8G+dRIdAZT9jsj/j89h4v71s6RcLGOKObjzBCkEjDpyuf41fEJ/hm7zJuM2Yj32Mj3eBfN/8DVnp+oPN+vqP/KD54hBTcdK2JC8nijibKD4ZAgifVdWywUE6PUZSem4VTqQW1SYyTAR8ppIUyHxF5iXMlwTmM0ExcgQ0Ob0uKUY9yr0Or0iAl5eIzl9m82GO4l7N5qceNlzpcf2mfztaIwX5GbT4hqmqEEWQ7Q8bbO+DByJiqblHLqih7+9Ib9wvyUUmUGqQWrN/YY3dziCkCJtcMe5p/eaHON/u3q6i+9GT7E2xuMRjcuEQPBf+w0+C386nBvDQxJYovDjydYrok7l1BQkxiFTJA6XPywVWkKQghMNprYCfxdCDKFgimS/w3xbTLJwdfKiTSxFMPTgFCBiqygfOO2KQcWjyJFpLSBzJ/8DogUELgdcqVq1fZ2Ogx7hbYIqCD4lA/wRcSqRSfo8Gv96bT9HFmOfFKj39Qb/Izhxb4bGfAL1zYYHf7CiGfUB54UvkAf0tWObr5WqPz397p8o8urCN9QAR4epjxid0e/ZstHkJMv4Ac/DyuaP7Nzj7P7g2QgwG6cNR6BWYwBusox12EWKYnAAAgAElEQVQCcKxq+FjbkcoDw/0CrLnj18qtHFRBJkvKcsxguIX1JaooweYIrdHSUPMpcQFyPMaOOhSbF2h0bsd+wjROtTS3v6jU2xFrp6ctEFaC7eaQ2+k+c4dSmjLMxOaMGTNmvJnMltH/AhQTx/blPiHqsBwO+uhCwJaO3qnjjKpVQhDEeIYWtm1AkxK84ZVsHyUctRARjOatu0/grGVpscKOy1ksVinjHg1fpeZTFvIalbJGUCNEnJDnFpkIogK0E8z1NDsL0769mm4yHPbRnRjaBVgJB6visVeIIPGlx0uHEhHWTghFjDYx3pWkMsaiyGyOHIygdEhgvrKIcTDY2aLSrNLZHqOVxFQN3gf6OxlSSaQU00hGo3CjIXmnj6pIdBUUhppXGHdw6QXIhgX1hYWpgXoIZD2PLy1RiKjtl4y140OVAUfNzdDzg+Vza6lWG1RyyWQ8QkvPx6IRNQO/N054NCopQsQnB4ZmGHFP8PhgUTJmaMe4zip5/wXy/jOo5Cl2+hKd/DRRNQOm1Tsh1XQy6qAfs9fZIDUpIQQKXyBzcTAE5Uh1lbiaYCJzEPuo+Gd787yvXvK+2gQtFcHDaFDB5hGLxyYcWdtHBI9xCUmu+Y2y5Pub8IqV1JXn+WHG7+72+MVDLWRqiGzgHWXggrZ4VzKMPaYYInxJUmlybz2lmLi7qt0Aa7Hh4VrKhgpoIfhwu8H7WjXi14kYBZiEwIvjnFVvOX7pEi5dJRZt5M41BrGliAqkimhpeEfdIz00JjHClzj92m2G4LGDXUolwJd8TddohcA9Ucr5Ak4C1SCRzmKDx2VD5KQgii3JQcW1iF/760qIqYH+sFuQ5ZY8sVT6d/QUR4YR5nZC0YwZM2bM+CtnVtn8CzDu5ngfKIYZwR8YSfeeYlm9yPbjD9BdWiC3Do/EloI51wYSIgGJUFRUwsV4l51aQaIr1CsJ9ajC0pV34LotKiT8eOcj02XYQlFg8TaQYygKi5ICbQVWT2Myo3z6wduKFpCbA+zOZdgYTq2LDrSH8RIvPNx0gxERsnRgp/naUiqU1NRCNM0WL8ZgFMIF8p0txp1tymyILTLSWoRJDwzVpSCpRUQH/769AjxBKIvLLMVeF/3y8zSpYA6SbWzhDyqF03tnpSWUgXaICN0bXLvwSdoW3qFHJMP81naD9wglMNpQI0FbQVkWPBx1uEcXPFVEvFhqjijPfxVfYY0ewXuczynChCRovCgxrYdZuO+7SRdPIaOI1tF1TFJOV299QGiDL3O89Thn0UFgCeQuR6OYlDleBoLNEUGQEpGYFELgkStV/r6BRAZccLeGqbQOaO3RbkJwBaXXPH/F8DvRmJ8PCQ91a/y9yPDfllU+s9dnPtKUjRgbKaTzPLjn+FsRtJIKUkUUvW02t6/z5d095g9VOHSqcfAc3R6WeaJR5ceW5/jn13Z4ejQV028kNAESKflnR5q81+6Rqip51iEXJWMyov4IO+ohD6b3Cwef2TWcHykIgRA8gcBk58rUwB4o+zt0xiP+aVbjSWr85khyBYWQiosW/ruBp6s9HT9GIanvjYhKkKWl2ssR30IrhuDZu9FnuDNhZ1KQdfMDcRlQUlJ6PU2mmjFjxowZbwqzyub/B4adnFEvp7edUdEjis0+/tC0eqImV6gN99iunEF6SUzM9niEshUqsaGCpHTT5dm+nvBcmqPNNd4xPINJo+ly7H2XIMD4lcN4KlC7irCGzJco78kjwAcUAlkGRiZHCUgGUK0npKFGmhtykxM6XYSaipyJHdF2MQU5MhiklxiRkBiFUnoaOxmnOGcJ1iJCQAmNF5AkFewkIxCIKnVcWXzL58gzrQzacZfgHREa2+lhN6/A8SfoblxD+ypB3p2pXliL3r1BLj2V+iHccIG+aWHtLkoKXO7QqSLYcBAlWbB14fO02w/QqQhinSCE479uDPDAV4qER5xECYdTjsJV8N02KnyN0dbv0jz7AURUo5W2yedPEXnJiV6NZ8sqRRbTXu5iGeNtgS0cSqiD+EVJ6lO01AwYoPIcX3Tpn9shahnSxUMU2nFcTWhWHDcKyVtVndZYETVzijLDO4OMKgz7FaI4cKLu6bkJHRGoFworHH//0BLNfknfBpwRlJFifUEwzgu2rGHbRTxaiXh2z7F0wXNZZJxYqGCGY3x3F7t25FaVUwrBPZWYtp6+7X9/r8fv7fX5pTOHb0V63okddQixISGmH7qI3ct4l5NU2iQa5vKU/bQkDYLnckgSzxntMOM+Ukp8OZ62IugYOxkw1gk1AYcV/FgdHj6Y2zmpoV4FISX/86TOd8Twn48L4mDojTdJlo6/8XVWTsj3r9OsBeJaBS+rXNkZIlNN4mG1HoFSlMOMWUL6jBkzZrw5zMTmn5MQAtfP7VNkFiGguvMcZafGGCjzBfbb38P2v/sNTq+8wDOPnCCVJRCoizmEtMQkZHaMEoKmTXls70FErFCxoCg9zgbKyQ5Rs0FwkiAc1gtkCBhhAYU2BkJJqQKuHE+XHYUkzmGlWyPNMmJv0Mk8I/poDC44YplSUw0ykVOUOdJKPIJK2rjrHIWUlEWBQuGkwvqSWDdAa7yCspxQTLJv+Tx5H3DddZSURKbGnK3g4ib+3gW8EVz66p+Qzi/RPP0u4qq+9dxa5ynHu4jgmD/0dtq1I/zKhad4aPA8iw9+CJ9BNBHoHEo5NSff7V6g0jhGJOapqip91ycJhqxQfCqrcnI4Rz0doNqWJFug1zuPVzvTaW9TpfAlDVMjEPA715hTjzKvehSp5eFsia8nl8nzHiIz1HRErTqP9w67b1FGMSgHaB1TDrcBhZAxxaDDRm1Co5/wjY7AZAlqObBQxOQTTycyxJljUk1YaXiWiblYlmTxtBqZa8+OGrEwbrGwPWFc0TgjCVLQSR0Ugt8cwbiAhxfgicTTqwRO2RF5f0i7p6mMY65M+sikccub4CdX2rfE51oc8c5GFRsC0avE5i9d2+KMnfCBWsRYOKRMCd6h4gYiCOZDi8QqnAhoL/gnTUCDnXjK3jQX3RcZoSym/Za2YC2u8gsHAvPoHfs6E8EZIATBg7FCKIFPNNZO8MVwOuT1KtcDV2QIISi6G7jJECMkbjgiqrVQtSql9/RKS7uXI7SiGH3rL0czZsyYMeMvj5nY/HOSdcfk3SG6WkEpjyjB7WfktkD6Kjd2LC8+8VZ25+rEjPDBAxFGGAKOl6sbtIcpaE2NklXbYdheQ9hAdPleBukQV1kni4HjL2L2hjivkXhKpZEODrJ0cNKRR5DIlNzlZLHFaIXvTTAotE4YmwElOT445uQCSmi0DOQiQ3uDf531SSkk/TxnVHjiJEaIHC01NkyzzQvvYDJ8zePuxJU5weZESYNaqfG+QChDESJ0nPLQu36YYRIoJtMs9MH6RfbPP4M+9RhH1t6Dqdam/pvAW+dXEXIAeMqiwOce5cDYfVZaR1h5y88yLnImk012rn6Z5PjbSLYXOWEk35VuYUWdWrPECkOzDp3rX8VU5lm55yPUTRMbpkNRHk+vXuX57ALjeoVqaTC5JNE1IpvT7Q4x9SZaaoITeBxSSCSSWCUk1LHe4wsgn6C6jrWizb1xl0eIuBgyPseQ3kbE25dqLEwiXq4M8SIwdoI/2hd8eOWOlCQhGBnH1krKy5cGzK9VqTUjRt2SuNvkX5qIz/QdPWVpNh2ngmO5E3GeEZtmRD2RTPZ3qek5Tu+n3DhcY1y/PSzzcC3l4VrKpSznqcGY719sTQdtQsDnYxAOcWAbJJWGAy9Y5wLaS5wIVEtFKQNOHQxQ6RjlCqSOkbHCTYYQPBtOsBimmfJvhBDwQ/UDM3zAmwRROHw+Qpr0lum+KzIm2xen7SUCVFybvjdHgZ1zI47en2K0pNSCybBA6IQQJW+02xkzZsyY8ZfMrGfzz8n2M5fIz59DZ/vEMVAInM3Jh32k/RwLxSfoLB9mklQQApyqsBstkglPJgs+vvQlerFk11X5jflnyXWGEBqEoGhsoyoDtPPEXmK8wPoADhyBQmpKdcdioAvTwZ34EHPREqmuosYRZTamFmIEkna8TMssIoUiDopAQAmFEALtDSHcbcAO03/npSeWUFqD9ZrSWwhQOkstruKdxebT5JzXIxv0CIAMIL3jxgu/RW/neSBQTCyTUaAYWa594TfpXz9PZeEQSXsFFTVJ4sYdS7/wQPsQp468fepVKqY39rovMrjwRfK8h9WCqJoQfImzBcZ5tLzMURXx3rTgVDunYSq0dAsTBU4/9CMcOv5eWnEbJRSxjNBB8lB/gfv9cYbtOiNRMDAlXzQb9DbmWXULmNJiRAU3KrGTafRSf/8CGkmiEpbHMWcGdcLYc//2Aou2xherV9mR2zzV2CJ3ljgJ1BuO/UrB1eYYKwNWBr4mM04PI+yrLJ6sm9BrxQgpGHUzXD6kGI8ZlxKrPPe14KiRREGzYwZcSTpkZNPHVUBFNVSW0WkqRpVpf6O3OeVg95a1khSC39nr88xwWq2W3vIzyZgP1F/fn9KpQKE8hfJYEXBymiX66TH8466hR42mTZA6Yr5jWdrK+VdZwse78k5HrW/JVybw33dgjObC1iZZZ1otDbbAjXq0XJXjk3m0qaCVoW0rnHR1QukYbW2QjkqMkoxLR3LkGNHRo3/GHmfMmDFjxl8Ws8rm/0smwyHOCTo7Od0b36TYvs7C/ffApQ6SiG1qVFyX5qDDiVCwU5nQlY5PHfk6D3Qf4FixzGYwfPfGezlRNNnWE5qlxluD62eIFApxjZpsUlM1qqR0+wV26x3o2lVckqNVgvMWeTAk44NDyxgtNHXT5KV+hWd2Cz6kRixJA3i89wQfqMoWFZfgBQgEsUpRxuCceM3nf+kD6BitFSJ4MhtRKEvkJahAq9pgOB5w5ZXnCdJw8p7770pAKvKcne0bBB2jvMAGR23lQeL6EkEIyrElRiGFJKo2iVtLaBnTPPs42SRG3OHdfqkELWBVKLA5+fkvoZpH0EunWKitYFWDMockCTTap2nMnaEMJZf2/j036i8w33wr9wzmGCSOjfIqIapj4hpaTvPqtRMEAYFANy7ZEiNKl0N3k7GdkA863N/8QY7lNbLWUYrMUxZDlI4RWrK3+Q1a9WMsLB1iFDl6sYVIsuUmDKJAJGImLsei+d2h5/sSzYPWsOEdw8ix7yAVcKTlCM0MrcF7kBKQEaPOkGZtnrUzDcYbr5DvWmpVQahrrppAPdesDRJerhZ4H+iZCXhJINyqkPZMzqQV8INdZFTBjjpUBjnOBkJrgeOR4V/dcxgtJb90dZsIz08pOZ3EfwNCmE51WXX76nk0nloTvX1YZRiXDGKLDhIfLP9NpHjnpMalckTkJKlVbNQmRE6Sq9u2YTdZUdPezpWiwWOTiH/NgA+kHU5fd2zGGUbE1EqNAE52qkROIhGsrGzSniQsbIwojtWZWA/FbDhoxowZM95MZpXNO/BZRn7xEqG43d91brPPS+sdLj79JNeef4lyNELoBFUasnPXcU4x8iM6PuOL5eNceOEwh7/wGZSPSL3hr2++jQoZOjg0cH++SCQFa1mNj117GBdF+GxC2NVIL7G5I00qUFpiLF5nBDmhFCCFwRMOqkOB0k+IREwI05nfhXzClQJ0sLxgFf9mt8nlCfzJeB7nI+SkwNpp9UpZh7AlQkz9GUMI2IMqZWn9rcpiwJOqCGxEUZY00wZGaeK4wn4BncGQrZ1dssJiDzwb9wcjssKRaE3sJEIb6iv3E1UXbl1xUgsqXnPo0Q+DTvD9Eu0FjUmKukN4/PoQ/t0AkAITYlrte6hU5jG2wdzcKYSA9esxo5FEecHado1Wv8aho+/iyNo7aegGTEbgLN3dl7lx8Y9ubVsEON2psTZI8BL2qiV5BM4XDK59naK7Tij7ZPN7nJ8bUSpHMelw/rn/k9HoKkmQtJceYLV+D4cHKRPtGMbTXt6d6tSovexbJtfPcTUY1H7Cua68lVwUAvzqAP7FvmUcLFpDv6fYWD9YLvaG9RsVetsj7GATJS1CGVSUYsxU5I2M5VJrjL/5TpYS7+xd09tCadykz8ktxeLmGJePWPJzLO2W2P4uRy4POHVlhArwz8eGn8oVy3mNtHx9sRmC5+LzH6ez8+J0+OvGDU7vJiwL+K4q3Ghk7CdTu4NrUZ8bSY961bNZnTA2jmFkqRea1CqO9SqsDV67xH1aCn6uKhlVc76sco5hUZ1p5ObYeHZrJS8uDAjA2Dg2ahNeag9QcYVMerpjR39k8QLKbCY2Z8yYMePN5Nu2srl/7QrBOtpHjyHU9EM1+8azZN98lvjUKarvfjfjIPnSKzu46+d5qFFSDLrEu4qUGkJH7I72wY2YhBFt9Qp78ixfeuxxFjrn+dVDn+FvXnsnC/k8i3mNgGfNB7SSeOcpywITaoRkiChbRJ1HCa3nMbURhZ32PObWoxZeprA5bXUap2KsKChsjnM5NTnHC4M6n9gY8z+cUVQH1/j5VKE8XHE1jkagpeFyEdHwFcyl36N0BUtnP8T285+ifugR4sWzU8/IYCmDJwqBYZFPh2WCYeJz5lSLyKU0lMQkBh8CvWzq5SiM4cbGNTbHJVE8TXIphgNqRtO0EfjAZLyFqcwhdTyttikxvfI8iMyz3Jxj33UwZYx2EiMlBVPh+7MN6HuQQhGpiPrqQ/gyZrxj0NUCdGCubUlTj88lneBBe+r1YwCM+jf4g6uf5MiZ/4w4bVFrHr51DQQBF+aG1Irbb4OqqmASQ/XE+5FK05g7Md1OUXL+mV/m6KF3s7D6FmqyzqlOjUr9IbpxyTeGIyYZVGqws21IU0uSwOaVr6J1zr0GapEnKa7xueYC/2Fo+KE6fHcF3PqTbG1cpfbgD9PZu44xVUJoIATMtwdUErCjHt6WmEr1ruvYS8hvlroJ05NyJSJNb91HqgiX9RnKBqW3SBOzpXOUE5TjPXYWTyKY9qD26p6qHxKVKe2+4Xx7yJF+iheBG/XJdPN2QhQ30DplPNxiY/8p2quriINvEk8FR+HhAQX/dJzwTlPykViwW5l+icv8mM8OPk8jOk2aHmUY2VuvVVpbRkrNfBbRziJemh/QnitoFRMGHl6eV9z5aysAnaQk0+5WdXQcldzQjsNh6hdajEtmzJgxY8abx7el2Aze8/Qnfw2fDXnizFupfcd3IBsN8kuXiE6cxG5tMX76aZ6dP4WeDHD9bZ6Z1FgZj1npgJIRPfp4VVA4S0Xf4I+Xv8LzYZf33HgfF+cE3/P5ReQy2Nr0gy4A3ntA4a1HOI83CVqmTGRO1n4KHeUYaShyQRRSyjAh9p5KWCQOS5RijFExialgRUaUSQ6liiOJZTDsUaeCU4KxyPi+KJA1IB+XnF0YkGTw1OH38scjxd9WEa3j70THdQIw2LvCYPciq0ce49KLX+OBhR9FtYZcNjvEXtLd+BqLq0+QjSpoBFf3RwxzR2oMabTAfmcTo+sUxZh6JSLkI17IWjSV4Cxd9l75Y5rH3k51/iS3ngzAi4ASkoZPGagBIdekQpErz76DmoSWmv4ByXw8D0wDYpwThABGwGLTYSWQerJ0fNdrXW2scfYtP43WKfVCM4jurnKVKtBJb4sRKSSJiEkWzty6LZ+MuHa5z2NLP8Rpc5SXlgcUBK7tWTYGkMqcK9e+QKX1AYQq2Vv/fVrtBWpHn+DomQ+iVB+tBE3zPOuXPoNKPkonrFBuv8By0iBZfYArvUtMRjtk3f+Iah5FiA9izLS/0036eJujoruF5qsR6qAi6iZ0t77J4qHHprcLAUKy0chBSKQ0TPDTd38eGMZuGruZ9dkMmyAFZU2xRUEQsJsWzE3MtAfXgzYVjpz5CJGVFMpTfegQm3ccxx+MYRTgjIF7tGNV+mmCkhAMOpdJqot0988TVxf4+t6TNNqneMQ8ysb+CFkMmEtW2E0LRsZNYy6BvCj4t7ZJVMLfrt85RAWZubtvWOqII7U+pzcNV1cSBnJW2ZwxY8aMN5NvS7E5vHGdvavnQTqy1mGiq1fxZYkgIKRELS5x4+nnWU/3qLUrmDgivnqBshdzI2RESYIKnq9XzzGpSNLyOH7/I7z3lReoVYecbdxDWBqik2lFc+f6SyStJZJqE5flBBeIBOSxIc8i8AMqBmqijvCOyFfACypKUA2O4eBeNqxCHioIAaQLaFPl613H+9spP3/aM1jfp2KaOBPIygIjDHkQDC99DYqcxdPfy+HKmAfEPDXbJ8wdJfZT4Zs5jysLepsvIcKAQ7Gk8BWuBMGcavLy9gvEUZ35+bdwfX9EPytpVao4ZzFKMV9roPyEQkiKwTY6G/Flu8a9vuCEiYhPvodwMDEMgpt1OBccURRhckklSpn0BT4KZDLwL/bhuIG/W5uqCidvrwsvB83cimWs4FinQuwkl1pjVBCM76hw3USblHquOdavcKUxZhBPxcfCOGKiPMP4W4uRjcufwedjRsd/hKuM8YBUsB4XZJlETDoU4yu0l8akaYU09dTnVqfWWDUJtABozp9Cm4Ra8yj/qBjxyrNfZe7s9xDFDc488uMAHDv7PcRpm1H/BuPhFgurb8GXGcIkrF/5PAurjzLoXsG7gtbCWeJ07tZxygM/1e7eOTrbLzC//BBCSJzL0VHl9U9OKfK9q4AguKlNl1TRXc/3OHKMI0dkJfd0apxPtslrCfd0auwnBev1CcE7djaeJknb/FTzJFUJkYAfqXq6u+fpZoZqY41rr/whzfnTnHnkJ1Aqoph06e68yOT4I9SqyxjVQI1GTKICG98+Zl2d4+RE0Cy65JnHJ2221r8Og+scv/djt64tIQRSKca65HLUY4hGhjfuPZ0xY8aMGX/5fFuKzSvPfBlb9hGuYOfGy0yyCaVStI+eQAMT53muO8Jf/gI9pWhKRdXV+NPmBT5+5DP8zNPvYknO85+OvcjcpM47dtdYGq7yxNNf4sLJ8/SqD0K9RoZHeAtBUjpL2zd5QryNF+XzbLir/KFd5Cv5Mn9v6/dx5T61U++mBCIkA5mzEmokIUXPWXY2/ogv7J3hRHyIB9IxXZewmKW8uL7HB0JCQ8wxUIGqUzjZxKBRwdNae5TKoEAoRcMb/rFrorIWv8JVfjBbJpclzzYK3lJ9hBVb4eLhLuddl+1X/oBq+iAPVc/QuOenGTenS9yjsSM2Ci0l+iARJ1F1TGdIM5ljc9gBIfkblQLfKxhvxvzfC/exUHh+OB4gAGnBa4/1jpapYaNAWlbomRwjAlUr+b6qp6mgmWuWRjHn5oeMMokbKe4nYaeSM8ZxrZmRWEkj1yyPE67Wx/ST14rHQWSnQjOytyqr81lELy5fIzZdeTCVrROEEKweezfOFagEdgvH1o2II0dzGk1Ho+mAFY6d/SgmnlYRj5396GviIgGE1NRb0+X9KK5x5pG/iXmVCEyriwAMe9fo7b1Ce/lBVFShzIf09l6m3jpGpbbC+qU/YeGgcnmTnfWniJImy4ffMRWaUnPl3KcIwXP83r/G1tU/ZXHtrYQQ2N9+jvbSA2iT4p0FAr3OVZSOabZPMRnvMerfoLV4H+pAxEpgw2/y8iufYvXsh9muxHSS4ubJ0dl5gdbCWZbbJ28dk1Qx/c5lpFS0Fu7lzCM/gRASdVCFXTr8Npy37MgSnbYYTva4evGTLOt3H4hnQa15BD/Z58NJk0sXP82gfYr/LWnz9vGEJ1pHEUJy5dzvYO2Ek/f/AABBGZ7dSaiXOctHZ3buM2bMmPFm8m0nNvd3Nnjhq58mmBYLL11lsv3HPP3hd9GoVDh+7mVWH3qY/WoL0b3AMJmjS85vLXyFH9z8ThZGK3zkpfvIt26wfXyJH7j4Idh4gUOVL1K2HubL3/lBRjvnScucipFUhGAomrx/7e+wyx65vMGXfZdPcITv7D3HB/e+zJEjjxDJ+4hrloqJWB9t0e1vM7d8D5c76zzb77Gw9AALw6s8VD3MD7s6z3e2aYkhT+gT9OpVFm7E9GPLMBqzOkpZ9oo/3f4EK6tP0KodJsxPl6zbUYuLrSGvFPDLo3n60YjvNBaRNdjdT1lqCPKKRsoCYSIyctaFpaxWECKwcf0L7EjBnzTfyg8uQargS/uKC5nkHyQeQ4X/NFllVeY8UDds5c/QG3yDv7Hyd/heO88Xhg6X5Dw8XGGnHHBZTBgFQWeQsb0eU0kKQkXzlnyOtDqhZywDadFeklhFlGle6gvOHR/eqrxZGRhGjqFx9JKSQr2Bt45gWtEMcKZTZaRKXqjvoE16191CCOAdqtLCjrqouHpX9TAbT+17vJtWN29Sqa/c3tWrhGZwAe8ObIaMurUE/GqhCeCshxCYX3mchUOPIaXBlmNMXOP+J3721rZPPfQjSKkoixFlPiCtLTPsXUWPqzTbpzDRtJLcXnqQEDzOTuh3LmHiBrXWUfY2v0Fj7gRlPkBIRVKZRwC760/RmDtJkffZvPpFGu3TKGWwZcZYRQzbUAv3YtIW2+J2BrkQgjMP/wQQGA+3SNI2UhmEgOP3fgxn82lC1R2tALnzFNahlaKwjtQokkqbo/d97NYQ0vzqo0hluPzSJzl+9mMonVBrHOYHDNTr72LBwI3SU6TLrLWPAoFLL/42SWWe1YV3sxDVKNwsF33GjBkz3ky+rcSmd45zT34O073Md87d4P9YOY5prNLMlskG+yx/8XOc27zES8eXUcWATAt6cc6o2Gdj+0XmWg/zePco7fWv8PQJh9eGo35C9eUu4d4BpnqK6oJi3qzhi5LUBBaF4IsIglOYjecZzecsRqvU1QLfMf8BTssbTA55Ftwyf5qNaIxfRgwGPFo/w7NijyO2y9vMMcJ9P0V3oNg2JZc3vopUkByb48L5P6W/9gjKtwjBsZvmiGxMXo6mRtYeVnsVjIRLcyO8huMKfkHlnIwMPkTUikB0yNNrO2zXE+uYI2c+AkCfaZUvBFAqISp7mAkfgKkAAB2XSURBVNE2navb1I88zLCQ3BdBrhwlGaKfEpd1RHXC6tpbaTQO0WgZOt2CyX6LrcqIw7UezlZRgwqVhmWkCqT0xKrG/555flGV5PsalizowEaS0xpFrAUDR8fkrycoBW8sNF9FJypwvkSYCJsPQRuUjg+ukQKVNonn1iB4XJHd+j+AesNRqzu+hSvQXYQwTVOKWjGucLjMoczrm0AcxHljGhFlv0ApxSTb58I3f53j934v1cbarfvKgwO49sofYKIaR+of5vi9f43g767SNu6oMq4efw/VxmEgsHT47Zi4zoXnfgMhFKcf+lHqcyfwYTr41Zg7wakHfxgTVfDe8vI3fpW5hXtZPf4e5lceed3jl1Ix7F3nyrnfYe3kB2gt3ENv7xUa7Wn7wF24gBKCuVRTjxW9IjDOLYmeCl+A+976XyKEwpYjFlffQlpd5NjZ70EIwUN3bOq3x5L92hP8wyp0PFxJj3HWCFqp5ETfcK3y+l6wM2bMmDHjr4ZvK7GZj0fcePLTXEjfyrXsbXz1gSd5rPs2loqEjx9/ik73GEtVwZfn1nnomxvcv7lP/9H38t07b0dke8TzVdba70CtTDi0U+dE/R1cWlpk6dpvcV29j8fkCtcq59jC05QPUrgdDNssiXPo4NjCU+9c5nvnqojaKk54gnBUTMbISkpfp9U8xkr6OKXS1A49xmPLj3Gsb9i0ga2Owi+XHDr2QSorDSYCsgs7DHrXqFeqXL/4H1EqYn7tu4kqP8mhsWCrkvP8wLPSmFbWJplkMFAcmxN4Fxg5gZKW+ban8AEf4LqFf9uHn6zDMQPrI8HpbgVRfzvV+YLK9S+R3XiZduthfiyxTPwIgoEy573zBXvbL+GHq5wRJ+ilVbqi5Hor42lf8Hsupq47NMcpUsOprIppCKqLQ+4dLPJINGBHZAyLlLWDCuDmesRQCIqVMbn23+IV/rPxvmRTD4jm1kgqTXyRke9eIahoWjX0DhlPq28qbeCyAdwhNuWfYRZ2U+4KpuLRZhbTMMhYgQCXvbHwEYWnlsY4JZh2EEPwjub8WZLq8us+ZvXYexj2rk8fLwRCmde9H3BrCR9gfvlBAE7c+9dBTB+rTcr88m0Zd1P0SalZPvx2as0j3/rkgVrzMEfOfIRKfZUi73P9wqdZC57Wwj237qOcwNlATQuikGEngXa1QTYa49Rt6yt5EFFpohpLh9/2hvv8YAqHNSQCLln49drj/K9tR47nabFFMVrhwT/zyGfMmDFjxl8W31ZiE2fZnwxZ4wEOqVXUpqaMFU/wCLv719k7HHDRHD+WLfKM+j2efORekmrEI9nbkFsf57Mnt6kUDcpja3wg/r8YlCdYYI31Jz7K5miJonQcUprcCUZCsCQCmZc0Q0DKQH3pLSg03pZIXXA1ucB6d5G5msTUdjgrG8Rqmd+YxPx+NuF/QpJo2K0UDOOS4ydLlAJXRtwchrjnHT9GKC3rrxQEarSXzxJFntM1WAiKoQZ7aMI4mpp8Z5kkn0ikDFzfMQyHivGqw/SmTupaChpMjdTNwYf+Cx7epSU7SuCdJPbvJDTfg4s8O+tfZ2fjmyys/RccmrdIEbgxfImuKRD1k7fiMIUQPFCzzNshbVmh0iqIpORqMaYfWdxY0mtIPlpvMOlv0D5+W9W1F+x0IvkvKDQBvC1IFk+gbgrKuIqutrDZEGWmolIe/K2SOkiFcJ5wU2UKIEz7F/2r2jID4As3/UFO/1NXNDrVB9uVSC3xLiAPFFVeOipBo6RABEHZFKQTgRMK6wNpdZGVtfcRyqmXaiAQvEcqhZDTHs+bfZ43j0EwXboPgFDirtSeV7eSmluDW9+a+ZWHX3NbOPB7fXXbwE27qKBi1k68/y6ROi4cdaG4EbY5Ro0KMSQaW0yomkC3KKnG5tUzXgA4W0DwCDldng8HP997R9DRIVHwT5oCXWQ899IncPoIrepHpu0RM2bMmDHjTeHbSmz69a+T0OZ8mbIZ+swLw46K2XYDlkdH2JeaI8MlYho0Gw9RDi/ziHobXT9iMQx514tPc+mwZcHU+VL4SRLxFaRdJUFDepFniGn6HjY/zu5kSDW6jvCe9fIUkbIc1rsUbsLIVWlEllHUInMpiVAIE9BS4EWFJQ3fX51WagC6BwbZB3agBA8+s6iqwY0HlJmntC1aSx+i2pguoxaLEy4GiQiCOLqd0DLXtsy1p/dZmS/5rPTcH0uECDxbCB6Pp1PEv9i6LUzeXwucrw4wAqqlZL6pyKqgguC+2uNE7QojO8L0HadZRd/3o5RGcJm7bYjWooRVE7HrDf9+ND1HYstvDeGZXPM/rsYobRDDLYJ3txJs0vS2yCz99Hn6FhHbb8hN+x35ql5JFdewoy4QQwjIgwxuISTKJJjcI6UEBIV2KC8wXjJSbmqo7wJJkAQPtqrQFU3RKxFKYBoGoW4KVYGuaYpuDkohAiRWsR8XBBlIYo2vS0oj0YVAjj0+ElPBiMXZAqFidNXgMosvb53YHRP4BzGfWiIVuNzfvvmmOJTy9t8Hos0OhyRoQhDkFIgoRSqN1PI1AvXmLl0+xHuHNRVwHmUM8c1zDdPzrS2cRSAIDpSFqlAMy4yiMYeqJ8ieZ+7QSWQUE69fwnYG5M4Tyel+XTmB4JGmArZAJTW8K/FuGhfqsn2kjm99eWg7z1JzGTfYZ7P9GNdlgx9pD193YGvGjBkzZvzV8G0lNj//a7/MXNnhdFjGxilrc/dzX8Ozt9cl8Qlr1rIxlORyl1bS4sH6Lp/tzNGsdZk89n4aYpc2CeiEWtA0OUUpAy5Y7tE5p92AelylqnbYzypor/BJhBGK2E4oRJ/BXM6N7UepWcvRSLB6SCGVIxISl48pcTxEQKf11z2H3R1NWWgW3IjI56BTBJ6V5T4qOuiLCxB5ydg4JBCXilL7af9gOSZ4DwS0ivjw0rSK9+RE8KtDMMAj8d0VMCWYihKgNYloiMBWK8cHWChrlEsPcX70HN+4/CU4+1N4oXjdEGznkK7kXOG5XBjSpAQVs6ah7kuCMqigSGvLZP2NWwLi5qZy54mDpLSeUkwrtUoIIiUJIeDzET54dDI1RDdOIgJY5fFA8BYVVV4jPISJD8TTGJRGyNtvi5iEjtrDpwkqCJqTaUTiGEtUSJx3SO0YyYJanKAigZCGeP5g6f1mElMIjApLqiXIqUdo5CRbcc5AFiRasVMt0SNLJYmotyAdWExpyJUjahhMY5l8bwuVxuhKQvDTyEhfOIQUB4b5U7EnblZW/UFspRAEH/CFw+eO4D12NETpFFlMaDRX2ErGiG6P+biNDwVZOcHlBqVuN6h6W4DLQRlEpYXQCa1iD51IdocTQlJBB4Hygom1EIPMCpy09GJYTlJkKHnL6RO0qk30lRGqVIAnacyR9roMhxkIi1IaIRQqrlKOe8g4JV643Qrg8hFFdxM3GZEWAa8lBZ4oShBpjfcunUJJPatqzpgxY8abzP/T3p3HSHJfBRz/vrp7pnvumfV6L+/6SGI7Zu1sDsUhSgKBHAgHCLIRRxQBAZKIAIoSJwLFkUACJAhXBAkhFzkcKyEhFyQRDkQgsL2218duEmN8rne9u7Nz9Ewf1VX1e/xRtfZ4PbP2eKe9s573kUpd9evqevV6e6U3v1/9qjZUsXlPdhlpTWks9GgMJJx/9Su45f5pGg98n6TZIFp8mHG9h8Fem7q/nYfTn2WLvw/Nc+ba8+TDuxn0PEJPiJ1PgEdYLKKSgCso4iGypI7XaTI1nOMlYxA0GPKFbq9De+sVMLSVyZZHWPPpqDLYyonSgjwUkl5ON22Sto6VQ4Ty5AsEfR9coCAFC7MJzeYA2y6qkc48iMvaeF5ITEwrLFhIyscWTnRzXJ7jKAgGRggGRyi6C+SLM7giwOUdxlLlnbHPJS6g6EKeRE8oOMvrBx/vQCsUsqLgjpEmI7WQcwc24+XPIx8NaKc5UkBUFT6qiuu1kSAimtjBaz2fV7fnyBc7QMyeqABfGHBC1xVk/gB5DmmxSBwkhC5AFOLIZ7IREajQc0qujplej26WERRdoqEpXJbhd8pJPT3f0QoLhnsBnoKkDh0fXpJTNcTvRURD59BrTiPqoc6VvX6qSBixSAc/jB77zEgrZDbJyIMUDTz8LdvJIo/w0QJ/bo603cLzfPIgIC9aZcHpBSQDNbppjygWisWCQgqarkmuQn1ygLjV5ILROrMCMwsLpMUC29Mh8qiHbNpFXhvD1QukM1v2wMa18r6wyZP/G6s6KIoyQ89Duz3UFeBBIQUFOXkjIEgzulvHyLZt4aWXjHLovnt5JJ9k4pEmje4cnZlpekmC+AFa9NDUoUWM9joIdXaMjVDzJ9B2l87c/dBxpIEiDnIPtkpCN87xzj8POfxDOqQQhAQuIncJGhdkYwneoRYeCWMTu0i943QWmwT1cTw/xgsT8AaQIEKLqhdXIPJqJEPbyGSGmc5R5kkRD4YHYgiHKNqPMpILqf8UF9oaY4zpqw1VbA4UU2xqd5mvzXPRyy9m13mTnHPuGA+9YCsPPtJkV/YiXnLZZro/+C/y+VlmpoWHbm4S5R3qo9uJJ3zuH34ezotQp0w6ZXBxFnodIr9GMbtA1vHxdRQ3eg6Bp+R+l7x2H0eSS/H9YbweFOpot8pr+yJfiGo+GghJ5NNgBBbbdNPOY0+EAXAonic0Gh3yrIvWJykWBhA/w0lM2NiMpCnSaXIsmKaVOdJOhohSFHU2RRO0fR8XjSDiEdcSolRZbB/BH9/OrpGIoKf0hjy8ZpNwYQGXxGQCTh1F7ojU55Gog0NJexlDISSBEIgjTupc/IJXIyI0koAjzS6dvABXIHmXZGQTUX38saHxYGCEbHEWpw6v0yUaOofjvjBfD7h8bJhce7R7LebbM/hjEbXCp+ECOnVH7ju8TBhoB3hFyrFuQRGNk8bDxEXKtDtK1Osxm+Rkzmc69HC9NkNhzGaX0OlmFJSXIpT9j4L4A0ST24jSjKLZq3pClflIWFzo4hOCF7KQOhY0pRd2eP7F2zn/8hdR4KOqDE93yUOPtpdyeO9+vOMp0egOamMN0pkjtBcXOeQUKRyB5ixmjmB4gOExZaaXc+7zL2P386c4sPc2DnkBozsvY9xFhLpIvHmKWhJxLN5MtzVKmLZI546CU5womSp5XqDiEeSUDygIE3IPwm6KDjUIk0FcEJPkXdz8NLt27WCwUSN56Q4atRDfE6amRnngtoMEQwNcunsrnYeOcHz6IJJDGI8xumkzGdCca8LwKJO1CLeY4e0c4ZHaQe453iIerOGHws6BgijNGdp2Dudf+WIOfG+BPFM27byYWmMIPwzIs1G6CxnRjgbM98iOtgk3D7P/yCJh7OMciAdueAqvnZO3ytstiRPUh+ZYgmzejh9OMdQ9ihd5DJwzhuaOdCymuO0Anmf32TTGmDNJzuYhpj179ujevXuf9v57v/ktbrrxdsZ3DvFzv/5rhFH0lJ+Zuet/ye++meFXvYZofJzMC+j0CnxRksAHBT8oh3HTQ0c5euA+5pIhHuwktPKcCy4Y49xNg7R7BfsPNkEg6DkmR2rglENHW3TygsyBa6agMD47Q3jkCCpSTjRxSuBV198FIXEYEdcn6RWC86WcqOIJ6gmPSkpX2zhpsXV0nCKF+vmbiWdy4rkeNd/j+EyHdqEU4ggWFimiQYYHQx7q5fQaEbk6gkfvYXxRCQIf3xcCPPJGDxco0WJI5IUMj0wQxAniC935WTqdBTwR1FUzsZ2jKBQGJ+l5STmhxANxZcHtZg+CFEjUYO7cLeShcMm5w8QeeJ0c53scObSfbnuOKEiIegF54ihwgOB1cuIipj62k6xTEPoevThgLmqheQtNm7RbTcT1iAbHyAe3kRQxo62COPapj8QMXDiKS3zSdo/ZY22mVUkDYaQHwyMJ+WLG4vHDzD7yAzwvYHiyhh8Iw5vGeOErXlld//hkqkqxkNK7fwHXyVDn6BYZ9x/uoANQRBnp0BBbto8xUQ/40m2PcMnWMV5+wQRpL+Mbdx/hkok6m4MAeXihfLxpzzGrBXdNt/AiDy+resRbOYE6JkdCwjylNlYnHBkkSQbpHF4gm0yYr0ckhZIXjsmhhNEoQDOHNxDgDTxxBnuzm1GPAjxP6D28wMJ9R+m4BcYvOI+wkZTd2kB2rINmBV4jIt4xxOEHH+SeO+4g8T1CT5k6bycT288jjBOCMGT20cOgjtHNW5b7ytDc0b5zmk4r5UgzpRb6FApOlUYS4HmQb2swC3SygoePt2ipEvoetcgn9MpJc06VvLq3qfdvtxB1lB991xtpjCXLxl2OiNyqqnue9geMMcasaEMVm3fuu4Nbv/Yd3vT2tzI6Pt7HMyuleUHke085OUFVKZzSycrb4mihtOcXcSjZ/AJDtZg4TAjjGJc6JBSKouy9CiKfAspHToYebVV6uWOoFjLZiHGu7BHVQtETxxdQFXq9nKKZsuCU0fEBHpptIQUEgYe6Hjo9S92LISvIuzmM1SgKIcKDmQyGEjpO6XVyfFcgrRZe4hPUI/zBAt95hPVBauPDZN2cuYOLFE5xItQDgVjQ4Zg4ChgZScgzxWWOonC4qlgosozpgw/Qa7co8pwihygJAEdSH2Jyx3YGhxvk8z3yTkY0XiMvlPZ8Sp45et0es48eYnhiivp4g/pwjHYyvE6OPxITDJ2610u1nP3dPD5LnmbUGuW/gx9G+MHTGxjQwpEd6+AWe3iDEcF4ghc98UadBw7PMzEYMzX05IJIC0XTnHyxhw7F3H2kSS30iQOP4YEIv1DqSUAYn9mBClUFVbK0S1EUxAMDj90P9Gkfw5XH0NyVRW11ran4goR+NVmqlBeO6cUeR5pdji2ktHo5rhotGIgCcqccueMQ4w/P8/K3vpThydopIj+RFZvGGLN21lWxKSKvA/4S8IGPqeofn2r/1RabRZ5zfGaGqamp0ztRY8xZ4Yc/OMb0/mle/IYLiWpPvxi3YtMYY9bOurlmU0R84MPAa4GDwC0i8lVVPbBWMfwgsELTmA3koosmuGDbCP4qCk1jjDFraz1N03wJcK+q3qeqPeB64KozfE7GmLOYeII/uPJTlYwxxvTfeio2twAPL9k+WLUZY4wxxpiz1HoqNpebRfOkC0pF5G0isldE9h47duxZOC1jjDHGGPNMradi8yCwbcn2VuDQyTup6kdVdY+q7pmcnDz5bWOMMcYYs46sp2LzFuBCEdkpIhFwDfDVM3xOxhhjjDHmNKybKZqqmovIO4FvUd766OOquv8Mn5YxxhhjjDkN66bYBFDVbwLfPNPnYYwxxhhj1sZ6GkY3xhhjjDHPMVZsGmOMMcaYvrFi0xhjjDHG9I0Vm8YYY4wxpm9E9Un3TT9riMgx4MFVfmwCmO7D6Vi852a8MxHT4p35eDtU1W7ka4wxa+CsLjafCRHZq6p7LJ7FW68xLd7ZHc8YY8wT2TC6McYYY4zpGys2jTHGGGNM32zEYvOjFs/irfOYFu/sjmeMMWaJDXfNpjHGGGOMefZsxJ5NY4wxxhjzLNkwxaaIvE5Efigi94rItX2K8YCI3CUi+0Rkb9U2JiLfEZH/rV5HTzPGx0XkqIjcvaRt2RhS+qsq5zt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" 10.1\n", - " reward\n", - " \n", - " \n", - " 38\n", - " (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew...\n", - " 223.166962\n", - " 499.0\n", - " 10.8\n", - " reward\n", - " \n", - " \n", - " 39\n", - " (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew...\n", - " 162.472949\n", - " 316.9\n", - " 10.9\n", + " 21.427778\n", + " 59.3\n", + " 9.8\n", " reward\n", " \n", " \n", "\n", + "

80 rows × 5 columns

\n", "" ], "text/plain": [ - " name average max \\\n", - "0 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 57.051663 202.3 \n", - "1 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 75.768736 198.0 \n", - "2 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 56.496674 166.4 \n", - "3 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 11.074058 26.8 \n", - "4 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 36.042572 275.0 \n", - "5 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 188.234590 499.0 \n", - "6 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 220.743902 499.0 \n", - "7 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 186.998891 499.0 \n", - "8 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 152.903104 499.0 \n", - "9 (DDQN, ExperienceReplay_FEED_TYPE_STATE, reward) 147.719512 499.0 \n", - "10 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 55.912860 397.6 \n", - "11 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 41.026608 164.8 \n", - "12 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 39.898004 154.5 \n", - "13 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 34.858980 179.0 \n", - "14 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 37.738359 155.5 \n", - "15 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 213.458093 499.0 \n", - "16 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 205.934368 499.0 \n", - "17 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 196.119734 499.0 \n", - "18 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 223.166962 499.0 \n", - "19 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 162.472949 316.9 \n", - "20 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 258.565333 499.0 \n", - "21 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 269.299778 499.0 \n", - "22 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 154.370067 499.0 \n", - "23 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 141.921508 252.6 \n", - "24 (Dueling DQN, ExperienceReplay_FEED_TYPE_STATE... 168.225721 499.0 \n", - "25 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 37.997111 137.1 \n", - "26 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 32.311973 82.8 \n", - "27 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 27.884035 131.6 \n", - "28 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 48.784701 254.5 \n", - "29 (Dueling DQN, PriorityExperienceReplay_FEED_TY... 55.326164 243.4 \n", - "30 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 55.912860 397.6 \n", - "31 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 41.026608 164.8 \n", - "32 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 39.898004 154.5 \n", - "33 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 34.858980 179.0 \n", - "34 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 37.738359 155.5 \n", - "35 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 213.458093 499.0 \n", - "36 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 205.934368 499.0 \n", - "37 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 196.119734 499.0 \n", - "38 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 223.166962 499.0 \n", - "39 (DDDQN, ExperienceReplay_FEED_TYPE_STATE , rew... 162.472949 316.9 \n", + " name average max min \\\n", + "0 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 57.051663 202.3 10.5 \n", + "1 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 75.768736 198.0 10.3 \n", + "2 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 56.496674 166.4 9.1 \n", + "3 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 11.074058 26.8 5.8 \n", + "4 (DDQN, PriorityExperienceReplay_FEED_TYPE_STAT... 36.042572 275.0 9.5 \n", + ".. ... ... ... ... \n", + "75 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 37.436889 129.0 10.9 \n", + "76 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 18.428667 58.7 8.9 \n", + "77 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 32.824889 68.8 8.9 \n", + "78 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 39.005111 105.4 8.1 \n", + "79 (DDDQN, PriorityExperienceReplay_FEED_TYPE_STA... 21.427778 59.3 9.8 \n", + "\n", + " type \n", + "0 reward \n", + "1 reward \n", + "2 reward \n", + "3 reward \n", + "4 reward \n", + ".. ... \n", + "75 reward \n", + "76 reward \n", + "77 reward \n", + "78 reward \n", + "79 reward \n", "\n", - " min type \n", - "0 10.5 reward \n", - "1 10.3 reward \n", - "2 9.1 reward \n", - "3 5.8 reward \n", - "4 9.5 reward \n", - "5 9.1 reward \n", - "6 12.4 reward \n", - "7 9.5 reward \n", - "8 7.1 reward \n", - "9 9.2 reward \n", - "10 9.3 reward \n", - "11 9.6 reward \n", - "12 9.9 reward \n", - "13 7.6 reward \n", - "14 9.1 reward \n", - "15 11.6 reward \n", - "16 15.8 reward \n", - "17 10.1 reward \n", - "18 10.8 reward \n", - "19 10.9 reward \n", - "20 13.9 reward \n", - "21 16.0 reward \n", - "22 10.5 reward \n", - "23 10.2 reward \n", - "24 12.8 reward \n", - "25 11.7 reward \n", - "26 9.1 reward \n", - "27 5.9 reward \n", - "28 9.5 reward \n", - "29 9.7 reward \n", - "30 9.3 reward \n", - "31 9.6 reward \n", - "32 9.9 reward \n", - "33 7.6 reward \n", - "34 9.1 reward \n", - "35 11.6 reward \n", - "36 15.8 reward \n", - "37 10.1 reward \n", - "38 10.8 reward \n", - "39 10.9 reward " + "[80 rows x 5 columns]" ] }, "execution_count": 6, @@ -578,12 +291,12 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 11, "metadata": {}, "outputs": [ { "data": { - "image/png": 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MF9K96QAAGctedjbjnDHGWM/oyS7yZwCc2+rYuwDGKqXGA9gF4HYAIKJiAJcAGBO75nEiaj9NwRj7xrKiUVTs3ulkMaWE7nbDCIcAAEYoCNKP/yPJsgRkSGueNCSVdHrcOcBkjLFe12MBplLqQwB1rY79XSllxx6uBVAQ+/4CAC8qpQyl1F4AuwFM66m2Mcb6xqFd22GEQ7BNE0pJuNxuWEYUAGBbJkg7vo8kJQEhBFSUgNgnjFDCiS+/TlqUMcbYcenLST5XAXgr9n0+gLKEcwdjxxhj3yJWNArbtODyeKCkBOk6AnW1UFLCikahHW+AqWJhpA5ICUhL4UDTASd5yfElY4z1uj4JMInoDjh5hufih9op1u6vBSJaSESlRFRaXV3dU01kjPUAYVsQlgnN5QIUoOsuCNtGU001wo0Nx53BlDI2Y1wBRo2CUa3BsA1ISB6DyRhjfaDXA0wiWgDghwDmqSOf/AcBDEooVgCgvL3rlVJ/UEpNVUpNzcnJ6dnGMsa6lRQCtmmCSIOMZTBtw0DV/q8QDQWPO9sohYKCghIEGQGSdD+CZhBCCg4wGWOsD/RqgElE5wK4FcBMpVQ44dQbAC4hIi8RDQVQBOCz3mwbY+z4HW0Qp6R0xlqSs6MPANiGASMUhBmJQHMd39w+JRWkkiBSEFHAJXWoah+EsnmSD2OM9YGeXKboBQCfAhhJRAeJ6D8A/A5AKoB3iWgjET0JAEqprQBeArANwNsArlNKiZ5qG2Os+9QeKsNXG9YdVVnd5UZW/iBn/Uvbhu5ywbYM2IYBrz8Zbq/vuNogpYJQNjS/guYBlABgH8lsMsYY6109ttC6UmpuO4f/1En5ewDc01PtYYz1jEhTY/NM8K7Ylgmv3w/bNCAsC7rLBZfHC2Hb6GoXn84oqRA0Q3B53dAACAtQkiCl4gwmY4z1Ad4qkjH2tZjRaPNuPJ2xTRO2aULTdWiaBmHbaDAa4cvOhGVEIYXdZR0dUUpBKgEX6dA8BEgAgiCF4lnkjDHWB3irSMbY12KEQ5BSItzYAH96RoflnMk9TpbS609Gar9+2NW4F8nuZAzJLehwC8ijoaTTTR6vX/MACAGAglK8XSRjjPU2zmAyxr4W2zRhGwbKtm3utFxioEeaBn96BoQUMIUFT1ISXB7PcbdB2hICojnA1L0EuBUkuIecMcb6AgeYjLGvRQnh7C8uO88UKtl2TUqpFKJ2pE3ZLqpqQwgJkAIljuNUAK+0zhhjfYMDTMbYcZPS2VPcNo0uU4VSSlBC/CekgIKEKa02Zav3NSEabHu8I0IKtKgcAMhpEq+DyRhjvY8DTMbYcROmEwTaltllIKdapSW31m6FVBJCtp3cYwsJyzhSXtgSteVBdDScMmxFIds9qTjAZIyxPsABJmPsuIUaGwAAWQMLulzDUknZorPaEhZsaUMoAbvVLHRpSwhbQFgStiVRfSCIUIMBYbU/W70yUAlTGm3vqXiZIsYY6ws8i5wxdtxCDXXQ3S6QprXJULbWeoymhIIhDHh0D4Sy4cKRWeRKKUSCFsyoDWErCFNCWAq2LeHytp1t7nf5kexutRan4i5yxhjrK5zBZIwdNykEiDQQUfPWjx1RSraYb6OUhCFMEKjNNBwlASNiwzIFpC1hWwJSqg67yDuaYMQZTMYY6xscYDLGjpuwbZBGToDZxWLrSrac0e3W3EjzpDrnEiLH+Ldm2IJtSITDBoStIIVEJGBC2G2DSSkVoLXdCYjAGUzGGOsLHGAyxo6bkhJEGkDUdRe5sJvXqQQAoSSS3cnOuYTAMx4QpmQlwYhYqGg4DNsSUFLBCFuoKQu2bYdSbTeaJGcZJA4wGWOs9/EYTMbYcXO6yAmarsMyDUgpoGnt78gjhQBpR/6mjW/t2HoPcimdgFDXCZ4MHdBsJCW7IQwF25Ltfmgp2V4QqWLjMHknH8YY622cwWSMHZf6ikOIBAMgzRmDaUUiOLhtS4flhWi5VqVUMpbRbLWdY4tgUQEQ0N0E8gC1gXpnf/FWVMI2kUcOxsZ2cgKTMcZ6HQeYjLHjEg0FIS2rObDzpabCMtouFRSnpGgRBCZ2Xce/kxKoLgvAtuIBp3S6ueHs+NMUCkII2SbIlBJtF1qP3YMzmIwx1vs4wGSMHRdNc7rFNd3pEnd5PB3O2FZKIRoMthmDGX+slISQApu2b4dtqeb1LhUACQmpJJpkA5QmUNZwqN0tJ9sOwgSgVAfd54wxxnoSB5iMseNmRaPNASaRBmG33ZUHAEL1dTCCgYSAElCQoNhHkAJg2jbCARPCEvCneWPHnQBRKuXs1JMioCDaxLFKtjPJp3n5Iw4wGWOst3GAyRg7Lp6kpBZZQ9I0CLv9/cNJ0xAJBaG73QCcjCUlXKygIIQNYUsoBejuWOCpFCQEhLJhSxtKCQjIVuM0naWN2vaQK2f3IM5gMsZYr+MAkzF2XJQCfMmpzY81rf0MphEOo2L3LljhMFweJzMpndxkQl0StpCQUkEIiebIVTld6aYwYEoTEgpSOl3mDdGG2DJEABK625sRj8FkjLG+wgEmY+yYWMLJUjqTdo4c7yiDaYSCEJYFX0oaiAj10XpsqWk521wpQAgbChJSSlDsk0lCNQeTQjrjNG0lYAmBfU37EbJCTmazg7byRj6MMdY3OMBkjB21RqMRHx38CEBsFnhChElEznjJVltGkqbBNg0ociK9gBlAfbQOImFh9ogdRsAIwVY2pFAtOs/dmguWsuHSdLg1F6QSsIQFIW2UB8vxxf6tsbUzW2cwY+tgdrGFJWOMse7HASZj7KgppWBIA2Y0grryQ226pYkAaYtW10gnwIxtJWkIE7YUCItwc5nqSA0OByub7xEXsSPxSgAAfncylFLY27AXlrRgChNG2IY0W6Ypo1WpkA2Zzv7lnMJkjLFexwEmY+yoKSiYwsT+LZtgRkJt9h+3TRNGONTimBQSZiRy5HFsTGWaO635mCkMNEabAE0iNcfbfDxoBmEIExIJa2UqAdM2YUkLtrRghyWgqRYfZmZNKsTh/s5ITx6DyRhjvY4DTMbYUZNKwpY2wuEAbMNsM6nHikYRDbbcK1wKATMagcsbm+CjBHL8OUj3pgMANNIQFVFY0oJUCmWBMgQtpw4CnHJKNneAp3jSYFgWlADssIJtK1iwnT3RY/yDa+Aesh9S8SxyxhjrCxxgMsaOmlQSQgnYhgHLNKBky+ygLzWtxX7jSirs31oFb1I6okEXQo0mbFO2CAY10iCkwAD/AFjCgiEMhC2n+1wB0EmHLQX02DW6psMOEKzDOqJVgLQlVJIFLXZeCYKIekAu25llLjmDyRhjvc3V1w1gjH1zCCWcmdzCAiwLmfkFLc4TtZxUEwlaCNaFYUaiINJhRgVMIYEjqxtBIw2msCCigN/lhymM5m5tqSR00qEg4dbcsfJO4CptQNrO8ExKmEcuIh6EvsqF3k+HSKlzdvlhjDHWqziDyRg7alJJRKvqnEXRhYDucv5GtaVAxIoCRC1mkUeDJoxwFFIAUjjjISUktIQZ327NDVtaEBHApTwgEAxhwhAGZGx9y3RvBnTNuRdpgBIKSjgBphROnXG634A3pwmith+kjdhG5YwxxnpTjwWYRPQ0EVUR0ZaEY1lE9C4RfRn7NzN2nIjoUSLaTURfENHknmoXY+z4mWYURkUtpBDwJic3H68MVeDLhl0gIkhxJKCrqwihvOkgFJwljAzbhGEZLep0aW4MThsCZQPeFA1+dzIidgQHAwch0XYBddIA07RgWpazMLsd20Yyxg554ckKwTNsL5TOk3wYY6wv9GQG8xkA57Y6dhuA/1VKFQH439hjADgPQFHsayGAJ3qwXYyx42SbJpRlQ0qBjLz+zceFEs3ZRikllFIIhsOIhiwoxMZCAjBtC7ZqOSEHAKyQdAZcaoAGQkREIZRTD7Ve31IDUvV0pFAa9GQBlWLA5/I1nw59lQOjOhWu5CjAk3wYY6xP9NgYTKXUh0RU2OrwBQDOiH3/ZwD/AHBr7PgK5SxYt5aIMohogFKqoqfaxxg7dlIISGFDSInaSC0OBQ5hQMoA55x0NgQ3wyFsKP1f7KuyMNQ3GvDYzphJJSGFgqVZICS1qNeqB4QJ6EkEjTQoJaERtb9DDwEkNHhSJUxSSFZ++F3+5tMpw6ughAajKRV2SqjbMpjr16/PdblcywCMBQ8vYox9t0kAW2zbvnrKlClV7RXo7Uk+efGgUSlVQUS5seP5AMoSyh2MHeMAk7ETRDQURNWuXc1B5uHwYUTsCIJWEAQNItadHWqoR9hsghm2IF0SUgoIUvC6NJhCwEbb7SRJA1yxmJNASPekw1JtywHOjkGkKZBOkEJBa9WF7ko2Ydb7Ye4bCE/RV9220LrL5VrWv3//0Tk5OfWapnFalDH2nSWlpOrq6uLKysplAGa2V+ZE+Suc2jnWfvKCaCERlRJRaXV1dQ83izEW13i4EtFQEFIIHA4dhpQShjCcWd5KNo+DjASaoGwB07Zh2QICAlIquLw6pHAymVpCF7kwFEQELT4FiMjpcu+gLe40gqZRLDt5pJS0NJh1ydD9JpJG7APc0e5cpmhsTk5OEweXjLHvOk3TVE5OTiOcHp32y/RiewDgMBENAIDYv/G06kEAgxLKFQAob68CpdQflFJTlVJTc3JyerSxjH3XROxIhxm/+spyRIMBKFsgakUglEDQCsGtuZ3gUikQaTCCQQjTgC1s1IXqoJSAEAogQNgSyZ4UaKQ316sEIAwg4ZCzr7lSsGX7WUzAyXQ6YzSPsIM+BHfnQVk69BQTIOl03XcPjYNLxhhzxD4PO4wjezvAfAPAgtj3CwC8nnB8fmw2+fcANPL4S8Z634dlH6Iq3HY4TbipEZZhwIoaUJaAaUdhSgtu3VmbUkBAQUF4NVSgFqFAEEY4ihAaIUQUUkjoGsG2BGC2+tiRgOYFSDsSKjpLFRmwZcutKFsTaJnldKdFkDb2IDSPDVGfAtvQO+gLYYwx1pN6bAwmEb0AZ0JPNhEdBPBrAPcBeImI/gPAAQBzYsX/BuAHAHYDCAO4sqfaxRhrnyUt1Bl1iNiRtieVghEMInlgLlI8QUSMEIS0ocPZZUdIAaUU9tTvRtgKI1JhwIxasHUNUtjwZBNcHh26F1BRDVZQwZ1Csb3C2x8j43clwZJ2O2eOEFKAXEcCVtIVXH4TdtiDyN6BcOebPbZM0SulZRnVQbPbPkNzUjz27KmDGjoro+v6lKKioogQgoYPHx556aWX9qWmprZ5gqeffvrwVatW7c3Ozu48Qm/nGgBYtmxZ1m233dbpGKTVq1enzp07d1h+fr4ZP3bfffeVXXjhhYGjveexWrx48cAzzjgj0JP3iJs1a1bh2rVrU1NTU4VSCr/5zW/KLrjgguO676OPPtqvtLQ0ecWKFQe6o2033njjwGeffTY7KyvLBoAzzzyz8fHHHz80bdq0kVVVVW6fzycBoLCwMPr2229/1bo8AHz88cc7165d6587d+6wgoICMxKJaNnZ2dZNN91UOXfu3Mb27nvrrbf2f/3117MA4Msvv0wqKiqKAMBll11W88orr2Rt2LBhh6ZpsG0bY8eOLX7sscf2v/XWW+nxewsh6K677jo4b968xo7a1N57NhAIaPPmzRuyY8eOJKUUpaWl2S+88MLemTNnDgeAmpoat6ZpKl7Xxo0bt/t8PrVixYqMBQsWDNuwYcPWSZMmRT/77LOk+fPnDwWAiooKT0pKikhNTRVZWVn28uXL902YMGFsYWFhNH7fkpKSwyUlJbWJbYm/xh6PR1qWRaeddlrgt7/97aFj+b/W+meZkpIilixZcrg739/5+fnjkpOTBQAIIej888+vX7p0aUVSUpICgNLSUl9JScngyspKjxACs2fPrnvggQfKdV3Ho48+2m/x4sWFn3766bZTTjklAgBFRUVjVq9e/eXIkSPNzu6bqCdnkc/t4NRZ7ZRVAK7rqbYwxrpmSxtCiuZtGhMppUC6BtI0JKWmwZ+aBhGb6S0gYAkLCgq2FLA1BWVF4dYVpGVBWiYajUa4dS9M24YSBLPW6do2GztOL/pcSfB1eDbeLmennziryQclNLjTI0gpPgDDaGqx8Ht3qg6argzWblMAACAASURBVIEZvo778I9ReUPU3VUZr9crd+zYsQ0AZs6cOfTBBx/Mueuuuw7Hz8eXiFqzZs3uo71v62t27tzp+dOf/pTbVYAJAFOnTg1+8MEHR32vr8O2bTz88MPtDp3qKXfffffBK6+8sv7NN99MLSkpGXLBBRds6fqq3nHttdceXrJkyeHWx1esWPHVv/zLv7T5T9xR+cSf4SeffJI0Z86c4X6/f197wfTSpUsrly5dWgkAfr9/Uvy9CABr165Nefjhh7NvvPHGmnvvvTd34sSJoXPOOSf01ltvpcfvvWHDBt9ZZ5018pJLLtnUWZtau/fee3Nzc3OtN954Yy8AbNq0yTto0CArfv/EIC3xuhdffDFr8uTJwZUrV2ZNmjSpfNq0aZH4NbNmzSr84Q9/2HjllVfWA877ftCgQUbic+pI/DWORqP0s5/9LP+8884bvm7dup1dXdeV7n5/r1mzZteAAQPsxsZG7bLLLhsyb968IX/961/3BYNB+vGPfzz8kUceOXDRRRc1BQIB7fzzzx9299135/7617+uAoC8vDxzyZIlA/7nf/7nq+O9/4kyyYcx1seEdNayDFrBNuekEHC53ZBQ0EAgEKQS0DQdljAhoRAVBmxlQSXpoIx+gG3CtgxIYcMQJg4FD0J4o4DUYIcBs0lB2YCMov0UZoImBFCL+jbHs/3ZcGlH/k6OVqYjcjATpCm4ki1Al9/aLvIZM2YEd+/e7d25c6fnpJNOGnPZZZcNHjNmTPGePXs8+fn54yoqKlwAcNddd+UVFRWNKSoqGrNkyZJcwPll2tE1N910U0FZWZl31KhRxddcc03BhRdeOPTZZ5/NiN935syZQ5977rn0jtq1Zs0a/4gRI4rD4TA1NTVpw4cPH7Nu3Trf6tWrU6dOnTrynHPOGTZs2LAxl1566WAhnOD/r3/9a9rEiRNHFRcXjz7vvPNOamxs1AAnC3PzzTcPmDJlysinn346c9asWYXLly/PBICPPvrIf/LJJ48cM2bM6BkzZhTt37/fDTgZpkWLFuWPGzdudGFh4di33347BXAC1IULFxaMGDGieMSIEcX33HNPbmf1JDrrrLOCVVVVzcc7u/dVV101aNKkSaOKiorGfPDBB/7WdT3//PPp48ePHzV69Oji6dOnjygrK3MJITBkyJCx5eXlLgAQQmDw4MFj4z/D3jJ9+vTILbfcUv673/0ut+vSLf3+978ve+ihh/qXlpb6li1blvvII48cbF1m8uTJUV3XUVlZeUzPq6Kiwp2fn9/8x9yECROMeCauI42NjVppaWnK8uXL97366quZx3K/o+Xz+dQTTzxxsLy83PPpp58m7dy501NUVDQmfv5Xv/pV3o033jgQALZu3eo97bTTisaMGTN6ypQpIz///PM2fz8nvr/z8/PH/fznPx9YXFw8esSIEcXx8uXl5a7p06cXFRcXj7700kuHDBw4cFxX75P09HT55z//ef+7776bcfjwYf2Pf/xjv6lTpwYvuuiiJgBITU2VTzzxxIHf//73zYsbn3XWWY27du1K2rRpk/d4Xx8OMBljAI4slh6yQmg0WvaQ7ajZjoOBQ7Ck6SwTFJvlneRKQl2kHra0YQgDZtSGUeNs3+julw1hGdAVwVYCYTsCpQEknIk90gCk1XaCT2sKCi9rb+Id7YM251ovwp48tBopIw5DScCqS4GMeiFE593s30SWZeGdd95JGzduXAQA9u3b57vyyitrt2/fvm3EiBHNXVgfffSR//nnn++3fv367aWlpdtXrFiR83//939JnV3z4IMPHoxncp566qmDP/3pT6ufeeaZfgBQW1urr1+/PuXiiy9uBIDS0tKUUaNGFce/tm7d6j399NPD5557bsPixYvzr7vuuoI5c+bUnnzyyVEA2Lx5c/IjjzxStnPnzq379u3zrlixIrOiosJ17733Dvjwww93bdu2bfvkyZPD//3f/50Xb4/P55Pr16/fuXDhwua/MAzDoOuvv37w66+/vmfr1q3bFyxYUHPzzTfnx8/btk2bN2/evnTp0rIlS5YMjD2vnP3793u3bt26bdeuXduuvvrq2q7qiVu1alX62Wef3XA09w6Hw9rnn3++49FHH92/cOHCoa3rOuecc4IbN27csX379m2zZ8+uW7JkSX9d1zF79uzaZcuWZQHA66+/njZ69OjIgAEDOnzzPvnkk3nx133VqlVp8ePz588/KX78mmuuKWiv/CmnnDKio3qnTZsW3rNnT1edB20MGTLEuvbaa6vOOOOM0TfffHNFXl5em66D999/P1nTNBV/XkfbpoULF9Y89thj/SdOnDjq+uuvH7h58+Yug57nnnsu44wzzmgcP368kZGRIT7++OM2wX5r8T+s4l/xP04643K5MHr06PCWLVs6fc2uvvrqIY8//viBrVu3br///vsPLlq0aHBXdWdnZ9vbtm3bftVVV1Xfd999eQBw2223DTz99NMD27Zt237RRRfVV1RUeLqqBwCysrJkfn6+uXXrVt/WrVt9kydPbpHlHjNmjBGNRrWamhodADRNww033FD5X//1XwOOpv729PY6mIyxE5Qtbbg1N4JmEGvL18Lv9uN7A78Ht+bGwcYyCDsCsp0uaRlblshNLgRkEB7lQXZSNgINEYiQkzTUPTq0JB/ICEMqCV1zQUFCS3ISi9ICoAB3WssJPq29Rx/iMFXjDDm98/aHPDDrUpA0sB5KEkJ78qBl2xB2z3SR9wXDMLRRo0YVA8App5wSuOGGG2r279/vHjBggHnWWWeFWpf/xz/+kfKDH/ygIS0tTQLA+eefX//BBx+kzpkzp6Gja1o7//zzg4sXLx5y6NAh13PPPZd5/vnn17vdTjKvoy7y3/zmNxUTJkwY7fV65fLly5vHHY4bNy5UXFxsAsDFF19c99FHH6X4fD65Z88e37Rp00YBgGVZNGXKlOY0+vz589ukrr/44gvvl19+mXTmmWeOAJxu/pycnOYM15w5c+oBYPr06aFbbrnFAwDvv/9+2rXXXlsdb3teXp5Yt26dr7N67rzzzoJf/vKXBXV1da41a9ZsP5p7X3rppXUAcN555wWDwWDzL+y4vXv3ei688MKC6upqt2ma2qBBgwwAWLRoUc3MmTOH/+pXv6p6+umns6+44oqazn4u3dVF3trXWTf2tttuq7r77rvzr7/++hbjFp988sm8l156qV9ycrJYsWLFV5qmHVObpk+fHtm7d+/m1157Le3dd99Nmz59+ug1a9bsmDx5crSja1566aWsG264oQoAZs2aVbdy5cqsGTNmtB3/k+Bou8hb6+o1a2xs1D7//POUOXPmDIsfM02zi34b4NJLL60HnKD/jTfeyASAzz77LOW1117bDQCzZ89uSktLO+oPuHg7lVLUegve9p7HNddcU/vAAw8M2LFjx1EFsa1xgMkYA+BkMF2aC1ERRdAOQtM0HAocQmF6IUwjAremISoMeF1eSOmMt9Q0DSKgIRJSyBzsBijsZCUhkZzsRbDKD01Ph6RaaLFlhVw+DS6NYDU520d2Flw2oBHrtI3opzIxSg3vsJxSQNNWJ1njzWmC5rWRPq4MwVADpBjU4XXfNIljMBP5/f52ZzJ19ouvo2vac/HFF9cuW7Ysa9WqVVlPP/30vq7KV1VV6eFwWLNtm8LhsBYPcNvsKx9bjmrGjBlNb7755t726mpvEpNSioYPHx7ZuHHjjvau8fl8CnCyS0IIil0DIlLHUs/dd999cP78+fX33HNP7hVXXDF069at27u6pr3nmKikpGTwDTfcUDlv3rzG1atXp8YzrMOHD7eys7PtN954I/Xzzz9Pfu2114577NvXsW7dOv/w4cM7DNw6o+t6m+cLHH0g2Zn09HS5YMGChgULFjTMnz8fr7/+enpHAWZlZaW+du3atF27diWVlJRACEFEpJ544omD8eC2u9i2jZ07d/rHjx9f7nK5VOKyaNFoVAOcIQ+pqan2sQavCe9jZdt28/v4eNTX12vl5eWecePGRceMGRP56KOPWmRnt23b5snMzLQTJyu53W6UlJRULlmypH/bGrvGXeSMMQA4spe4ctaOjNgRqNgARisaBek6bCWgkRYbg+kscq6iGqStQEQQQoCkDtMTdXb3Ke8PGUiFUhIuzQVLWke6tTVnB5/OpCAZs8WPMFv+CI0IIIy2M9yVAqTpAukCenIUtd5KbNK2QEsyQbrosUk+3wRnnnlm8G9/+1tGIBDQmpqatL/97W+Z//qv/9rpDNX09HQRCoVa/GSuvfbamqeeeioPAKZOndpl8HHFFVcU3nHHHeWzZ8+uLSkpae6m3bx5c/KOHTs8Qgi88sorWaeddlrgjDPOCJWWlqZs2bLFCzgzhr/44otOu0DHjx8fraurc7333nvJgNNtXVpa2mkX5dlnn9305JNP5liWk2w8fPiwfjT16LqOO++8s0pKSatWrUrr6poXXnghEwDeeeedlNTUVNGvX78Wb8BAIKAPHjzYAoD40IO4q666qvrqq68eOnPmzDqXq/fzP//85z+T7r///oHXXXddu1v/9ZW///3vydXV1ToARKNR2rVrl6+wsLDD2cwrV67MvOiii2rLy8s3Hzp0aHNlZeUXBQUF5t///vcuu7yPhWEYVFJSUjBgwADzlFNOiRQUFNh1dXWuyspKPRKJ0DvvvJMOON3TBQUF5tNPP50JOFnvTz/9NKnz2ts3bdq04MqVK7MAZ+xyU1NTJwOMHI2NjdqVV1455JxzzmnIyckRCxcurF23bl3qa6+9lgoAwWCQrrvuusG33357m0lGJSUltR9//HFaXV3dMb8hOYPJGAMQG4MZ1CB0G8qjmmeTK6VgRwyQngypBABneSGhBOxGZywlFEDQYAkLXk8yDAqDlAY5Zj18Lh+itoRH9yJoNiFJdz5XXclH7q2g2oynFBD4g7YSk9Q4JCkfXtBfxSzxQ4zEMChJULYGcguEvsqBWZeMrJP3QSngn9p+vK99jKLDU6Fs2WNd5DkpHvtoZn4fS33dVVfcjBkzwpdeemnt5MmTRwPA5ZdfXv39738/snPnzg67vPr37y+mTJkSLCoqGnPmmWc2PvXUUwcHDRpkDxs2LPqjH/2oxTJK8TGY8ce33nprRSgU0lwul7r22mvrbNvG5MmTR73xxhupmqZh4sSJwZtuuqlgx44dSaecckrg8ssvb9B1HU899dS+Sy655KR4t+Gvf/3rQ+PHjzc6aqPP51Mvvvjinuuvv35wIBDQhRC0aNGiw50Fvz//+c+rd+3a5R01atQYl8ulFixYUP2LX/yi+mjq0TQNt956a/kDDzzQf9asWU2dXZOZmSkmTZo0KhgM6n/4wx/aZGXvuOOO8rlz5w7Ly8szp06dGjpw4EBzMD137tzGkpISfeHChbWtrzta8+fPPym+TFFWVpb9ySef7AKOdFPHy73++uu7AednOHr06OJIJKL169fPuv/++w8c73JMx6q9NrW3DM6uXbt8JSUlQwBni8Kzzz67ccGCBW1n/cW8/PLL/f7zP/+zxVraF1xwQf3KlSuzzj333LazGGPiYzDjjy+77LKaO++8s02wPX/+/JM8Ho80TVM77bTTmt56663dAOD1etVNN91UMW3atNEFBQVGYib4hRde+OqnP/3pkKVLlw6wbZt+/OMf15166qntrAnXufvuu6989uzZJxUXF2eeeuqpwZycHCsjI6PdD7nTTz99hFKKpJT4wQ9+0LB06dJyAEhJSVGvvvrqlyUlJYMXL1485PDhw+7FixdXLFq0qK51HT6fTy1cuLDql7/85TF3BVF37dPbF6ZOnapKS0v7uhmMfSuUNZXh/f9dD+mx4BoahYLC9/qdjLSIG6s//Quy0rIRsINI92bAlhYqQhXIswYhUBuFIaIYOCoToToTst4FafgR3NUfvlH74Uu1URupRb+kfqiN1CIrKavF0kI2bDyuPYN8DMAseX7zcRMW3qb3sUVzeiIvERdikMqHFk2CMFwI7hqA1FHlsJqSYDX4kTqiEppH4G36ABu0L/Afny2FJzWIU85MxZR/O++YXgsiWq+Umpp4bNOmTfsmTJjQ6bi4b6tAIKAVFxcXb9y4cXvrjNzRWr16deqDDz6Y11vLGvWFadOmjXzggQfK2hsDeTQ+/PBD/89//vNB69ev/9pL3rBvp0gkQi6XS7ndbrz33nvJJSUlQ45n3GiilStXZtx+++2D3n///Z2JE/6OxqZNm7InTJhQ2N45zmAyxgA4GUxIgoposW0abRyuKoMd9EKaFgSp5i5zl+bGoNTBMOolNOGGLUNOFjLiguYCCDZ8Axvg8xECWwYjKdcPzR9Fpi+zObg0alLQJEN4uf+zCFIIB1U5ntNW4VJ5EQgED9yYqf4dA2QeTJhwHxqMwCFnjHxSQR30JBOBnQOQMeEAouWZqN+VDW3sTuynMgDApnGrcHJwPJTscvIo68Rrr72WumjRosJFixYdPt7gknXtF7/4Rf9nnnkmZ/ny5e2ORWUMAHbv3u25+OKLh0kp4Xa71VNPPbXv69Z5+eWXN1x++eWdbvJwPDiDyRhDfbQeGw5vwMENQUSjBrzjwojWSORYKRjqTsO6/Z8gOasfbGkhw+ssKaeEQqRCwWwANA/gyQTsJkDzHZnYoBQQ/DIP3twmeDJa9gYFduXBtoEtY95AoRqElfrLAIBbRQl06AgihCT4oMMJSOt35EA1pUKRRMb4g4AkRKtS4evfCBHy4lnvX1CZ9hXOlDOgQcN72oe4uv4yfK9oNE45f+YxvR6cwWQngsSdc+IuuOCCuvhi59+2e69atSrtjjvuKEg8NmjQIOPdd9/d01P3ZF9PZxlMDjAZY9jftB//KPsHvF/moTZYB8+4MMy9LmREvfDoVagKVSElMwuWtJCdlAMAsAISkQpA9wBWEHD5nfUtyeVC5FAWfP0b4fK339tihzwIl2UheUgt7KAXWnoQH3jXIBlJ+L6aBgD4xP4cgWofTk0fgTR/y3HsjVsHQgkNGeMPIrQ/C5pLoi5/B97U3oGAwFx5ERrrdKRHUzBpfDamz/zxMb0eHGAyxljXuIucMdYpj+aBR/PCQx6AFCxhwaenIRwOwWgKQPP5ETGizgKXsbmPIgJnco8b8GaRs+2jAjToMGtS4c0+Mk8gNuEc8RVMlK3BsoCarTlwSx9cKWk4dfRUeMiFMhxCP2RhkMpHctn3QE1hGFkhZ5Z4WgTCZcKdFoEIe6EUIEJeINlEPvrjfHk2vPAiCxnQy/MhNQNK2PElanr7ZWWMse8sXqaIse+YqB2FaLV0j1ACBIJSQLo3A1JK+FJcMBtDMJUOj0qFWUfwNWZCCQVpKkgb0BO6w3UPoCcBepKJlKJKuFKdCZR20Iv6DYWwAz40ognv0AdoSD8EfdwuHM7fAuUPwQ76kBTORAOasFJ/BQdwCPnoj/RxZZC2htDeHAR398db5sd4QH8chwdtROrIShhVabCDSaABh/GI9kes1F9BCpIRhYHQyC+gBuxzRo1+g3tqGGPsm4gDTMa+Yz4p/wRfNnzZ/Fgp5WynaGkgAH53EoqzigEJSMuEqQR0ciHdkwEPuWEHgEilAmxACQ1KxALMJAJpOoJ78qC5RXO2UvPY8OU2QYQ9CFgmttJORBDFLtqD1AFBZAyvhTe3EaQpZCEDl4gLkd84AoHDyWjcXICUYVXw9AsgdWQ5Mn3Oii6uWOeLOz2MbUPfw/+4/o4QhZGncpAEHw7gEJ7xPYsGbx2kkl9rdxLGGGPHjrvIGfuOie8bHldXfhBlX26EcGlOV7YCpAlIQVBSItOXCU1zg2QsEUixvcSFhqYtzlbLKUWVIJeAsnWIsAdKHumO1jwC/sF1aNo+AGn147BwlB/RrUNRMWA1mrL3YahvMJILnWX/dLiRWz8cxpcFeGfMkxhnnA584SxL58trwve1qfi+ODI0UvNZWOt/G+NVMeaKHyMPOSAQBiIP82quRHIoHRjw9ba/Y4wxduw4wGTsO0QpBVvZsV14HLZh4GDVIZhp2Uj2AGYTEK1RgASgRGxRc2ccJbkBK+SMtYSS8BdWIbwvF1aDH0Z1GjSPjfQJB9rc1w55oHktWPXJ+LK6ES7Pfvw7TgepI2slK0kgTcF0h2DpBs7cNR9G/n647TC8uU1wpThB8Ye0FhlIw3jlBJ5nqtOwlXbgVDUV/tgA0RQkQ9XkwQrrUCrQMwHmxucyEKzqvs/QlFwbE+d1ulSIrutTioqKIkIIGj58eOSll17a195WiqeffvrwVatW7U3c9q0r8WsAYNmyZVm33XZbdWflV69enTp37txh+fn5zTO57rvvvrILL7ywxxbpXrx48cAzzjgj0JP3iJs1a1bh2rVrU1NTU4VSCr/5zW/KjncB8kcffbRfaWlp8ooVK9r+5zgON95448Bnn302OysrywaAM888s/Hxxx8/NG3atJFVVVXu+ELrhYWF0bfffvur1uUB4OOPP965du1a/9y5c4cVFBSYkUhEy87Otm666abKuXPnNrZ338SZ5V9++WVSUVFRBHAWJH/llVeyNmzYsEPTNNi2jbFjxxY/9thj+9966630+L2FEHTXXXcdnDdvXmNHbWrvPRsIBLR58+YN2bFjR5JSitLS0uwXXnhh78yZM4cDQE1NjVvTNBWva+PGjdt9Pp9asWJFxoIFC4Zt2LBh66RJk6KfffZZ0vz584cCQEVFhSclJUWkpqaKrKwse/ny5fsmTJgwtrCwsHlx9JKSksMlJSUtFr2Pv8Yej0dalkWnnXZa4Le//e2heLvj/0dt2yZd19XcuXNrf/nLXx7WdWei4jvvvJNy8803DwoGg5pSiq655prDt99+e3X85/rEE0/k7d69e3N+fr4NAH6/f1I4HP78GN8iJwQOMBn7DqmL1sGWNixhNR8L2SEEysNIcvtBSYA7BdB0IFVLg+lOBgQgYwGmrgGkw5ncowG+3CCU0BEp64fkoVXQvDbam0sT3yccAIbu+z6axn4Gr98LgtPlHdiVBxHxQBpugCQ8SgMEkJOaCulrgJ4wG/0r2oc8lYvxKMb79DH+qW0AAGygzThdnQrAWaS94aRN8AZ8kCiAUke97fbRC1a5kF5gdV3wKDUe7HJXoMS9yGfOnDn0wQcfzLnrrrua93iW0hkOsGbNmqNezLz1NTt37vT86U9/yu0qwASAqVOnBntr4XTbtvHwww+32cquJ919990Hr7zyyvo333wztaSkZMgFF1ywpTfv35mO9vdesWLFV+0t9N5R+cSf4SeffJI0Z86c4X6/f197wfTSpUsr48sU+f3+SYkLfK9duzbl4Ycfzr7xxhtr7r333tyJEyeGzjnnnNBbb72VHr/3hg0bfGedddbISy65ZFNnbWrt3nvvzc3NzbXeeOONvQCwadMm76BBg6z4/W+88caBKSkponVdL774YtbkyZODK1euzJo0aVL5tGnTIvFrZs2aVfjDH/6w8corr6wHnPf9oEGDjKNZtDz+GkejUfrZz36Wf9555w1ft27dTqDl/9FDhw655syZc1JjY6P+0EMPlR84cMB1xRVXDH355Zf3zJgxI1xRUeE6++yzi/Lz86358+c3AEBGRoZ999135z3xxBOHumrHiY7HYDL2DRe1o7Dk0cU5UkmYwmwuv/+Lz7F//5cwDQN+PRmkA+QC7BAAQdCkBmkT3GkEVwoghdM9DgBmQzLskAfudOd3WWh/Ntxp7e/UlzFxP9LHH8D2ia9iy6D3sdm/AS9qrzWf92SFnOAyJm1sGXwD66F5LbjTotBcRwLEK+QlOFudhgiiaEQAI9VwTJRjka/6N5dpQANWev6CQ95DTvZSfvu6yGfMmBHcvXu3d+fOnZ6TTjppzGWXXTZ4zJgxxXv27PHk5+ePq6iocAHAXXfdlVdUVDSmqKhozJIlS3IB55dpR9fcdNNNBfEt86655pqCCy+8cOizzz6bEb/vzJkzhz733HPpHbVrzZo1/hEjRhSHw2FqamrShg8fPmbdunW+1atXp06dOnXkOeecM2zYsGFjLr300sFCOG+mv/71r2kTJ04cVVxcPPq88847qbGxUQOA/Pz8cTfffPOAKVOmjHz66aczZ82aVbh8+fJMAPjoo4/8J5988sgxY8aMnjFjRtH+/fvdgJNhWrRoUf64ceNGFxYWjn377bdTACdAXbhwYcGIESOKR4wYUXzPPffkdlZPorPOOitYVVXVfLyze1911VWDJk2aNKqoqGjMBx980GaV/+effz59/Pjxo0aPHl08ffr0EWVlZS4hBIYMGTK2vLzcBQBCCAwePHhs/GfYW6ZPnx655ZZbyn/3u9/lHuu1v//978seeuih/qWlpb5ly5blPvLIIwdbl5k8eXJU13VUVlYe0/OqqKhw5+fnN3/ITZgwwUhKSur0P3VjY6NWWlqasnz58n2vvvpq5rHc72j5fD71xBNPHCwvL/e0t7d4fn6+vWzZsn3Lly/PlVLiwQcfzP3JT35SO2PGjDAADBgwwL733nsPPvTQQ80fXnPn/j/2zjy8ivJe/J93Zs6aPSEkIQsBkpCEHSJUBHdb0YooYtVaEAuIimjVVqu2eq1y61V/VtvbaquiWLXVoqBe91oRcQMEDBASWcKShZDt5Oxnlvf3x8kJARKIVrTi+TzP8HBm3u3MnMx857te3PLSSy+l792794g1xv/TiQuYceJ8y1lVt4pNzZv63D5iRgiZIbau+ZhAh5fg3jBmxMTSJUIRKHYwfGDpgGWBjKokFU2AGdVkWiaE6jMJ7U1Bc+u48ltIGNS7wkuxm/icrdgdklE56ZjCJEUmdR23p/lRXRHcBc2kH1eL5tZx57UherhDGcEAb3tf43HxDOfLs5hunc1Z8jSKGNTVJpUULm2bTV7TKKTcX4HoWEHXdd54443kESNGBAFqa2uds2fPbqmqqtrc2aL/fAAAIABJREFUvdTbypUr3c8880zG2rVrq9asWVO1ZMmSzFWrVrkO1+f+++/fE9PkPPLII3vmzp2774knnsgAaGlpUdeuXZt44YUXemB/LfLYtmnTJsdJJ50UOPPMM9uvu+663KuvvjpvxowZLccdd1wIoLKyMuHBBx/cXV1dvam2ttaxZMmStIaGBm3RokU57733Xs3mzZurxo4dG/jNb36TFVuP0+m01q5dWz1v3rwuf4pwOCwWLlxYsHz58m2bNm2qmjVrVvONN96YGztuGIaorKysuueee3bfeeedAzq/V+bOnTsdmzZt2lxTU7N5zpw5LUcaJ8bSpUtTTj/99Pa+zB0IBJR169Zteeihh3bOmzdv0MFjnXHGGb7169dvqaqq2nzBBRe03nnnndmqqnLBBRe0PProo+kAy5cvTy4rKwvm5OT0Wp/+4Ycfzoqd96VLlybH9s+cOXNwbP8VV1yR11P7CRMmlPQ27vjx4wPbtm1z9na8NwYOHKjPnz+/6eSTTy678cYbG7Kysg4xdb/zzjsJiqLI2Pfq65rmzZvX/Pvf/z579OjRpQsXLhxQWVnp6K1tjKeffjr15JNP9owcOTKcmppqvv/++0cs6RV7sYptsZeTw6FpGmVlZYGNGzf2eM7Ky8sjlmVRV1enVVVVuSoqKg7QLk+aNCmwdevWrr6JiYnmxRdf3Pzb3/4269DRvl3ETeRx4nyL8UV8hMzQAUE7PWFZUV9Ky7IIB3Wad0XIS9HRIxH8+7xopg0zEgZcCCGw9JhAJuluXZZWNABImpBUtguhRiVAV06PLlvRPlKCCU1aM28pK+hnprNZqeEU64SuNkKVpIzY06dsQjvqVjNqm0VmYQYM7bmNHTsZbdmE9yUh5V7kMaLBDIfDSmlpaTnAhAkTvNdee23zzp07bTk5OZHTTjvNf3D7d999N/Gss85qT05OtgDOPvvstn/9619JM2bMaO+tz8GcffbZvuuuu25gXV2d9vTTT6edffbZbTZbVJnXm4n8f/7nfxpGjRpV5nA4rMWLF3f5HY4YMcJfXl4eAbjwwgtbV65cmeh0Oq1t27Y5x48fXwqg67oYN26cL9Zn5syZbQeP/9lnnzk+//xz16mnnloCUTN/ZmZml4ZrxowZbQATJ070//znP7cDvPPOO8nz58/fF1t7VlaWuXr1aufhxrntttvyfvWrX+W1trZqK1asqOrL3JdcckkrwJQpU3w+n09pbm4+QBO1Y8cO+7Rp0/L27dtni0QiSn5+fhjgyiuvbJ46dWrRr3/966bHH3+832WXXXbYpP5flYn8YP4df+Wbb7656a677spduHDhAX6LDz/8cNZzzz2XkZCQYC5ZsmS7oihfaE0TJ04M7tixo3LZsmXJb731VvLEiRPLVqxYsWXs2LE9m0yA5557Lv3aa69tApg+fXrrU089lR7THPZGX03kB3OkcxY73pmP94gn+Oabb24aNWpU+a9+9aujXrHpaBIXMOPE+RYTsSL4Ij6S7cm9tgkHAmz/9BNCgSQSi/sRCZioXh3dGcEyDEwLpBUm0tqEu/9AIOqHCaAlSBT7fqdKaUU3zQmqWwJHjiGxIvAO71OkDeQ6cx4O7FxkTqM//Q5p25dc6A25ktw6Sa7en9VVL5LHAHLKJhzQxsRkX/5n2NIcWFb+0fHB/Abo7t/VHbfb3eMXPNyDr7c+PXHhhRe2PProo+lLly5Nf/zxx2uP1L6pqUkNBAKKYRgiEAgoMQH34GT3QgiklEyaNKnj5Zdf7rEGd09BTFJKUVRUFFy/fv2Wnvo4nU4JUe2SaUbzaPX0cD/SOHfdddeemTNntt199939L7vsskGbNm2qOlKfnr5jdxYsWFBw7bXXNv74xz/2vPLKK0kxDWtRUZHer18/46WXXkpat25dwrJly7b3NP7RZvXq1e6ioqJeBbfDoapqjwUN+ipIHo6UlBRr1qxZ7bNmzWqfOXMmy5cvT+lNwGxsbFQ/+uij5JqaGteCBQswTVMIIeSf/vSnPTHh9qvCMAyqq6vdI0eO7NE/ePPmzXZVVcnNzTXKysqCq1evTvjxj3/c9Ua+atUq94gRIw4QfPv162eed955rffdd98XdlX4TyJuIo8T51tMxIzg1/0Ejf11vi1p0ehvZEvNDkzTwjR0vC0tRIJhIoaOkALDa+LzeNnZugvhtKMlpGD4PFiGge7tQLELhCYBC6Htv03YU6NbYE82vm2Zva5LGhLDL/lQrOEe90Osdn9KOx7cuFBRGcxAEqQbK/LFtSUnuk7GftIEtijbyN0lwOM7pI2BwTO2pWxzbP9O58E89dRTfa+++mqq1+tVOjo6lFdffTXtlFNOOWwkdEpKiun3+w94NsyfP7/5kUceyQKoqKg4ovBx2WWXFd566631F1xwQcuCBQu6zLSVlZUJW7ZssZumyT/+8Y/0yZMne08++WT/mjVrEjdu3OiAaMTwZ599dlgT6MiRI0Otra3a22+/nQBRs/WaNWsOa9Y9/fTTOx5++OFMXY8qG/fu3av2ZRxVVbntttuaLMsSS5cuTT5Sn2effTYNotHCSUlJZkZGxgFvYV6vVy0oKNABYq4HMS6//PJ9c+bMGTR16tRWTfv69T8ff/yx69577x1w9dVXN33tkx+GN998M2Hfvn0qQCgUEjU1Nc7CwsKe69ACTz31VNr555/fUl9fX1lXV1fZ2Nj4WV5eXuTNN988osn7ixAOh8WCBQvycnJyIhMmTAgefLy+vl6bO3fuwNmzZzcpisINN9yw7+9//3vGBx984IKoIPzrX/8699Zbbz1EOL311lv3Pvnkk5mxF6RvI3ENZpw430Le3f0u38v5HrqlEzIPfN6vaVxDR9CLp1qSnzUApIW0TCK6jlfvIMWWht8wafd30NrkxYw4UGx2ZFDHDAYINOwhJakcMxTAjBjoHSlIQ8We7kdLiN7TtcQwHMbSY+nRyHOjMyIoJ5KBrhqsFuupkKOiVYMM0P1g16K+n0ci3LKPljWrSCgsYkXuWk7dnQKaSmK/XOrfWEb2aT9E6Xwo27Ax03MZ9n2ZWAkSaR0FDWZif6Mvkd9faLyvmEmTJgUuueSSlrFjx5YB/OQnP9l3wgknBKurq+299cnOzjbHjRvnKy4uHnbqqad6HnnkkT35+fnGkCFDQuecc84BaZRiPpixzzfddFOD3+9XNE2T8+fPbzUMg7Fjx5a+9NJLSYqiMHr0aN8NN9yQt2XLFteECRO8P/nJT9pVVeWRRx6pveiiiwZHIhEBcPvtt9eNHDmyV78Pp9Mp//a3v21buHBhgdfrVU3TFFdeeeXewwm/P/vZz/bV1NQ4SktLh2maJmfNmrXvlltu2deXcRRF4aabbqq/7777sqdPn95xuD5paWnmmDFjSn0+n/rnP//5EK3srbfeWn/xxRcPycrKilRUVPh37drVJUxffPHFngULFqjz5s1rObhfX5k5c+bgWJqi9PR044MPPqiB/WbqWLvly5dvheg1LCsrKw8Gg0pGRoZ+77337vqy6Zi+KD2taejQoYcIjjU1Nc4FCxYMBLAsS5x++umeWbNmHeI6EeP555/P+MUvftHQfd+5557b9tRTT6WfeeaZh76RdhLzwYx9vvTSS5tvu+22Q4TtmTNnDrbb7VYkElEmT57c8dprr3W5icTcWGJpin70ox+13H777Xsh6qf6+OOP77jiiisKvV6vWl9fb//9739fe/bZZx+yppycHGPKlCltjz322LfWF1N8m9/sKyoq5Jo1a77pZcSJ87Xzz53/pCK7gs/bPmdzy2b6ufpx1uCzAHiz9k30sEnHRkH/zDRGDR7I5x+vwOdPxlcGZsTEU+kjVdtHi8+HlAm4XU6Mdh+JhTmEW/aRPHQ4vu1BPJslVijqG59Y0oA99ZCX9AOQUuIRXl7g/zg3MoUUPQWzrZW6pD38Lf1dEmUC1xg/jSZr18EMRQVRR/qhAmbE00Zobz0JhUUoNjvh5r20fvoRAJsLOxgUyiGvYCwtn6wEIOeMqQhFwQgG8O34HL3DRBHnUzC+ntNnnIs7udfA50MQQqyVUlZ037dhw4baUaNGHdYv7ljF6/Uq5eXl5evXr686WCPXV1555ZWk+++/P+vrSmv0TTB+/Pih99133+6efCD7wnvvvef+2c9+lr927drqr3ptcf7z+O///u/MxYsXZ65atao6MzPzS/1dfdNs2LCh36hRowp7OtYnE7kQYogQwtH5/5OFEAuFEKlH6hcnTpyjgylNLGmx17+XiBnB2xLB7wmjWzoBPUBE1wmGQ3iDfjxNbUgJPk8zofYwRpuCaQSJBAMYho6l6ah2gdAiRDrakZaFNA2kNJG6jeThe6K1xd0RpBXNWdlRlXPomkKSYJtJkCCNahM+zYe0QNEMGmwtOKSdy62L0TvADESrAin2zryaPRCo24Vvx+cIBC2frMS7rZqEgUNw9s9hRP4pVI42+DApGj2fXDoC0elb5d22hcDuHYTNfXjL3kOoxtHRYH5HWLZsWVJJScmwuXPnNn1Z4TLOkbnllluyL7rooiGLFi361uc/jNM3fvnLX+6rqanZ/G0VLo9EX03kS4EKIUQR8BjwEvAMcNbRWlicOHF6x5QmETOCJ+IhPzmfvZVB6kU7mUNdeAJenHoCRgRM3aJjXwMdzT4iYYuO6iYcSjZWsBXpUjEjBsJhIhDYEpOxIhGkZVL/qsQKJ+LK3YXqNNHcEbyfZ6G3JUQXIHoQ2Cx4OeVVzuJUrvHNgSSTx7QlVCgDGRcsZoL9JDRNxbB3VgKyQHFEzenSOtBMLi2LwO6odbHts9XYklPx79qO7olaxXJGj2e7+D/y7DmceOpZBBvriHS0E2nZh+Z0kzpiHI/kvUqRrlAuC4725TimmTZtmnfatGmV/+44P/zhD70//OEPvxbT6zfFJ5988qU1j4sWLWpctGjRAVHD3SvnxDj33HNbY8nOjybfxNxLly5NvvXWW/O678vPzw+/9dZb247WnHGOHn0VMC0ppSGEOA/4nZTy90KIL126SAjxM2AO0cdMJTAbyAH+BqQDnwI/kVL26sQbJ853FV9bCCNkEbEiaIqGQ3WA5ifgC7N+3R6CHaCkGpiGghG2iMgIQriJhJrQpR+n2480gghbJpbwITojwc1gCt7qHJx5NchOv3LFJRFK1I1G0UwcWe2YQTtJJT08YwS0qm28rrzDeKWCp+XzIEClAJdLw7SUaK5N0ZVaE6GAokH3NJVWJIIR8JE+ZgIRTzuGp42krHz8e2pJGlxCQmERQggWWJejoiIU8Gze0NXfnVdIUlEpF/svRmnsh5Eb12DG+XbSvXLOd2Hu6dOnd0yfPv0LpwmK859JX6PIdSHExcAs4JXOfV/KuV0IkQssBCqklMMBFbgIuAd4QEpZDLQBP/0y48eJcyzyedvnfFK7lu3r99FY68G/C/ZUdou3MBQM08AyLRzCRUTXsVSDsN9EaDZsTheGFsYIBqImcD2MhYbLlU6qK+rtojh01AQPWALFrmNLr8OWsj/uxF3YTMLAVpJLG3tMgA7w08ClfC528LT7eQAuTz2PiQmpqMKH1C0MX7RSkACkaaCGd4MiDxAwfbWf0/zxe4RbmkgqKsWhOPHUbCLn9HNIHFSCokbfi+3YowKmqpI+bmJX/4T8QsJtLagbtqDuTUIPK8dcovU4ceLE+U+nrwLmbOB44G4p5Q4hxCDgr//GvBrgEkJogBtoAE4F/tF5/Elg2r8xfpw4xxR7/Xtp3LcPfyBIdVM1ZthCN/a77ehBA0/Ig24ZOISdkB5BdQMJOuFwGMuQmGYYaZgI00JxOTEjFlgCmxJ9V1SdBloChOqLscI2nFmtKOp+s3VfclQKBYr1wUwLnM0vk6+kUBsAUiKUCKY/BCIqYOo+D+0bP8LSW1CCDUQaW4FokJCvNmoNC9TtQgiBsExARv/fSw47RbPhyMwifdxEbMmpEA4TttppG7oKzRU+ZhKtx4kTJ863hT6ZyKWUm4lqHWOfdwC//TITSinrhBD3AbuAIPAmsBZol1LG1CV7gEPKdcWJ813EsAyCRhDd1AkEA/jCQcyIJKKHo+l+pCSwp5Y9zhDuFDeWGibJnYZUJHrYR0RxIlEgMYFUVyJWOIBQwDIkdFqOpYRIa9S/UnEEcRfUoiW6QQ9GM6vbEw67RjMs6YgEWJuyluM93yPbnsEeuZv+ZjKpQkHIMKgCoYItRRBsNIh4Wqj7oIV+ZU5EZ6SP1HWQFq6sbBIKh6J3ePB1tJBaUHzY+SOeVsL79pI6fCwA7ojCW8c3Y8dHqT4E4hrMOHHixPlaOayAKYSo5DB3ZinlyC86oRAiDTgXGAS0A88DU3oavpf+84B5AAUFcef9OMc+29q30Rxsxmz009JmYaSoGCELX8SPb4sgIcuHYlrofh/+iA/LbqG1eNFtgkjQQySlAA0HUlNRhYbub0PNTESGLETnHUDqKv5tWbgLmtGSa0AIdK8dzWhHmhI18/ACprQg6PLxqVJJnpZPa4LkKe8yTndP4CThRBE6qk2CCqoDHCkZZIz7Hh3VazGCfhRbNE+1Yrcz4MQTIRKAlDTMSBibzdGr5jKGO7cA94AClM4ygFiSc9vPwGjPJ5IWOioazGVbl6W2Blu/slzC6a50Y1rRtPYjt4wTJ06c/3yOZCL/IXAO8Hrn9uPO7VX2m7O/KKcDO6SU+6SUOvACMBFI7TSZA+QBPZZdklL+WUpZIaWsyMzsvZJInDjHCt6Il7ZwG2YkTCTsRzcNrLAgFAkTrPPTtmE3DmHDnaIQ8vkRERPDH8QKhzGNMEZYR4qoF6Ki2bGnZ6IoKmqijJrRAWEzSR6+G3u6P5qj0rIQAoyQhhnq4TYhJVgWkQ5JuFUiTchW+nOTuJpB+kAytFROTpjA95zDQYJwOKKVgdSoiRwBznQX7jQ77Tv20L5jM5bZqU419c6alBJVVcjsPwiHK+mw50jRbPuFS8AI+bGqqlEaLMyQ7ahU8mkNtmrZCdn6V7X1RVhVVXVcaWlpeWy75ZZbsr/yL9aNp59+OuVozxHjoYceykhLSxtVWlpaPmjQoGH/9V//9aXL5FVXV9uLi4uHfVVre+WVV5KSkpJGx877xIkTSwCuv/76Af379x/Z/Zo0NzerB7cvLS0tX7ZsWRLsv4ZFRUXDhg4dWn7HHXdkmWbPWWqWLl2aHOvvdrvHFBYWDi8tLS0/6aSTinJzc0fs2rWr6zdz6aWXFtxyyy3ZsbnLysrKBw8ePOyGG27I6ek7dF9TT9x0003ZRUVFw0pKSspLS0vL33nnnYQzzjhjSGlpaXlBQcHw7mO99dZbCRCtXKNp2th77723qw7syJEjS0tLS8tzcnJGxK5vaWlpeXV1tT03N3dEbPzS0tLyyy67LP/gdXQ/xwMHDhz+/e9/f8jatWu7KieNHz9+aGFh4fCSkpLyQYMGDZs5c2ZB9/rv27Zts5122mlDBg4cODwvL2/EzJkzC4LBoIidEyHEuGeeeaYrSe4pp5xS9Morrxz+hhOnTxz2hial3AkghDhBSnlCt0M3CyFWAXd+iTl3Ad8TQriJmshPA9YA/wIuIBpJPgtY/iXGjhPnPw5LWngjXlIcfU/03Z2gEaQgqYAGYxtNviaU1HxEusQfNFFVBTNigKljGGEsLYDp1TvTD7mQ0sCI6KgiKjBigVAVFKFgWEZX3WCpq2juaAk9uy0dKSUyBKYlQRhRga9bZI+ytxWkREnJwJLRQ6obVDsIBHbNxmn2EVE7hIDoXiMqYAqBf8/nmIFG+g+yY0ZMwn4NMxTAu3sHwbqdZI0pR+gB8LWC1VkA/YsgJWHpx1/8ERnu8qhAfAzQWy3yo4Gu63TWTPYcsfFXxDnnnNO2ZMmSXY2NjWpZWdnwH//4x21FRUX61zX/4aioqPD1lCS+tzrbvbXvfg3r6uq0GTNmDPZ4POoDDzxwiFKle1T1wUnc/+d//ifzmmuuyV++fPmO999/3/3JJ58kPvbYY1VvvfVWYmzujo4OZcSIEeXTpk3zHG5NB/P2228nvPHGG6mVlZWbXS6XbGho0MLhsIilC+otaf6SJUvSRo0a5X/++eczfv7znzcDfPbZZ1sg+gKxZs2ahCVLluzq3mfFihU1OTk5h61i1f0c/+Uvf0n7wQ9+MPSzzz7bNGDAAKNz3u0nnnhiIBQKiWuuuSZ3ypQpRatXr662LItp06YVzZkzp+naa6/dZhgGl1xyycCrrroqb/HixbsBsrKy9HvuuSfnkksu+dp+598V+hrkkyCEmBT7IISYCBzeZtYLUsqPiWo/PyWaokgB/gzcBFwvhNgKZBDNtxknzree1lArHzd8/KX7R6wIilCIREKYuhWVlYQkGAqTmpqIFTaxdJ1IOACWganrOPslYDN0NAuMsImhm6CAZUaDdWyKjbAZRhEK3pos2tcPJLwvWqZXCIFAgAKGpXN/wQv8STxF2NBZpD7I/yqLEaEIRPSoYOkA1Qm1SbW8abyHFBIhTPDsgVCnxVfRsDkDXTKqUCRCWmjJKWRVDCR9SDHhpkb8O7dhGQYi1tCIQMSP+IImbpvmYHVFkH9mfRYVlr+ogPotoqWlRS0sLBy+YcMGB8A555wz6P777+8H4Ha7x8ydOzevvLy87Pjjjy+pr6/XADZt2uSYPHly8bBhw8rGjRs3dN26dU6A6dOnF86ZMydvwoQJJVdddVXeQw89lDFz5swCiGqnfvCDHwwZPnx42fDhw8vefPPNBIhqmGbMmFE4fvz4oXl5eSPuuuuuLs3jH/7wh4ySkpLyoUOHlk+bNm3Q4cbpTnZ2tllQUBDevXu37UhzT5s2bdD3vve9koEDBw6Pfe/uVFdX28eNGze0vLy8rLy8vCymbZs2bdqgv/71r10FQ6ZOnTro6aef/nJvgV+S3Nxc49FHH61dvHhxf+sLptK64YYb9u3cudPx8ssvJ11zzTUFDz744C6Hw3HAH0pycrI1YsSIQHV19WFrux9MXV2dLT093XC5XBKiZQsLCwuPKOg///zz6ffdd9/uxsZG244dO766MqrdmDt3btvkyZM9jz32WPrBx5xOp/zTn/60p76+3v7hhx+6Xn755SSHw2Fde+21LQCapvHwww/vXrp0aYbH41EAysrKAklJSeaLL76YfDTW+12mrwLm5cD/CiFqhRA7gD927vtSSClvl1KWSimHSyl/IqUMSym3SynHSymLpJQzpJS91qGNE+fbRkAPoFtfThGjmzqqULELB9K0wAKpWiR421AIY4YNpG5gdiZJtyVmYktKQhom6AamHkQKgRDRsoztqod/KatosVpRLBW9Pfp8DzdHrUKfs503lH/xmVrJizkrkELSprbzO/sjAHTgBSykJUCNJkv39Wun7Z1PKV3eSstHL1H32tsQ7oCYYKjaUEV7pzYTMsYWkj0uE1QbqHYCzY101GzEkZFJznFjohpHISASQkgzqsXsK1bUvH5G/TAu2HYlus99rCgwu+ocx7a//OUvaRkZGeYDDzywa9asWYP+/Oc/p7W3t2s33HBDM0AwGFTGjh0b2Lx5c9UJJ5zgvfnmmwcAzJkzZ+Af//jHXZs2baq6995791x55ZVdDu3btm1zrlq1quYvf/nLnu5zX3HFFfnXX3/93o0bN1a9+OKL2+bPn18YO7Z161bnihUralavXl113333DQiHw2LNmjXO++67L2fFihU11dXVmx955JFdRxonxueff24Ph8PKhAkTgkfqU1VV5Xr77bc//+ijj7bce++9A2praw8QbAYMGGCsXLmyZvPmzVV///vft//sZz8rAJg7d+6+J554IgOiQvratWsTL7zwwl61WLG666WlpeU33XRTl9vAww8/nBXbP2HChJKe2peWlpZv2rSpRyGvvLw8YlkWdXV1X8ifV1VV/vjHP+689NJLhwwePDg0ZcqUQ+pZNzY2quvWrUsYPXp08Iusadq0aR319fX2wsLC4ZdeemnB//3f/yUeaT1bt261NTc320455ZTA1KlT25588slDBMCeOOmkk0pi6+mrW8SYMWMCW7ZscfZ0TNM0ysrKAhs3bnRWVla6Ro0adUDZzvT0dCs3NzfS/bvfdtttDYsWLTq0PFmcf4sj/qBFVJVQJKUcJYRIJlq/PK5KjhOnD0gpMSwDQxpfOpBZt3ScqhMbNgJGEC0CILGpJrq3AyEMHJn9MMIeNGcizqTon7UtJRU94icxIRWHSwMv2JJgy54wG3O3M8hVgIZKwqB9qK4wiiNqpdoitlKpVEVfPwXkRdIZFRnDqwnvcIZ1EsfpIxBWA1IKtARw9lP4yFdNXtP+91UzGIoKemao00yuoogA7mxJcG8ze9/9hP6libgHZAFgGVEBUktIilb0CeoIyweqDWmGwDyMgBn2gd3dZcIX4QhWWCewZxfY8zByU5HWsVGJrTcT+Xnnndfx3HPPpf3iF78YuHbt2k2x/YqiMGfOnFaAyy+/vOX8888v8ng8yrp16xJnzJgxJNYuEol0JaE6//zz2zTt0EfDqlWrkj///HNX7LPP51Pb2toUgO9///vtLpdLulwuIz09Xd+zZ4/2xhtvJJ9zzjltMfNnVlaWeaRxXn755bSioqKk2tpa5/3331/rdrvlkfpMmTKlPTExUSYmJhrHH398x8qVKxPGjx/fJVREIhHx05/+dODmzZtdiqKwc+dOB8DZZ5/tu+666wbW1dVpTz/9dNrZZ5/dZrP1rnT7qkzkPfFlfYQnTpwYLC4uDi5YsKCp+/41a9YklpWVlSuKIq+99trGioqK0CuvvGLr65pSUlKsjRs3bn799deT/vnPfybNmjVryK9//es9CxcubOmtz5NPPpk+derUNoCf/OQnrT/96U8L77jjjkPOy8H0xUR+MEc6X7HjUkqEEIc0Prj/mWee6fvVr37F66+/fkRBOk7fOaKAKaUnIjijAAAgAElEQVS0hBALgOeklB1fw5rixDlm+Neuf5HkSMKwjD4l+24LtZFsT0ZVOtP2SEnE1HFrbpyKA5ISiCQbGK2tmKEglmGgJdjBqaI5UjCs/fdp1e5ACAPN5UJ23mPNoJPSvcfTz+lmUGYSwb0p2FKCaO79RbNOk5OppIoUKxGP6uOUYAk5VhHDfMPQ3IL1+hoGoJARKcDWKZacmng8wR/5sfb6iHhspAzRoGXz/oCdGNICCWYgTMO6MEPyBgCQPKSQxKw81P5Z0FGP4gsjLA9WkowKur0EQQAQbANFAVtnxJIEQ3Wiawae/LUMSRpzzGcpMk2Tmpoap8PhsJqbm7UhQ4b0qC4XQmCaJklJSUZvvpyJiYk9SvNSStasWVOVmJh4yNnsbppVVRXDMMThHu69jRPzwXz77bcTpk+fXnzeeed5CgoKjMP1EQclaD348913353Vv39/fenSpTssy8Llco2LHbvwwgtbHn300fSlS5emP/7447U9fe+jzebNm+2qqpKbm/uFhKwYiqKgquoB+76IcNsbmqZ1lfccOXJk8Kmnnso4nIC5dOnS9ObmZtsLL7yQDtDU1GSrrKx0jBgx4iu3Rq5fv949bty4QE/HDMOgurraPXLkyPrMzExj+fLlad2Pt7a2Ki0tLdrIkSND7777bpdA+ctf/rLh7rvvztE07Ri/W3x99NVE/pYQ4kYhRL4QIj22HdWVxYlzDOA3/Ph1P6ZlHiBghnw+OpqjSgdfWyshX9S6tXbvWhr8DV3tGnd4COyWKELB0k2EaiFsFtLvR7E7kHokGvENvfsZymigkWUqSF0j7bjtFPdPQhoqwd3pGL6opShEmM2iBicOHJYdE4N8UsgWCexWd/KG858sUh/k1cRV/N+Az1A0C8UuCFohGkNN7Hv1A8xwCNVpx7ujHtNSO30wOx/4lgHhDlzZGWSPLyB/QkbXEm2dAUZIugRSYUYABYRAWBaivYNDJUUZdSzt7qMpJaoCNcMlywZ9isXR8b9Md6Ubjf5G21e1pbvSv5SAAXDnnXdmlZSUhJ588sntP/3pTwvD4bAAsCyLxYsXpwE88cQTGePHj/emp6dbeXl5kccffzwt1ubDDz90HW58gEmTJnXcc889XSbMDz744LB9zjzzzI6XXnopvbGxUQXYu3ev2tdxTj/9dP/555/fcs8992Qdqc9rr72WGggERGNjo/rRRx8lTZo0yd99LI/Ho+bk5OidJuWM7hHb8+fPb37kkUeyACoqKkJHOgdfNfX19drcuXMHzp49u0k5Qiqur5MNGzY4Kisru0zI69atc+Xl5fVaunnDhg2OQCCgNjU1fVZXV1dZV1dXuWDBgsYlS5Z85XLCE088kbpy5cqUyy+/vPXgY+FwWCxYsCAvJycnMmHChODUqVO9oVBI+cMf/pABUeHzqquuyr/88subDn5ZOf/88zs8Ho9aVVXl/qrX/F2lrz4fMX/Lq7vtk8Dgr3Y5ceIcO0gpCRpBXJoLiTzALNO8ZyfBDg/J/frTsLUapzuB/GEjCZthTLn/AdjRFkAGFIQQWBETZHQcaVkodjtm0N8ZlAO6aWDXDnSpEoBE0hHugJAD39YsXLmteNoVqov+yYnjrC7/xA1iE/9UVpIvB3Bm60SWZ7yLG42kJBsfyzVsV5pJtVKYsXMsab5ssElsSYK1gS38s/k9Lk0di+pyEm7uoH1jDe7vZaOmd3epkhBoQW9uwJmioeI8cKFCQletBQGGAZFOzYxloXj8mMmJoHTTUJkGYMIhQqRgUkchI9unoqvGUUlT9E3krIz5YMY+n3rqqZ758+c3P/XUU/3Wrl1blZaWZv3jH//w3nzzzTkPPPBAvcvlsjZt2uQaNmxYdlJSkvnCCy9sB3j22We3z507d+A999yTYxiGOO+881qPP/744OHm/vOf/7x7zpw5BSUlJeWmaYoJEyZ4J06cuKu39hUVFaEbbrihYfLkyaWKosjhw4cHli5dWtvXcW6//fbGioqK8rvuuqvhcH3GjBnjP+2004rr6+vtN954Y0NhYaFeXV1tj41z3XXXNU2fPn3IsmXL0iZNmuR1uVxdP5b8/HxjyJAhoXPOOedLX8uHH34467nnnut6W1q+fPlW2O/vGNt/0003NcyePbstdg0NwxCqqsof/ehHLbfffvsRTclfBb2t6eB2HR0d6sKFCws6OjpUVVVlYWFh+Mknn9zZ27hPPvlkxllnnXXAOBdddFHbJZdcMvjee+9t6K0fRH0wY8J1WVlZ4MUXX6w9uE3sHAeDQaWkpCT4xhtvVMciyAFmzpw52G63W5FIRJk8eXLHa6+9thWi2t1ly5ZtnTdv3sB77703p7W1VTvnnHPaequxftNNNzVceumlRYdbb5y+I47GjffroqKiQq5Zs+abXkacOD0SNIIsrVlKhiuD5mAz04un4+404+7eXIm/vY3SiSdS8/EHWE6FkpHjWb51OaP6j2JwymD2bGllZ9Meqlq2UFTRn90vbMAydYIDMzF27iQ9OTtac9vhQHEn0BHpINmehKrsf2/06X5yEwfQFmrDFwriiUg+VT7juG3n4tM8VJe+zkRtNLs9W0hKykZRNJ5VX6TCX8SahK2cIoo5VR1KJNzO7uQMshoKcNTvIUwCqoyw63sBbA3NmBE7Q4pGoagqekcEo60OfI14G8NkjsqNmi39+8CVRu1bNbj7Oek/diB0VvAxghrBBgst0Q4RH0q7gdIRQCYnIPxBsCeDasMoyodOc6C0JHpLCLushaQc6KypLnx+5J522vZtwVDKcWQOYfpVJ9CvYGCfr50QYq2UsqL7vg0bNtSOGjWq+d/6UXzNuN3uMYFAYN03vY6jxfXXXz8gMTHR7MkHsi94vV6lvLy8fP369VUZGRnHhqNunF556623EmbNmjX473//+7bJkyf3aGKP88XYsGFDv1GjRhX2dKzPUWtCiOFAOexXO0gpl/zbq4sT5xglaASJmJED/CJjmIaB1Wmqk5bF5uYt6M0J6OZ+1zlfe5hgMExYD+PfY2JELFSbggwEomZxRcGR3i/qV9dpghfiQDObApiWiSkthGrRkVqPVzSQWNyAc1MJa/xQlVDFe+nRF7VbQlfzC//V2KxqTvQWk5wa1RbahcpgWxZ+y6Le0c47mR8zpj2fpZ6PGbMnhZHbUhHFYwCwJdvRtBS2v7MegMwRA0AVUVO2lPQrTUdz27uEyxhCUSHii31ARIyotVwIhGEghYaI6ChtrZgDMpEmSNOIjt3dPcAi6odps2jpv5mcZA0pJ37ZyxjnGGXZsmVJV155ZeGVV165Ny5cfjc444wz/PX19ZXf9Dq+K/RJwBRC3A6cTFTAfJVoacf3gbiAGSdOLwSNIJa0ogE+Uh7og+n3YRoGe7dvRUqLQCTALu8udEvHMI2odi5sonshSUsh0mp1JUk3IyGUWMR0LKBBRP0sDw5wUBWNgBHAkiZWyM4n+uekJrpJTtDQh+3Gk7ibNex3PXtEeYpJZgXjEiVO14FZQAQmoKLrNvY52liaV4+CoHJwB4m5qRR1k20DdVFFX1J+GkLtPOBMAkUlOcmGlX6A333UPG5zgeXvjAZXkHY7wpBINSpsYpOgR1MvAWAaCCMEmgrd3AqQFhLBvmIby/pvYHbT0GMmTdEX5VjWXgL8v//3/3qs+NYXpk2b5p02bdoBwsbSpUuTb7311rzu+/Lz88OxBONHk29i7sbGRvXkk08eevD+d999tzo7OzsudMf5t+irBvMCYBSwTko5WwiRBTx69JYVJ863n4gZQVVUdEs/xAdTDwYJ+X3s21VLyBS0BoKkSAuf7ou272xrTxPQLLAUC6GAqUdIMhOQtgSC9akYfjuJRU0gO1NyILpSSAJoioZP9yF0E7k3h+97L2dJxW2EjdPQXAbflyexxvoUPehnV0IrLfYOKuUWKtTiA7+MjP6jKhbZoTSurj6Vx4vepkLLo7+p4XanQMgDzqiZOtLmRXNGNZQdO1tJHpgOig0jEETsbkdNSAbH/pQwQnTO4UwGBEJ2gGaLRo9rCpamYJo6aocPYZr7q/sIMxpBbnSLPzCj5YOG6/nkb56MqTqOig9mnGOP7pVzvgtzZ2dnm19XZag43z36KmAGO9MVGZ25MJuIB/jEiQPAuqZ1lKaX4tIODIbVTR2H6iCgB6JR4N0CUaSU6MEgNoeD5oDE4w0T1qOaSd3So7ITAmGzQFewVLMzYsdCjRiYuoE0FBSbBZZAhlxoNWNp1W0odp3kYXUoNgtVqOimjq1eooU91Bevo0yW0BHuQFNUVKfKNttuErBzW+NMGgKNOPopoPUQ72GZOO06QUWChHk7CrEL8JsCtZ8J9tYuATM9O5nMcCs7W8JorqggqTV4aW724dkVoLBQR3X0kHNQKCitPkTEjJq+DQuEIOJS0MMGCaYFpkW42UJLEAhpIVEQZhjCXnAkInQdFPDsricUDKD1O+E7q8GMEydOnG+KvuZFWCOESAX+AqwlWubxk6O2qjhxvkU0B5tpDh4a+2FYBnbVjl/3Y1NtByT/lZZJUmYmkWAQwzIxIxF8u+qxq3YMy8DqbGtYBlqKxPSHAYnqdKEHfEgpceW3Et6XSLAuDX9tP6QeFdisiI329QVYeuzPW2IEMokECxmUmMHpLaeheh2Y0iKVFPL0/py1ZxgiGCIrmEK2r5fbgpTYzGCn66QkKSJw+A2a60L4GgNg7tciChlGMQQDMt0kFUTN4b76DqxAhIFZdmyaeuj4MWt/KFr7XGoqQjejJvPO8yFMEwwDIa3O1ERm1JdTD0crB+khRFgHRcFwQHvqTgL9Nx0ztcjjxIkT59tCnwRMKeVVUsp2KeXDwBnALCnl7KO7tDhxvh2EjTDVrdWYB1WL0S0dRSgM6zcMtVtAi2WaSAnu5BQcbjdNgXqkaRDy+lCFStgMIy0JQmJIA3vAj+kPAQLNlQBCJdKSi9RVtMQwocZUTL+ThMFNpFVsx1+4BRCYwa5MLajuLezKe5E/a08R0DpQHQpuxUWyTGRW6xTK23OiZmdLohg9uF4JgeHz07qzHlU1ACsq6BkmhSUJpBenIDq80UCeiB90HSxo2eulbuU2otnVLYKeMG5NHpi3ErqESyAqDFqAKrBSXVH7uZQICegGwrQQUoK0Ov1CAbsrmtTdssDfAtLAn+vi+THbaFc8x3yi9Thx4sT5T6OvQT5LgJXASinllqO7pDhxvl2EzTABI8CKPSs4teDUrv2mNLuCcQCaAk0k25OxuguiEvx6B5ZpEg4FSFU0TNNEWtGQICklYlcDBMOoaU4kEjOUgN6WS3sbJA/fgxWygZDY0wJ48fFU9mOQLZgmz6S4fRSiIQu3awOlAYN+dafTT9jwJ4KCiiktVGmBIhBWVPATpnGoPKaotH72Od7dHnLzbQicCFNHCA1byESYBupeH1a6B/bVIoJBkKCYEjNsoPsjJLk1hCNWbacHATO2S0qEbmI4NCKmhUsFsEDRELqJZbNFNZwSBBZILfqqbISi7UwLFIv0fRF+1jiboNrvqPhgtr/4YqrR3PyF6kcfDq1fPyP1vPO+9tyaceLEiXM06KuJ/AkgB/i9EGKbEGKpEOLao7esOHG+PUgkraFW/Lr/gJREhmVgtvmxIjq+iI/tzVvZuGc92z9djR4KdvU1dAPLiDDAlQ1bW2jZuKXLB9OSnZrCiB8dQUdQJ+CN1u/WNB+qvxUtzYc9LZrSLYlEfiBPASHZyz7CLQkYHQn42spJNBzkBfqhqIAVxhb0ILEQlkSaYQj4kTrRgJmD0h2hOkjNdzC0JAWXI4LNFgKbi4DUaG0OI3Z7EIYEPYxW14rSHgALkuzRcXb9swaBIMnpQFgiqmk86CzGEBZgWURMC8Owukzk0mXHSnRG0xZJC6WpHaFKLGzRNqYJwTaEZSLNMKFWL969GyCSgHmwxvQrwGhu1mw5OfpXtfVFWFVVdVxpaWl5cXHxsClTpgz2er093sNPOumkoubm5h78EHon1qe5uVn97W9/m3mk9q+88kpSUlLS6NLS0vLYtmzZsqQvMucX5brrrhtwtOeIMX369MLc3NwRpaWl5UOHDi1fvnz5l573oYceypg5c2bBV7W266+/fkD//v1Hxs77VVddlQswfvz4oYWFhcNj+88888zBPbUvLS0tb25uVmPXsKysrLywsHB4RUXF0GeffTalt3lvuumm7Fj/2G+xtLS0/K677uo/evToUqvz79owDEpLS8vfeuuthO5zFxcXD3v66adTDremnub1er3K1KlTB5WUlJQXFxcPGzdu3NCamhp7rF+/fv1GdR8rFAoJgCVLlqQKIcatW7fOCfDJJ5+4Ym1SUlJGx67vxIkTS6qrq+1Op3Ns9/XEKgB1J3aOS0pKygcNGjRs5syZBd3XHTsvRUVFw4YOHVp+xx13ZMWqR/XlfN933339Bg0aNGzQoEHDhg8fXvbKK68kdZ97+PDhZbHP7733nnv8+PGHZAH4T6FPb99SyneEECuA44BTgPnAMODBo7i2OHH+o9m16TMS06KV0AqSCmgONuMJe8hwRe9JuqUTrm8mLO2YTpN927fhNWopshWgaHYsUxLSwxh6OJrP0bQwvSF0h5O9OzswwiaGMMG00ANB2oM6UqjYQgloCQHSxCeYPhv1NpWcFCdKZ+j4ODmSvMbhOFtzSBy6l5ArgtVkUOdoI2jzMNiZj81mYOvQ0SN+sCRSMRGGCUmpKEYQSx74LDV1i4ZPW8Cw0DQ/+flOtu8LgRCEdIvUBAOhKBAOQTiC0ATCVEmyKaQMSMFT76Fqp4eBA5JI1M1DTORCsN9MLi2sREe0AiR0BTehKKBpoEuEZSENC6VTk4migsMF4UBnuUmJpVl4UlpRcz7GkiOO1s/ga8XhcFixqN+pU6cOuv/++zPvuOOOriTjlmUhpWTFihV9rkN9cJ/q6mr7Y4891v/mm2/ed6S+X0XN675iGAa/+93vvnRaoi/DXXfdtWf27NltL7/8ctKCBQsGnnvuuRu/zvkPx/z58/f2lGB+yZIl20888cRDkoj31r77Nfzggw9cM2bMKHK73bXnnnuu9+C299xzT2OsCo7b7R7TPQL9o48+Svzd737X7/rrr29etGhR/9GjR/vPOOMM/2uvvZYSm/vTTz91nnbaaUMvuuiiDYdb08EsWrSof//+/fWXXnppB0RLU+bn5+ux+XtLuP+3v/0tfezYsb6nnnoqfcyYMfXjx48PxvpMnz698Ic//KEnVsmourranp+fH+5LVH3sHIdCIXHNNdfkTpkypWj16tXVcODfaF1dnTZjxozBHo9HfeCBB+qPdL6fffbZlMWLF2d+8MEH1Tk5Ocb777/vnj59etFHH31UNWjQIB2gpaVFe+6555IvvPDCjiOt85umTxpMIcQ/gVXAj4Bq4DgpZenRXFicOP/J7PHuIejroKWlAdMycdvcODUnurU/Ubpu6WBKdK8k3GQRtiI4cQIC1ZbC3toOTFNHDwdIDCdiBi3QTQwdjIiJoVv4a7dhBH1gGEjTIlLXDzXiwkqqIxAMY0qIGFaXhm65eJ1V4hMSZSKmJ4GORjeu5L0kOzfzYb+tvJ61FiwdlyeAXSpYviaEGY26Np0aivSjWKGoNrITaUkaPqzFCJmYhiTBraKHdEKGJKRbDB6QiGJLBECEgkSznJtYCQ4sh43+RRnYk6M5NRXTRAo6Uwl1nifTIhA5KBm9pkS1t9FRO/0to7KjpQiEoSMMMxrsE0N1gKKBtPCaAfRkeH58LU2OFizz6NQj/yaZNGmSb+vWrY7q6mr74MGDh1166aUFw4YNK9+2bZs9Nzd3RENDgwZwxx13ZBUXFw8rLi4eduedd/aH6MO0tz433HBD3u7dux2lpaXlV1xxRd60adMG/fWvf02NzTt16tRBMS1UT6xYscJdUlJSHggEREdHh1JUVDRs9erVzldeeSWpoqJi6BlnnDFkyJAhwy655JKCmGbnhRdeSB49enRpeXl52ZQpUwZ7PB4FIDc3d8SNN96YM27cuKGPP/542vTp0wtjtdVXrlzpPu6444YOGzasbNKkScU7d+60QVTLc+WVV+aOGDGirLCwcPjrr7+eCFEBdd68eXklJSXlJSUl5XfffXf/w43TndNOO83X1NTUtf9wc19++eX5Y8aMKS0uLh72r3/965C61s8880zKyJEjS8vKysonTpxYsnv3bs00TQYOHDi8vr5eAzBNk4KCguGxa/h1MXHixODPf/7z+j/84Q/9j9z6QP73f/939wMPPJC9Zs0a56OPPtr/wQcf3HNwm7Fjx4ZUVaWxsfELfa+GhgZbbm5u18111KhRYZfLdVizhMfjUdasWZO4ePHi2hdffDHtcG2/LE6nU/7pT3/aU19fb//www9dBx/Pzc01Hn300drFixf3tw6x2hx6vu+7777s//7v/96Tk5NjAEyaNClw0UUXNd9///1d12PBggV7f/vb3w44Gt/nq6avJvLPgAgwHBgJDBdCHHIy48T5LlDdWk1Naw3+kI9Gf2OXUCmlJNItklo3dTAtIh6JVu3FMHVk5wM14Amjh02waYQxESKdcIuJFdEJ7zUwdQvLNDH1CJZhIE0D2742vMkNbOn/EctynsdUlaggJyUhbyCqiepM5+7tX0tt2kaCrVHBTuo6p+0bxpSGcSihIDaPF7vsrIRj6NEa4JaFsCLRBObW/qgbyzBR7CrppVkUFyTR2hbG4xcMKc0kLcONEk2oBKpABKNJ24VhIjUFNIHSHqD/yBwGZifilhJp01C8+5O7+8IGHSG9U/NIp3ZTROXKzjZhI5rjUzejeS+FrkerGclujSIGwhCAiUDijijc8NmPKNl1BuYxJmDqus4bb7yRPGLEiCBAbW2tc/bs2S1VVVWbS0pKun6EK1eudD/zzDMZa9eurVqzZk3VkiVLMletWuU6XJ/7779/T0yT88gjj+yZO3fuvieeeCIDoKWlRV27dm3ihRde6IH9ta1j26ZNmxwnnXRS4Mwzz2y/7rrrcq+++uq8GTNmtBx33HEhgMrKyoQHH3xwd3V19aba2lrHkiVL0hoaGrRFixblvPfeezWbN2+uGjt2bOA3v/lNVmw9TqfTWrt2bfW8efO6al2Hw2GxcOHCguXLl2/btGlT1axZs5pvvPHG3NhxwzBEZWVl1T333LP7zjvvHND5vTJ37tzp2LRp0+aamprNc+bMaTnSODGWLl2acvrpp7f3Ze5AIKCsW7duy0MPPbRz3rx5gw4e64wzzvCtX79+S1VV1eYLLrig9c4778xWVZULLrig5dFHH00HWL58eXJZWVkwJmj0xMMPP5wVO+9Lly5Nju2fOXPm4Nj+K664Iq+n9hMmTCjpbdzx48cHtm3b5uzteG8MHDhQnz9/ftPJJ59cduONNzZkZWUdEi34zjvvJCiKImPfq69rmjdvXvPvf//77NGjR5cuXLhwQGVlpeNI63n66adTTz75ZM/IkSPDqamp5vvvv3+IsH8wsRer2BZ7OTkcmqZRVlYW2LhxY4/nrLy8PGJZFnV1dT0K1d3P99atW10nnHDCAdrn4447LrBly5ausSdPnuyz2+3Wyy+//LW4ivw79NVE/jMAIUQiMBtYDGQDR7zIceIcS1jSYrd3N5a0kJYFCEJmVFiSSLa1b6MgOepqpVs6igVSGqiGSri9A8OVhC8YAqERCRmE/QpmUjKq6cCKBLAnuAh7DCIhE8sysPQwph5BmiaWCe4EaHDsjo4vLByGGQ1gqW8hIBP5ftrJuHASQSdU0IbbaAbTYm1WHXWOZs7aMRL662imjqLYEJZA+H2dMpoARYKlQ7dHg2rXGHD8INS9HtRgAE0TtLWG0Owa/XOSov6WpgWqAsEgKBJpd4CmYmkqvoYO6j5rJKefGyMr+f+zd+ZhclVl/v+cc++ttffupLN0OgnZOxshMSwmoyCMo0AMyQAiCKigML+oCDJxEMiMgywC+ow6Ki6sMgsSDcqoCCirICSGkLWzkLWXpPfa6957zvn9cas6nT1AWK3P8zShq84599xb1VXvfbdvYMjm93p6MaAKHk1P6b0fSoVQt8GgjEb6kFY5asJxhNKBF1QWjFHA6kwFns68j4g4eFmfntQrOLWTKHrK3uvk83k5ceLEJoATTzwx+eUvf7lz+/btztChQ92PfOQj6f3HP/XUU2Uf//jHeysqKjTAmWee2fOnP/2p/Nxzz+091Jz9OfPMM1NXXXXVyJaWFvvBBx+sPvPMM3scJ3DmHSpE/q1vfatt+vTpk8LhsL7nnnt2FB+fOnVquqmpyQU477zzup999tmySCSit2zZEpk9e/ZEAM/zxMyZM1PFORdffHHP/uu/+uqr4U2bNkVPO+208RCE+QcNGtT/pjr33HN7AE455ZT0tddeGwL44x//WHHFFVd0FPdeX1+vXn755cjh1rn++usbbrjhhobu7m776aefXn80x/7Upz7VDfCxj30slUql5P55hVu3bg3Nnz+/oaOjw3FdV44YMSIPcOWVV3bOmzdv7I033rjn7rvvrrv00ksPq3t/rELk+/NmCuK+9rWv7bnpppuGf+lLX+oa+PiPfvSj+oceeqg2Ho+r+++//zUp5eva0ymnnJLdunXr6mXLllU8/vjjFaeccsqkp59+esMJJ5yQO9Schx56qObLX/7yHoCFCxd2P/DAAzVz5sw5rP740YbI9+dI1+xwz7+Rudddd13bzTffPPS22247wEv8buJoq8gXAXOBmcB24G6CqvISJf6m2NizkbzKI4Qgr/KQBTcSOH+KHkylg+rx7tWbsJXGyyQwfWmiPe34k6rJJPNE4jHcvMfu9G7yvgmkHn2FtCJoP08i2cdru1bju3mk72JJBwG02a3U5OuxVYo/jVzLmbuODwqnczk2Om08Yb3El9RllBFHh3PsCm+hqaeebZlNZQ0AACAASURBVLFOuu0EQvuQ6sEyYaQMY/W6QWwiHHgCJRoTjiKyHlTte+7CVeArRjbYtHUIKqsKQQwDQmmMI5GZLDoShmi8f15Z1KG6oZJyGZwnUiLUXseMNvR7XlM5D0dDodUmAEqboC+oAaV1ochHIXwfKQZ8+GqNUAodlsFcaUhUZtDD/4TW+ykTvUcZmN81kFgsdlAX7eG+vA4152Ccd955XT/96U9rli5dWnP33XdvO9L4PXv2WJlMRvq+LzKZjCwauPtLmQohMMYwZ86cxG9+85utB1urvLz8gH0aY8TYsWOzr7zyykG7mkQiEQOBd0kpJQpzEEKY17POTTfdtOviiy/u+eY3vzn40ksvHb127dr1R5pzsHMcyKJFixq//OUvt1944YV9jz76aHnRwzp27Fivrq7O//Wvf12+cuXK+LJly1472PpvNS+//HJs7NixhzTcDodlWQecLxy9IXk4Kisr9SWXXNJ7ySWX9F588cU88sgjlYcyMNvb260XX3yxYuPGjdFFixahlBJCCPPDH/5wV9G4PVb4vk9zc3Ns2rRpB80PXrduXciyLIYPH+6vWrXqgOcHXu+xY8dmn3/++di8efP6819XrFgRO+GEE/YxjOfNm5f813/91+HPPfdcfP/13k0c7ZWOAt8GJhpjPmKM+TdjzB/fwn2VKPGuJOkmSXtplFa0JHZhXI+aUE3/83md55ldz+C7Ll4+i3Z9jMlj+WD7Es/10L5C+RptNKmUGxRUK7CcKHYkgjaGZCpBKrUdozSRaDmirJycZTHmtb/DV0Foe0d5B67WYBTZ7tdoWJ3m77MfJE4MjeYR+XselY+Dr1jQPptPvzYr6HOZ95BGYwmJlfXB9wlMPBF4L20bkd0b6k+3Jdj1zGZ810NogRWO0zCqGssOPj5MLIQJWRgpwfXB3vdjRWIYXBHBKn6wC8BX2K/tAUCZILSfzHm4ykOh+qPlACmVwy24VA0EFUFe0ItTFAxPCOTM0UA0iBY6EcHDJ+1kV6wD/2C9Pd8kdl2d77W1Ocfqx66rO2Q49I1y2mmnpX77299WJZNJmUgk5G9/+9vqU0899YDijYFUVlaqdDq9z4t4xRVXdN511131ALNmzTqi8XHppZeO+vrXv976j//4j12LFi3qD9OuXr06vmHDhpBSiocffrhm7ty5yQ9/+MPp5cuXl61ZsyYMQcXwq6++etjo2LRp03Ld3d32E088EYcgbL18+fLDhnVPP/30xI9+9KNBnhc4G3fv3m0dzTqWZXH99dfv0VqLpUuXVhxpzn//939XAzz22GNl5eXlqra2dp83XzKZtBobGz2AYupBkc9+9rMdl1122eh58+Z12/bbmn4JwF/+8pfo7bffPuz//b//t+dtP/hh+MMf/hDv6OiwAHK5nNi4cWNk1KhR7qHGP/DAA9ULFizoam1tXd3S0rK6vb391YaGBvcPf/jDEUPer4d8Pi8WLVrUMHToUPfEE088QP6stbXVvvzyy0d+5jOf2XMww3b/63311Ve3X3fddQ3t7e0WBEVAv/3tb6uuuuqqAwruFi9e3Pa9731vyLE8n2PN0YbIbxdCzAE+DdwjhBgElBljDnrHWaLE+xVHOoEyj3TwtU8+nQYVfBcaDDk/R8SKkMj0oFJZrGglbtoFI5DZONmeXpQ1BOUZNIZcQmHKBGiBCsdxuyTGGPLpDlyZIirDCCHQUhL3DZmKHgbrQVS0ZpnRMYaVdZvJhPdwQrQWN9HGsD+l8E48DquqkqzIMVVPCophhEXUs/Ax4LlYlo0AHGmTD3mETMG7KAIFHZnbG8IWlkCGLIQh6JVp7/vdb8I2JmyDUli9aXT5fh8rQmD1BdXqlAVzZc6DgppPsaBcGcjoHBnlYrICiRV4dgvPGx0UHBkDVMaDxuoD5Df7PalS9Gubf/WvHyfNB3CPP/YG5nuhZ+WcOXMyn/rUp7pOOOGESQCf/vSnOz74wQ9mm5ubQ4eaM2TIEDVz5szUuHHjJp922ml9d911164RI0b4Y8aMyZ199tn7nHMxB7P4++LFi9vS6bS0bdtcccUV3b7vc8IJJ0z89a9/XS6l5Pjjj09dc801DRs2bIieeOKJyU9/+tO9lmVx1113bfvkJz95nOu6AmDJkiUt06ZNyx9qj5FIxPzP//zPli996UuNyWTSUkqJK6+8cvfhjN+vfOUrHRs3bgxPnDhxsm3b5pJLLum47rrrOo5mHSklixcvbr3jjjuGLFy4MHG4OdXV1WrGjBkTU6mU9eMf//iA78ivf/3rrRdccMGY+vp6d9asWekdO3b0/0FdcMEFfYsWLbI+//nPd+0/72i5+OKLj4tEIhqgpqbG//Of/7wR9oapi+MeeeSRzRC8hpMmTWrKZrOytrbWu/3223ccrIL8reBge5owYcIBhuPGjRsjixYtGgmgtRann3563yWXXHJA6kSRX/ziF7X//M//3DbwsU984hM9DzzwQM0//MM/pA41r5iDWfz9oosu6rz++usPMLYvvvji40KhkHZdV86dOzfxu9/9rj9NpJjG4vu+sCzLnH/++V1Llizp994e7npfeOGFfS0tLaGTTz55olJKdHZ2Oi+//PK6YcOGHXDzef755/d94xvfOOY3pccScTT5FkKIJcAsYIIxZrwQYhjwC2PMB9/qDR6OWbNmmeXLl7+TWyjxN4Q2mg3dG3i+5XmiGYHY0UuliZGZVMXg6mG0plrxtEddtI7RdgPPPvJ/1I0YTHp7LzppYVq34w+3GVIxGS2qec1tJZNJI0MC2wtjeYL6YWGSnV3UDR5EW+8OnHCMqtYEG2I9hFMWkfqJaKOIvLaTjmqXpeP+yKwtw2naEmbnkBwjdznUTTuRqAu/b2xmghhHpL2PFWWb+Lvt9cQzMUJ6B/FwBX79DJyeVnbrJBHLRqkwoVCKcNxHJnL4o2rRVYUIjDHYu7qxd/UEeZSHIl/4Xgrvm38uU4GtoAsGJgZkOk928jB29eYwBqyeWtK6h6qONDocwsHG80Io6QMJYpEhJPMhauJxQuE8fmcvkcGKbLgOO6Kwt3eB0phYiN5UDt/bSb5P4FR9gtkLm5h9+olH/VoLIVYYY2YNfGzVqlXbpk+ffti8uPcryWRSNjU1Nb3yyivr9/fIHS2PPvpo+Z133ln/drU1eieYPXv2hDvuuGPnwXIgj4Znnnkm9pWvfGXEihUrmo/13kq8t/A8j3PPPXe01pply5ZtPdah/WPFqlWr6qZPnz7qYM8drQ/+HGAGgQY5xphWIcS7voKpRIljyXM7niOtMvhumnxnCicv6bEUEfZ2wEh7aaoj1azpWA15Sa7LIJ1KRKYHyylDWQIrFCcnBNlMHqUVjhfCGHAjKmh0bkXJZRJEXHASSUDwqxHPMbp7HOOtMoZ7Q8hGcywd9xQAQ1K1oBNsGJlgtpiFY0cQiT6meuPYHt7NoGSK+l058lFF3Ae/ArSnSOUVtVoCgVfSKCh6BGXeQ/Wm8SrCWK7G3tIBIRtdfoTi0kPcsPYblkWKaVo5PxDeEeBmMzhS969jhMESYXwtEFIE4XAK6j0YhASh1V6VSWMwsYIeOxIjBInKHLnhzyKdSZR4Yyxbtqz8yiuvHHXllVfufqPGZYkjc9111w259957B91zzz2lyGAJHMdh2bJl7+n3wtEamK4xxhQTpIUQ7+rE0hIljjXGGHau7cWu8PDcNkgkCCeryPgVlHdWQDVUR6oDHXFjSOaSpNOQsXLElUNMaQQSO2OhagNtbaU1Ih9CWiG0bdCAckEg8fwc0tPEZJgVVc2E/BinbfoC2wf9FRnLUenHmd4xjiG9MerMcER4F/+4YTjG2LjsIYJDm9zDk/JZFjCZIV1hnHIPKgDbYHsKKTQai8CoLPaaDAw8L+ywW+bIbW9Dre4lHrFpHFFxoIb4/lg2R5/aDXg+lgwKeULJDMJSWEh8CELeEghSRMGARiGEwRRaMklfFRqxm4JxK9AYtLCwYlH+MGE7Da5TKCEq8UaYP39+cv78+avf7DpnnXVW8qyzznpbQq/vFC+99NIb9jzefPPN7TfffHP7wMcWL1485JFHHqkZ+NgnPvGJ7mKz87eSd+LYS5curfj617/eMPCxESNG5B9//PEtb9UxS7x1HK2B+ZAQ4i6gSghxOfBZ4Kdv3bZKlHh38aedfyKby6M7tjO0Oo5rZcllsihVgd8XGGURK0JV72CSnRsJDarAGIFSoPKBVjcGyGg6k+1ktkygXE7A9sIILPLRLnRNF9oCWa7RGR/humCFqMtXMKmvERN+maF2nlAuj0Ry0u4peL270Im1/M9pu5jTMpYJ2ytIde9hWP04prhjqbXqeHD8Lzk9M5TGjhRVFXGQBsdzcfwUibyGSNEgNAgUWku27OxDF5rLRKtjDAkJyKvA1Xg4nCO2mtsXtdcolLq4vMQzflCEVBgmhcQYhcBBY8h7LkJ7xFVQEIQ2/V5R1wvUfaQ0fOGVE0nZZ5AZUXK8lXjvMVA552/h2AsXLkwsXLjwdbcJKvHu5GiLfO4QQpwBJIAJwI3GmMff0p2VKPEOk026dLelicQdeltyKFdjtI+dE5D0yIXKMT2C/s4nGtwODz+Tx1QotDIopTEeSN/DGIHxFG6iA1FTR8bLYCI54kQJt49CJgTO0B58FfTWC7k+wvGoSlRyUqoOxyTxiCC0AiQCsEMVbBjVRjasWD24lRmdI4hXVWFhIYxN59Z1XLSlkbLG4YQqfHwDlhVB+i4in8MYG+wIxoAykYJmI9RVR0nYmtyePLXH1RJu7QbPR9W88SJM3yhssa/UsFEaLCuoYTeBDrkA0AJf6oKBaRDGwvF9LDxy+Rx2NI+QHtJXyEweygQYgTYGTykENp7nkepuxanYhdJHlNYuUaJEiRLHkKPug1AwKB8HEEJYQogLjTEPvmU7K1HibcRXGtsKPHlKaRKJNC079uDutimrCZHp9NB5MFmFdixMWgd9vmUelcxiVDnJLQZchXI9cuk0ShuMBhwf2/JQ8QgqqfD8LH7tNlJJQ1VmBMSTuOPXkVcKTRQBuMolnE0F0pEyhtEhtC4DnUXsbYuOscqYkZ3GqPVjsdIGyxY4VhQhNCaVZVyykaRuJp4xdPbsQVqDKK8MoaWF0Qpt7ML5h8i7vexp76B6WJT66ii6HMSMOqJ+BNMmMLHQ3tzJ10lee6RUjlpnQOq2BKMMxgKjFUJLLKMxtsS2JCFhIXQQ3LYQOFpgGRcXDxn2CVl9CBNCeBq0oKglWUwDjVhhOquSJIa9wIyyGW9s4yVKlChR4g1x2GQpIUSFEOJfhBDfF0L8vQhYBLwGnPdGDyqEqBJCPCyE2CCEWC+EOFkIUSOEeFwIsanw71uiHVqixMH4U/MeOguVzqnuPCtf2cDalo0oV5PNeLi+j/J9VAqynRbZ7hAqn4NcH9ldW/HTYFSguJhJp5E7rOB3FRTUELKQYQspkxgt0D3VVPaOJN47HKdlInRXkRc5/iL+SpdK4noeqKCx+YuDWni1PIPvzUJ4dn8epDEKlffYEd3DgxOfIRNKgVCklCKZTyI8D5XuIxSpIRQOU1ZRR7KvF2kstHDwlUKZwAh28xoh8mCgpyWL6ytswBF2oOMdsjGRAySaXxcHeC8RuDkXAWhfYwRYBQ10S4j+hs0CQbmMB83V0dgmUEeSthso+hB4PjF71SYFklgoxF+aemiu63hfapGXKFGixLuZI3kwHwB6gBeAy4BrgRDwCWPMK2/iuP8B/N4Y849CiBAQA64DnjTG3CqE+BrwNWDxmzhGiRJHjacMWTfI07NDkkQqje8ptG3IJPNIYxFN9ZDKCZSQaN+gcxaRiA0SetdvRlrD0Lk8KqGQVtC3EVdguZmgCTkQdyJofzCyezwq9BR7qrqp6xtP1lXIlhH8ueYhRmw+FScziPbo7xiei/KB7Z9AC5+Q/Re0ThRC8ga8HLq3GadsCEpqylwLbEOyrx0/10ekohLt5VC+ixCVhCLlpJNdbG/uIjpsOPg6UCTKaJKdawCI1Tjk+nx2tCQZXFlN1Aqh84dsR3hUuNojqXJEpMNeYUcwUpDLeIRrrECzHPCjIbQlkIVKcYNBCjCU4YgUlskjCprpBoGbd3FDGjfjY+scri+RBIawFJLzmofg1kxFjT72BuaGF1qrMgn3mHXDjlWE/IknDztsb03LsmaOGzeuv6HzggULuvcvDDmWPPjgg5Vr166NvpXHKPLd7363dsmSJQ319fVePp8Xl156aceSJUveUMPv5ubm0FlnnTVu06ZNa4/F3h599NHyCy64YMzw4cNd2Ntf8uqrrx7285//vK6mpqa/H+Fzzz3X/OKLL8YGjge49dZbd86fPz9ZfA2LfRIvuOCCrhtuuGG3ZVkHHHdg0cuOHTvCgwcP9iKRiK6vr3c3b94cfeGFF9Y3Njb6ABdddFFjY2Oje8opp6QvuOCCMQ0NDW4+nxfnnHNO95133tm2/zkM3NPBznnx4sVDli5dWiulNFJKfvCDH2y/5ZZbhuzcuTOcyWRkT0+PXVzre9/73vYzzjgj3draajc2Nk675ZZbdlx77bWdANOmTZvouq7s6+uzcrmcrK+v9yDoeXnaaadNiMfjqtiC56STTkree++9OwfuY+A1zmazcsKECdlbbrmlZebMmW9IbWhgu6xj+f5euHDhqBdffLG8rKxM5fN5OWPGjNS3v/3tltGjR3sAXV1d1mWXXTZi+fLlZQAzZsxI/+xnP9sxaNAg1dzcHJo4ceLUm266aefXv/71PQAXX3xx46xZs9L7y26+lzjSh+NxxpipAEKInwKdQKMx5g1XAgohKoC/Ay4FMMa4gCuE+ATw4cKw+4CnKBmYJd4mfK3xtcFog5dXpJN5lBCIkAi8X77EFjaxqhCqVwEWykiEURgvj8r7aHKobJrySDWJ7jwmLhDKJZROQU0QGpZCEI/sIO9kiKWS3D/pVwCcvmMetT3H8dlV38DYwXdVPPsxeoHVQ59kWvdoQu42fBXFyrsoQtjhKOG6icRMnC++Op9Qrh1TJgnFq7HLR6JSXVTFash5wXrhSBn1jfW0b2/H1Qq0CZQb7Qix8hpiMQVxn0i5Q9SV2Fmfcs/G7e06cvX4YfCMJipDSERRrg8o1K6roArcIijwsa0oBoWPWxijkFIghIVvwkhSGOmA9tAGPFfha40unIvWQf6qFAaUobvLEKYDrY+9gZlJuHZZdcQ78sijI9WTO6KL+FBSkW8Fnudx4YUX9gF9b8fxAM4+++ye+++/f0d7e7s1adKkKRdeeGHP2LFjj9k1fjMcSnf9UDKIhxo/8DVsaWmxzz333OP6+vqs73znOwdIDQ4setm/x+a3vvWtQV/84hdHPPLII1ufe+652EsvvVT2s5/9bP3jjz9eVjx2IpGQU6dObZo/f37f4fa0P0888UT8scceq1q9evW6aDRq2tra7Hw+L4rV3IfqaXr//fdXT58+Pf2LX/yitmhgvvrqqxsguIFYvnx5/P77798xcM7TTz+9cejQoYdtGD7wGv/kJz+p/uhHPzrh1VdfXXuwBuSvh2P9/r7pppt2feYzn+nRWvPv//7vg0899dQJGzZsWBuJRMyFF144sqmpKferX/1qDcBXvvKVYZ/85CdHPfnkk1sguGm56667Bl9zzTUdRanT9zpH6ifS/4dtjFHA1jdjXBY4DuggUARaKYT4aaHtUb0xpq1wrDZg8MEmCyE+L4RYLoRY3tFxgHpSib9xXOXSkXl97wtjDPmkh9KGvo4s3a0pPM9FK0NosKJyWBgU4GuiThgrlMNyIhgtkXYI/Dw60YfKKbRShGOVaOkibAstFUpKKOR3YkAYg5C9PDUiCAJM7BlJa2UzLdXPIfNR/Egahu/tCjOt7SPY0RaEAKF9hO9j3CReJoGwLCDSv66RAtsGYztoT2G0QQjVn5gYCttMnFJPPBLBV1kS2d0kOzYTjoSpqYthhyShqIUTFwhfEW5LIDIuxjnQu/J6qHHiyP01iqXoD3FbOQ8HQQiHcjtMSNr9EpBSBLVH2o5grFDQrsh4+Bq0JYLrWwyVG4FnNAaNtATJKo/m2g7ez12Kurq6rFGjRk1ZtWpVGODss88efeedd9YBxGKxGZdffnlDU1PTpJNPPnl8a2urDbB27drw3Llzx02ePHnSzJkzJ6xcuTICgRfmsssuazjxxBPH/9M//VPDd7/73dqLL764EQLZu49+9KNjpkyZMmnKlCmT/vCHP8Qh8DCde+65o2bPnj2hoaFh6k033dT/2f3973+/dvz48U0TJkxomj9//ujDrTOQIUOGqMbGxvzOnTudIx17/vz5o0866aTxI0eOnFI874E0NzeHZs6cOaGpqWlSU1PTpMcffzwOMH/+/NE///nPq4rj5s2bN/rBBx+sPDavytExfPhw/6c//em2e+65Z/DrvQm65pprOrZv3x7+zW9+U/7FL36x8T/+4z92hMPhfd7pFRUVeurUqZnm5ubDSm/uT0tLi1NTU+NHo1EDMHToUH/UqFFHNPR/8Ytf1Nxxxx0729vbna1bt765nJpDcPnll/fMnTu372c/+1kNwPDhw6e2tbXZEDSqnz179gSARCIhzz333FFTpkyZNGnSpKaBr3WRge/vhQsXjrr00ktHzJgxY2JDQ8PUe+65pxpAKcVFF13UOHbs2Mmnnnrq2A996ENji88dCiklS5Ys2VNXV+c9/PDDlWvWrAmvXr06/q1vfav/JuL2229v3bBhQ6z4d1tTU+PPmTMn+Z//+Z+1h175vcWRDMzpQohE4ScJTCv+vxAi8QaPaQMnAD80xswA0gTh8KPCGPNjY8wsY8ysQYNKlaEl9mV3Zjcvtb/EM7ueoTN7dKIrXl6RbcuSyHoopXE9P6hG9jxaUq1BD0VFIckStJtDWpJqEcGxQ6A8VNZF5RT4GoxESYtwJEyZY+3bfFwYsukxiGw1nbE0ZfkII/vq2FT+Gq3lLaybupQ1Q5+motaht/Y+/jxyGZ6zB2GCHEWhNcoXJHO95Du346c7EFJjtI0wfpCDaDR+tpN0ppfefBdZshitKFbBBAFoQzqbIpXdjVYevteHEDpQixSQs8DOKxwC6UoTfXPfFXErXMjB3HsttBDIQs6lzGSxCh9HjiVxhEUOF41GIoLCJlE4BQxae9iWhbYlVtZF5hVeoROU8PPE0mmksNgwNsGa4R2H6v/+nqMoQ1f8+clPflJdW1urvvOd7+y45JJLRv/4xz+u7u3tta+55ppOgGw2K0844YTMunXr1n/wgx9Mfu1rXxsGcNlll438wQ9+sGPt2rXrb7/99l1XXnllY/EYW7ZsiTz//PMbf/KTn+waeOwvfOELI66++urda9asWf+rX/1qyxVXXDGq+NzmzZsjTz/99MaXX355/R133DGsqM99xx13DH366ac3Njc3r7vrrrt2HGmdIps2bQrl83lZ1Hc+3Jz169dHn3jiiU0vvvjihttvv33Ytm3b9nmzDhs2zH/22Wc3rlu3bv3//u//vvaVr3ylEeDyyy/vKGqBd3V1WStWrCg777zzDunNKspiTpw4sWnx4sX9GtA/+tGP6ouPn3jiieMPNn7ixIlNa9euPaiR19TU5GqtaWlpeV3pFpZl8YMf/GD7RRddNOa4447LfexjHztAArG9vd1auXJl/Pjjj8++nj3Nnz8/0draGho1atSUiy66qPH//u//jtg+YvPmzU5nZ6dz6qmnZubNm9dz33331RxpDsCHPvSh8cX9/Nu//dtBHUv7M2PGjMyGDRsOq/pw3XXXDT311FMTa9asWf/ss882X3/99Q2JROKwNs/u3bud5cuXb3jkkUc2LVmyZDgEXtmdO3eGmpub1953333bVq5cedStNKZNm5ZZv359ZNWqVZGmpqbMQH1527ZpamrKvPrqq9HiYzfeeGPb97///Xrff1crQB41h31DG2PenNvi4OwCdhlj/lL4/WECA3O3EGKoMaZNCDEUeEO5NyX+xjHQlesibIVJuAnqovs6NJrbk4wZFO+vGIdA31orzfrdu9mZF4wSIURqD248TtgOo41B+yBNUEXilJdDxkM7YRB5MAqdSWOFe4NqE2OjwzEcKbAwA9Wy8U2UTGYqwtlOZzxIpVtd9xoV+Rgf2zqTX09eRUKmiCiXZ8f/ldpclFO6KgjuBQUqnyOdSqP9NE7FEOyKepA6MBtNHgXBfnJpXDeLkRa2CMLGwgr6AO1pT9DVmUYgiIQqUJbAlAXOCSEKyj7CIA3YkQim781ZZ3tLdUTBYAwi7p4OckmN1pDOEoqGodD4PZBGFyh8oiJULBCn0oqTM3kyyg000X0f0GhPgAyu0ay/rqG6L8GGBXM4fXsdJj4ehr2pU3jXcKgQ+TnnnJN46KGHqv/5n/955IoVK/rzDqWUXHbZZd0An/3sZ7sWLFgwtq+vT65cubLs3HPPHVMcV9QAB1iwYEHPwC/CIs8//3zFpk2b+r8MU6mU1dPTIwH+/u//vjcajZpoNOrX1NR4u3btsh977LGKs88+u6cY/qyvr1dHWuc3v/lN9dixY8u3bdsWufPOO7fFYjFzpDkf+9jHesvKykxZWZl/8sknJ5599tn47Nmz+6UaXdcVn/vc50auW7cuKqVk+/btYYAzzzwzddVVV41saWmxH3zwweozzzyzx3EOfSN1rELkB+NoJJsPximnnJIdN25cdtGiRft8Xxb1rqWU5stf/nL7rFmzco8++qhztHuqrKzUa9asWff73/++/Mknnyy/5JJLxtx44427DpcPeN9999XMmzevB+DTn/509+c+97lR//qv/3rAddmfowmR78/RXK+nnnqq4rHHHqv67ne/OwQgn8+LzZs3hw43Z968eb2WZTFz5sxcV1eXA/Dss8+WLViwoMeyLBobG/2TTjrpqKO4xX0GOjUHtuDY/zwmTpzoGEOoOwAAIABJREFUHn/88em77rrrqIzzdzvHLEH9aDHGtAshdgohJhhjmoGPAOsKP5cAtxb+feTt3luJ9z5duS5c30Wbg4ebNrQnqIo51FcEN7/ZlEs+7YNv2LphPValSzJ5HMYYauvjGKPRRqNTe7Bkof+kFIFD00gyqRqU6xNSLkT70CZKb8IUEgxFf0shU/iPb4KbXylf4yNbR5Fz4tjKEDaV4Dmc3vVh2mUfvxvya+Kew4jMgKiOEBhX4ftpRLgcp2I4VlhjlMYIgYoHrZMMCqusnmphcKMVCJlHS6e/p2RtbRmWCdPT00s0PAg/HsKJBs6qojFoBBANI95E7mURE1w1RGH1vPZwXVDKILVBJDOEfIMVsfDdMK6v8UQSy9goNFIEvUaFEUQsDyMT5H2NJYJSILRBeRLhWIzavI3qvgStTVMQQtLXYQh7LVQ1HvZ75T2PUoqNGzdGwuGw7uzstMeMGXPQcKYQAqUU5eXl/qFyOcvKyg76x2OMYfny5evLysoOeFMMDM1aloXv+6KQb3vA2MOtU8zBfOKJJ+ILFy4cd8455/Q1Njb6h5uz/xf3/r9/85vfrB88eLC3dOnSrVprotHozOJz5513XtdPf/rTmqVLl9bcfffd2w523m8169atC1mWxfDhw9+Q20pKyf4FQq/HuD0Utm33qy9NmzYt+8ADD9QezsBcunRpTWdnp/PLX/6yBmDPnj3O6tWrw1OnTn1zVYIH4ZVXXonNnDkzA2BZlimmF2Sz2X7PgTGGhx9+ePP06dP3OX5ra+sh7yIG5j4OMA7f8D5Xr14dO/3009unT5+eW7x4cUwp1f9aKaXYsGFD7KSTTto5MD3ixhtvbD/vvPPGnHjiie951at3Sj39i8CDQohXgeOBmwkMyzOEEJuAMwq/lyhx1OxO72Zr31Ycy0GZA5VbjDG0pVt4tWMVABkvw5rVr7F7Wx9aaTKZLFnPw83kA9nEZBs5P48xGuOkAQ/tq6AXuZFYtsHdPZlmp5LvTPwtW5xWUAbfM2ir0KuykBvoezadbSeTSJ1AlfUnpO5jRnsDH2hvYM4uycSeeiyjsdIuI9oMV3VcxFWrZ/OxnWOxdJ7Aq6dRIkQkUkmociiucUEaZCiPwGBCEmU00vjYOhvYuNrDCAstixrdBsu2qK6sZOLwRmLxaoTQSDnQphCBQWhJyPtBn8k3gSBoOSREYGwmVC6oDw+6uxPrSGIZWQiDG4wRREQIqSpABK9j0U4RMljRsW2QEr88gtAGSxu0kCSqqshFIvSOaEAKQbraY92QLiznnfqoe3v4xje+UT9+/Pjcfffd99rnPve5Ufl8PuhXrzXFfLF77723dvbs2cmamhrd0NDg3n333dXFMS+88EL0cOsDzJkzJ3Hbbbf1hzD//Oc/H3bOP/zDPyR+/etf17S3t1sAu3fvto52ndNPPz29YMGCrttuu63+SHN+97vfVWUyGdHe3m69+OKL5XPmzEkPXKuvr88aOnSoVwgp1yq197Phiiuu6LzrrrvqAWbNmvWGqpLfDK2trfbll18+8jOf+cyeYiX1u4FVq1aFV69e3R8+X7lyZbShocE93PhMJmPt2bPn1ZaWltUtLS2rFy1a1H7//fcfc0/cvffeW/Xss89Wfvazn+0GaGhocJ9//vkYwEMPPdSfG3nqqacm7rzzzvqi8fb8888f8T1+MObOnZtatmxZtVKKnTt32n/5y1/KjzRHa81NN900uKOjw1m4cGFiypQp+cmTJ2cWL148tDhm8eLFQ+fMmZMYN27cPtd1xowZuXHjxmWffPLJtzUf+K3gbfdgAhRaHM06yFMfebv3UuL9Q2++l45MBxXhCpQ+0MDsTrv0ud10ZDy29m3lr7v/Si5tMdWaiXY1IWGRdfPk8x4RkSEkyujJ9zA4Ngjj+5jCF5NwTFDgE/aRY59ha+QvYAQ1m87AjSfR4S6MY5DdNQjdiyFMb8cHgrnCA9WFi6IjqqjO9RHzkoTpRFFBB708MuNpzu48hRlYaGOwdBZsh5ybJZ3oJhStxLJsFAJQgadU+NhS4YpuJHlQgkQ+g5vupGLQMIwJg4BU1sUOhwgDIuIglQaj++80i15GEAwNVZHP5/u9sG8UT2mUNkgkWZ3BLqyoEdhaIdJuIIWOKRzdECZaMHpNwfcZhNNtCWWWQ0rFcBD4WmNpA47Asi36amt4ee5cJm/eTG5wmJ3jsqwefEBq2jEhVhHyj6by+/Wsd6QxxRzM4u+nnXZa3xVXXNH5wAMP1K1YsWJ9dXW1fvjhh5Nf+9rXhn7nO99pjUajeu3atdHJkycPKS8vV7/85S9fA/jv//7v1y6//PKRt91221Df98U555zTffLJJ2cPfWT48Y9/vPOyyy5rHD9+fJNSSpx44onJU045Zcehxs+aNSt3zTXXtM2dO3eilNJMmTIls3Tp0m1Hu86SJUvaZ82a1XTTTTe1HW7OjBkz0h/5yEfGtba2hr761a+2jRo1ymtubu53WV911VV7Fi5cOGbZsmXVc+bMSUaj0f47phEjRvhjxozJnX322YdtD3U4fvSjH9U/9NBD/YUZjzzyyGbYm+9YfHzx4sVtn/nMZ3qKr2GxTdH555/ftWTJkiOGko8Fh9rT/uMSiYT1pS99qTGRSFiWZZlRo0bl77vvvu2HWve+++6r/fjHP77POp/85Cd7PvWpTx13++23tx1uTx/60IfGF43rSZMmZX71q19t239M8Rpns1k5fvz47GOPPdZcrCC/8cYbW6+44opRt912mzdz5sz+m4tbb7219fOf/3zjxIkTm4wxoqGhIf9GvLqXXHJJzxNPPFE+fvz4yaNHj85Nnz49XVVVdVDt2euvv77h1ltvHZrL5eSMGTPSf/zjH5uLXtH/+q//2nbZZZc1NjY2Tkkmk9a0adPSTz755EH3c8MNN7R98IMfbDrYc+8lxJtx/77TzJo1yyxfvvyd3kaJdwnN3c28sOtFYqEoYTvM1EFTOa7yOCBQ6vnFX7ewsXctjYMUI6oraU+3o7fHmCSPZ8WWDnrC2+giwWi/lnJnDdXlw+iNVdNYPpINf32cUD4w5iIRyHcL/HIXzwA7pqDdGhAKZ3AbXeFe7FQ1se7hOM5KPF0PahhlVZuJiE3kOvtorunjN03ruOT3o5DGUBmP4dp1bBiS5o/H/ZWhmQou2zQDF03OlxAuwyQ7SPTsRkqLaP14XBkmHPOQ0oIMxOVmlAyT9RS5fBXhZAbfZAhXD8KyQoTtCCl2Um2HiZoYUceiJ1VGt07glO1mULiMrCq2BzJMcgaTSiXZZaWIhQ/UGI/s7sNJ5kiOrT/s69KaStHUa1G2ehNtjeX0TRyK9iWeB05vGun7CNvCqhyL71YAYElN2lckRSfVoo6IFPjapiKaQFo5dnkdRGSITN7H6qkjHw0jbZ94qg8jLGYsf5ne8cNZN1TiRKuZccnnmdE056jfS0KIFcaYfW6CV61atW369OlHVzn2LiEWi83IZDIr3+l9vFVcffXVw8rKytTBciCPhmQyKZuamppeeeWV9bW1tSXB+hIHpa+vT1ZWVur29nbrAx/4wKTnn39+Q7H/6Bth1apV4bPOOmvcHXfcsfP8889/29qAvRWsWrWqbvr06aMO9tw74sEsUeKtIJ/2sbZVY2oM+bog7SazYgXRGTPIeIrm7g2k/DRZT5JXeRzpkHUFG3t6ydlp8DVVyge/DWwDfh7cFOlsH/gKO14RdE/XSZy4YkfnEGp7+otG0fVrye+ZhDusG1PZjU6Vof1KjKkjUr6JaKwTndYoFGuGtPOh10YSiZcjvQS9qQzhsiwTdw9mSN8MIqGCbKVwECLIAzVoKipGIOw8SmkEDggXaXtYkTS4hfwzA0iDZYWxwxKETVHmRqMQRva3DCqLJEl6veRchQmbIN8RgTEqKJrROgiV74fwFcOfWEty9KAjGpjGGEJtXYS7UwzxfdKTGuhU6cBLqQ1eWBKXERxhoQekzwV7KRy70KpIiEDlp0jEsUjFnKDlETB2/QYEgs4pU6ncvolMqA7Lec+nMpV4C1i2bFn5lVdeOerKK6/cXTIuSxyOM844Y1wikbA8zxPXXntt25sxLgGmT5+e37lz55pjtb93KyUDs8T7BuVpTF5AwiFT1cPWnteo6wGUQilD2JEoYcgrj45UimhI4GcFoSoL0gLdqYmEbYxIk8v7ZGUWbcfo2bkF0zeYxOYxVM/cBuk+pGWoE2HS0Q4qY6+xYtDLvFj5GmfkL+XZwb/gJO8kcqFy6t3jSEW3ELbbyPoWYTTKGFoq+pj9ajkGyBYyv5y6oegejyHpKDJvyDh+0OMRg3KjpHs6sGSEWM1gBBqkClooAQIvsL4AxxEoY3DLooBDyDj4WuFIgxEGCwtZsNGEIKhC1+AbTVg6uNrHFlZgrGrTv+5AjG3RPmd8oBV+8CH70Hf8eMTM8aRsH1tlkcigdZAx+BEHK1aB8A1CBNFLbSSWMFgFEzPoUFSMtuw1eKUUhB1BXgsGd/SQjcfpHNrAYO2CEGQrXXZWZzjBz+y/pb8J3s/eS4Bvf/vbBzQnP1rmz5+fnD9//uqBjw1UzikyYsSIfLHB+FvJO3Hs9vZ268Mf/vCE/R9/6qmnmocMGVIyugu89NJLze/0Ht6LlAzMEu8bfK3AEzg6TKeXpi/bw9rdO5mlPkj7aymEBiEVOddja3eeccMqA/UXY5DCIh/NEslbKOnieYoMady+PIowWCGQBqMkGM1LodeoGN7OBHc4XirMIK8OLTfx+IS7OXnbOQzrm8yD07/J6O6p9EU66Yq3MK1rDGe3j+I3U7YQ9yNEwnEcQpRXRFDhCjw0hBTCB6M1JihaB2Nj/CROuJpYuBoT6QVPIoUGUVDe7h8MHj6WECgtURK0CaGVIo/G2IH2uGUVLUyImjBpsvhaU+aE8bTCEhKERCiNObAQGIDM8Goize14LT2EGg7dd9gYQGuiFeVEgZiK0J3LFppWSrQV1JiHbRetLXJ+GK0lllBYFDXJTdBknr2N1/dFU93bTf2uXfRMnEW6TJMZXU2Ps55XhvXyj/qQ9QklSvQzUDnnb+HYQ4YMUW+XMlSJvz3ePWVrJUq8SbQfeOLQ0FTbRD6XI5vNkEj30dueQbYJlHbJpX30bgsbB43B0xpPu8TiZRhpENrFs2MYpVDbRpLdcAK6t4Gq6TvItlXRlpWku0ZSv/p8VjpbENIw0R3CDas/zrjewdjaQTl5JvYMQzgdNGYCoZKOSC8PN7xKW6yXM5+pozIUpqxaE4rYqJxLetsaMh0bESqHMgJPOIWyF4Nye/HyPYi4xNgedqi74O0reDC12qcUx5ECIWTwLypolo5BG1PQAy82JALLOFiFgiKJRIogPF1sWOlyYDTI6c1QvWYXw17ZTvnuw6cQxRNZap9/FfpSiBfXEO1IIpAYDPmaOEYGdetSGkJOHm1kobJdYEkLSwgGbVzDpCeXFQTeKZT9FCvLg3KntknT2HDWAnQoErQ1Asb1lfHZVWOoCR0g4lGiRIkSJd5CSh7MEu8btDagJEaByoC7VtPXEyKbyZHL+FiuhetmyXo+Ed+CnMAog7I0rsph2UA4hd+Tw4QiIAy27sZlGCZXBfSQ311JuGwMU+K95OJtTM6MQCoPgYc2huN7m0j6O4gOLuOj249HRcPktc9JHZPpc9L817g/UNMXwvYhsbsbOaScaGSvRzEcq0aICEqH8XU5DikEhmhZNdFYFCecxGCwhRc4L4tmpVHFHj5IICbDYFl4BW+fQRM0tzRgRHFoYL4WQtzGBDmYEhm0KRICMaQaK9dRMEr34iSzVK9tYc0pE8jUlXFQbTNjENoglcFKZjCZHHLjdmR5DIZaew1iIfZZGwNSGCSGKlmG9FwsoehpHDPAwJR79yTyBb0f+l2boe5u6lavYcvoWrxD9EQtUaJEiRJvHSUPZon3DW42hzFJ0JDeYZC7evBdScfWNNKSqJyHMAbHxHFUFDpjmLTG9RWeyePs3o7s3oNK96I7e/FTFQjlUF33DDWDX8bKpqiatoWUb2PvbqKa5Ti7PexUirSX5JvTfsfKmi2M6huC7e71+llGIrTPpvJmBvWEmfNqLbGqINXKaA0IQjGHynGTiZYNwjgO0rIx6MBLZwy5ZBvQhZQeRaPS9lOgFWCQ2sP0W40CO7C2Csbjvs3eA0MzQEpBZSTo6KIwWEIyKFRBXSio5naEhY3sPyaAlXUZ+kwzXsShuzKKZl81zCK1K7ZRub4VZUt2f2AKanAt+qKPo5tGgzH09xYeqKTZnxtqEMIghSGe7qBm40bSdYNBFtrF+5qkn6bgl0UAw9f8lfKWncUTwzgWJuazaUSKlvQbTtUrUaJEiRJvgJIHs8T7hvSeTlRiD1QNQqd8jBd4NXNpD9+Eyck05H28nE+5KQty+qyd7MloomYPluvjuzl85WGbCG7rKEKqF1sIhJ9BEUZaOaz67eSTUWIphRIOtsxT6QvO2DGdUWo4oJEDDEwKxTJjegcx+bXCQzWGwaOrC4U0XuCZE5pcphs7HMKKlOEY0BpULk0ulcAYh3A8FHgW8XFkJugl6Rc1vgvWWb8nsijebXDsvUblgVIo4ClDTy7L4HA5NeG9Urthy8EScp9CHuErvHiYjlF1VOU86tfuJDNtBLpy31ZGoUSWvIAZz+3COA7+yHqwJKIQpi9apR7+gJC92VvQUzCM7boQXX83Ex2J4igXbBkUdAmDbwVWqgTKujsx0aCXslddSdfffYCc2UKyLN2vc16iRIkSJd4eSgZmifcNyvMDBR5AJLKQD2QT/azCQ2GEJrK9B52JYwuFrhlLrrudaGUFYd0DUhLxFWFpoYWFLl9JqDODcOMI1w/a9iifoZZCmB5cXyNshS3zGGWY2TUaXeuTtjRWfq86mQR8pahJ22QAJ1aFE4kgRNDX2gDCGASGfKYHo+NYTg1SaHwtsCwHKSVlNTEUutB43CZidZM3FTj5FGJAGFggsIoeTAL9cYFGGytoaL6fhRnp6EaGNcK2sMVBWhLtG8CmbsU2coMraBs/jGhHgvodXejWHraef1L/GK1h69wJ1GztoNrX4OfJ+xq6e7Fe2USoqQZXhlCowvnsNTAt6SNEECbHGELdfeTra2n8zZ/IDR1E3wemDGhhFDRgFwKa/+6jhC0DhdpXIaA6F2bunhrqP76vJv2xYM1TT1Rl+nqO2WdorLLan/Lh0w/b8NuyrJnjxo3rb4i+YMGC7ptvvrn9WO1hfx588MHKtWvXRt/KYxT57ne/W7tkyZKG+vp6L5/Pi0svvbRjyZIle44880Cam5tDZ5111rhNmzatPfLoI/Poo4+WX3DBBWOGDx/uAtTU1Ph//vOfN1599dXDfv7zn9fV1NT031E+99xzzS+++GJs4HiAW2+9def8+fOTxdew2Gj9ggsu6Lrhhht27y/3CPtWlu/YsSM8ePBgLxKJ6Pr6enfz5s3RF154YX2xZc5FF13U2NjY6J5yyinpCy64YExDQ4Obz+fFOeec033nnXe27X8OA/d0sHNevHjxkKVLl9ZKKY2Ukh/84Afbb7nlliE7d+4MZzIZ2dPTYxfX+t73vrf9jDPOSLe2ttqNjY3Tbrnllh3XXnttJ8C0adMmuq4r+/r6rFwuJ+vr6z0IGtKfdtppE+LxuCo2Wj/ppJOS9957786B+xh4jbPZrJwwYUL2lltuaZk5c2YOYPbs2RP27NnjhEIh7XmemDt3bvLb3/52S11dnYK9fzOHut6PPfZY2Ve/+tURqVRKGmPEF77whd3/8i//0lE89g9/+MP6zZs3ry5Keb7fe8seS0oGZol3HFOIlYojSKV17dpBJpFgRNOUgz7vuz4YhfYAXxA3MZTK05t06RU5NC6VuQpyOY+wbke7ozCui050oaIelogglYsKBy1zlJ8mHMoisha+tNE5F9HXyaZ4O3WqjDKtkfiE7AyZXBwhFb5RYNnIvEL5EbQvkbbC620jn+khFK/Ajg0uhLr3uQogDBW1o5COCPJJAVuUI+w4gwZnMA706TRREcbYURw/DeiCUW0GroRdyKMslsMI6aF8iZRQHtr7Z28nUgx+agVjj6tj25ShVDvxA66rVajiBoGdzGFnXTwhUNqQqSunZ3AFlEWw03n8eBiMYfCzzbSMrKVmQxCa3nrS8dQGJfuQTGPnKwmXW0EY3OxrwEoZyEWCoTrTRu0zK+g7fgLJyWNR8YLamwBpRL9OsERiY0GhIEm6LnV/epEdI6vpMzbaP/YdVzJ9PXZ57aCDan6/EZJdHUdUBQqHw/rtqvr1PI8LL7ywD3jbGkEXtcjb29utSZMmTbnw/7P33lFyVGf+9+fequrck7NGM6OcJUACESQw4DUmrgDjsOu11wbWeI/Tmj1r7+t3veF4g9ew/Da8jmADtn+7DjgANsaATRJglLNGWaPJqWc6V1fde98/qmckIQlwALx2f87ROeruqurb1dNdTz/h+/3jP07NnTv3N3aOfx3O5O992223DZ1O6P1M25/4Hvb19dk33XTT7MnJSeuuu+46pY/jxMny8847b8Edd9xx7OKLL84D/Ou//mvjhz/84Zk//OEPDz/77LOxF198MXHPPffseeyxxxJTz51Op+WyZcsWr1u3bvLl1vRSHn/88fijjz5as2PHjt3RaNQMDAzYruuKKcmkhx9+OHnnnXc2v/RY999/f+2KFSty3/nOd+qnAszt27fvheAHxMaNG+P333//Sa5NTz311L7W1taX1ZU88Rx/5Stfqb3iiisWbN++fdeUm8/9999/6OKLL84Xi0Xx4Q9/eMaVV145d8OGDd2vdL57enrsP/3TP531ne985+CaNWvyAwMD9pvf/OZ5M2bM8N7znvdMANTU1Pif+cxnmr/whS/0vdJ5q3AylbpRhTecfb9YT2rwZd3EAMimxsmngwSPVhqjDcb3GX/maUZ6juCmy5aABrQPIeOBE6VY8BjNFbFzY0jXIx4C6WtUphfjlTCZIRhLYUol0ApTjCGGr8C4bUjLRleFKfgl3Mkcw2qY783YRJ8ZwPgK19MIoxHGIKVCmSCrKXyNkB4YgVXII8oOOZblYIxAyBMCnnLtWYjAb9x3Cxg0yiiUl0Xj4zlxPOMTFWEE0GzXUmPVYvluoInJ1Esvl8dluWAepEcRMihLaw32CYG8n4gx+qZVDM5vCvTZX5KthGCgRpcD2KbnD2Bni/R11KONQQjB3vPnUXVsjOo9wfevLPo4qSwinabv3NlsuGQeuqUBTxloqUffeBnFZBipgsl3SxzP3AS9l5poKE8sVEDVJ8ks6MKrrSI/ZyZuSwN2+X2WZU15zyiSk+O0b34OJx84xRlLoiMhojaEI5R7VX83GRsbs7q6upZu27YtDHDttdfOuvPOOxsgyLbceuut7YsXL150wQUXzO/v77cBdu3aFV67du28JUuWLFq5cuWCLVu2RABuvPHGrltuuaV99erV8//8z/+8/T/+4z/q3/Oe93RA4Jt9xRVXzFm6dOmipUuXLvrpT38ahyDLc9NNN3Wdd955C9rb25d95jOfmfYM/6//+q/6+fPnL16wYMHidevWzXq545xIS0uL6ujocI8dO+a80nOvW7du1vnnnz+/s7Nz6dTrPpHu7u7QypUrFyxevHjR4sWLFz322GNxgHXr1s36xje+MS0vcN1118365je/+br6P8+YMcO/++67j3zta19r0vqXG0a7/fbbR44ePRp+6KGHkh/+8Ic7/v3f/70nHA6fVJ+oqqrSy5Yty3d3d4fPdJzT0dfX59TV1fnRaNQAtLa2+l1dXa8Y6H/nO9+pu+OOO44NDg46hw8f/o3ZqJ7Irbfemlq7du3kPffcc4rPeSQSMV/4whd6+/v7Q88///wp3uMvPd933nln0zve8Y6xNWvW5CF4nf/0T//Ue9ddd7VM7fOud71r7MEHH6wbGho6NcVc4WWpBJgVXjdyky5e6dQLvV8q4ZeOl5S1CZxrXkqpkJ/Odh7eNsp4fxZ33z5SRw8zeuwofq5IMIIMlq0ImRwGSSgO4RqN5Ugo+YG8j8yTzQ5DsYQp5TCehyjmUKoGLXIcrdnFxvay0YLvgnbBdUlMaN6xZSGNPS5FNxNMShuNLV2kpYOgy9ZIV2GrHOgsxewYoer5JOpnY4cigESIE8+DQGoPSxXwS3kyY30Y5ZMd2U9+/ADZkd2UcmmMgZCwkUIihSz3Yppyefz4IM906VhM9WBqbKuIEROniqJLSampHhUOoY2BvIsxhlTew1dlGaByIFfyNePLZ9JzwTwmG6unc6YC6D1vDtLTVO0bBAzPXz6H/s46Jmpj5KsiSCHwVPk9nciw+sHtzN56FHN8/nv6uZKRLGHHw7YCa87MigWUGutAGyK9QzT9ZD2d3QMIEbxOH4XtlQhnTki02ZLxtSspzqjFiYqTBpv+NzPlYz317ytf+UptfX29uuuuu3re+973zvryl79cOzExYd9+++2jAIVCQZ5zzjn53bt377nooosyn/zkJ9sAbrnlls7Pf/7zPbt27drzuc99rveDH/xgx9RzHDx4MLJ+/fp9X/nKV3pPfO4PfOADMz/+8Y8P7dy5c8/3v//9g7fddlvX1GMHDhyIPPXUU/s2bNiw54477mhzXVds3Lgxcscdd7Q+9dRT+7q7u3d/6Utf6nml40yxf//+kOu6cvXq1YVX2mfPnj3Rxx9/fP8LL7yw93Of+1zbkSNHTgps2tra/GeeeWbf7t2793zrW9869Bd/8RcdALfeeuvIvffeWw9BkL5p06bE29/+9jNma6d8vBcuXLj4E5/4xHQA8sUvfrF56v7Vq1fPP932CxcuXLxr167TBnmLFy8uaa3p6+v7pSqKlmXx+c9//ui73/3uObNnzy5eeeWV2ZduMzg4aG3ZsiV+1llnFX6ZNa1bty7d398f6urqWvqdNLoeAAAgAElEQVTud7+740c/+lHidNudyIEDB5zR0VHn0ksvzV933XWp++6775QA8HRccskl86fW8/d///dNr7wHnH322fm9e/dGTveYbdssWrQov3PnztM+fuL53rNnT3TVqlUnuTCsWbMmf+DAgel9E4mEete73jX6L//yLy9vWVbhFCol8gqvC0ZrBg5MUN0Uo3Fm8pTHzAmNgZuGNmELm7OazkL5GtsJfjgWs1lsJ7h2lIo+qb4JJg72ooouhYkJvFwOmXQI1wpk0UdXxzFZiZI+Kj2KLOQgVAV6EvAw2TSOsBB+CTP1Wyt/NlKWyM75KV0TwXQ1ygOhkPkc46lRYkJix6pxtB2sW/tokSYWM6R0gog3jlY1aKeIm+rHz+eQhTRVte1BEHdKgAmgsXQey6nGitTiFSens26RZAOhqELhBf2V5bUKRCBPZNR01DiVwZyuasN0iTwcUsetFwGUou2BxynMaMJ2NMfaq3Ae+imjf3ABxeokIUtgW/Z0AOiNZwkPTpDtaiy/jjJCMNFaQ9O+AZx0gfqNh1CLmjk2t5Gir5AyyKj65QBTPr4BgNH2uuD3wEtaI04MgBN7DyNKHpnl84kf7KF6y16yc9oZbYsjRZC7lUhyzS0caJ6LbXnTPZhMnRFl8L3fiirrr82ZSuTXX399+tvf/nbtX/3VX3Vu2rRpuu9QSsktt9wyDvD+979/7IYbbpg7OTkpt2zZkrjpppvmTG1XKpWmz/oNN9yQsu1TLw3r16+v2r9//3RWKJvNWqlUSgK85S1vmYhGoyYajfp1dXVeb2+v/eijj1Zde+21qanyZ3Nzs3ql4zz00EO1c+fOTR45ciRy5513HonFYuaV9rnyyisnEomESSQS/gUXXJB+5pln4uedd9500FAqlcTNN9/cuXv37qiUkqNHj4YBrr766uzHPvaxzr6+Pvub3/xm7dVXX51ynDMn3X5TJfLTYU4nw/AquPDCCwvz5s0rfOhDHzqpV3Xjxo2JRYsWLZZSmo9+9KODq1atKj788MPOq11TdXW13rlz5+6f/OQnySeeeCL53ve+d86nP/3p3o985CNjZ9rnvvvuq7vuuutSAH/yJ38yfvPNN3f93d/93St6xL+aEvlLeaXz9WofN0EV5hVP/ic/+cnhFStWLP6bv/mb17wX+XeJSoBZ4TWnVCxweMtGfDUL2zk1aR4EacczluOFcRw3ypHBUYwxzD6rCeX7lAoudjiopmltUL6imPaImBJDWzdRyilCkXLFy/fBEhgj8D2D2B0mFGrC1OegqILn80tII3D8JGORIR6bvZHFAy4t6dnMn1xIbHwYpAbjg9RMhHPsjWdY2JPEL+bIOxGswjDjsogT8sCUQHlIPLRlUGoCP58jHKtFRmoRRqGIAQopT3SWKU/eGI22DNovUCymcBIhIvVhbL8WJzyO0oG+ZVxMXWfLoZ/WIALhcmUUIWGXp7AJMndT09i2RBh50vP68SjRvmGsiENfWxUmEUO5pePrAgqepmBcnMlJ6nf1kWqthdjxapEEZL6EVfLJttehfY/Ze4YZmN2IEhopKQeDwToKF5/N4dEBMo1JDJqICBGWp/8qsnIFZDHIbudmt2OkJNfeTEGlAp90DDaSiHBOGY+ve3oTqeoQY5Eo+dTr1kb4hqCUYt++fZFwOKxHR0ftOXPmnDaiFkKglCKZTPpn6uVMJBKnrdUaY9i4ceOeRCJxygX5xNKsZVn4vi/OdPF+ueNM9WA+/vjj8RtvvHHe9ddfP9nR0eG/3D7iJbZOL739j//4j81NTU3eAw88cFhrTTQaXTn12Nvf/vaxu+++u+6BBx6o++pXv3rkdK/7tWb37t0hy7KYGiL5ZZFS8tIBoV8muD0Ttm1zzTXXZK655prM8uXLC1//+tfrXy7AfOCBB+pGR0ed733ve3UAw8PDzo4dO8LLli1zz7TPr8rWrVtjK1euPK3/q+/7dHd3x5YvX35abbITz/eiRYsKGzZsiJd7jQFYv359bNmyZScdu6GhQV1//fXjd9xxx6vKsFYIqJTIK7zmKN8nO56hlCuc8uUPYIyezohli2km8yks5aCVwS8F17rs+CipwQn69w+STeUxGvLpIoXsJBMjY5hiibBvYw8F33/CVyAFtlXELylKyQlkKQ5hC7SPNBrtuQg7RsS7GE0IDGxt+xnN2Vns0SVyMo+2ZeBmUyzgD41yrDlPPhlMdiuviOtOMj5ZIlRSoD2ELqFNgaztYkUsEjNaiSQacKIJjAijTXQ64Jt+/QRZRtvPYqQmVDODULwWjEYKTSg8xtS0tC3kST2UllHo8sUlr4sUTekkl54g6ArOYSjnEir4JHfuJ9w/TOxoP+MXnU3/TW9hx2WLaBzM4J+zACtXRJ3wC195MOG6DDfH2fC2ZfRGT21z0AZCkwV8R5KrTyCNwRIWDh6tMkWn2DX9G2I8HCVTHS1rhRoccWprU/Xm3dT8YjuTKxaQuujs8ou1yM+ZCRMZqsaz5b+l4F/D4QPM2P6L6f2FCPpLQ2GLcEQjnV+qBe1/Hf/wD//QPH/+/OJ999136Oabb+5yXbf820Pzta99rRbg3nvvrT/vvPMydXV1ur29vfTVr361dmqb0/WrvZQ1a9akP/vZz05fYJ977rmX3eetb31r+sEHH6wbHBy0AKZ62F7Ncd785jfnbrjhhrHPfvazza+0zyOPPFKTz+fF4OCg9cILLyTXrFmTO/FYk5OTVmtrq1cuKdcrdfzv97bbbhv90pe+1AywatWq4iudg980/f399q233tr5vve9b/ilmfw3km3btoV37Ngx/aHZsmVLtL29/Yx+q9u2bQvn83lreHh4e19f346+vr4dH/rQhwbvv//+V1Um/2W49957a5555pnq97///eMvfcx1XfGhD32ovbW1tTTVXnEiLz3ft99++8i3vvWt+qm/p8HBQevTn/70jE996lOnBKef+tSnhu67775GpdTvRr/N60Alg1nhNcdoTW4yh7CzKP80yRFzvGSxb+uLjPZ007ZkFlobvJLi6I6teMUiQoQoZgrs37AHaTXhFXzcySF8K0Qx62KEf3ya2vcxCIaHl8MwhOIHyLRYREQNaB9lBMbUIHULUkXpyM/g/Zvehh8f4mDXw3THejjYOMktPReCZZEuDSFLPpdubaYh3o6OaNKZPsLhKlqbPHTcxvcKWMrGp1DuH1Q48TB+CgQaIf2TAr5pynY6WoYRIiiBK0sSqQq+3zXmhD7F499t2o6CcvCtMBKJ0YXy7LgMzoMpb1/epXXfAHV9KYRtE+kfwZnIMLliAX5NEoSg/dAIHBqhAch2tCIETBZ8HOEQwsEXGktaeHhETtTFFFAK2wy8aRHK95mYkWT3wmaSIkKr7OPy8HYADviLgWA4Z97mo0QKLlsvXXBy2b6MH48R7RnAKhRRyZNnQGr3HqbKLzJ5/rzAoUiA5XsnSUMBpM9ZRNobxxkbQYZ+8191sepa/9VMfv8yx3ulbaZ6MKduX3bZZZO33Xbb6Ne//vWGTZs27amtrdXf/e53M5/85Cdb77rrrv5oNKp37doVXbJkSUsymVTf+973DgH893//96Fbb72187Of/Wyr7/vi+uuvH7/gggtOuSCfyJe//OVjt9xyS8f8+fMXK6XE6tWrMxdeeGHPmbZftWpV8fbbbx9Yu3btQimlWbp0af6BBx448mqP87d/+7eDq1atWvyZz3xm4OX2Ofvss3OXX375vP7+/tBf/uVfDnR1dXnd3d2hqeN87GMfG77xxhvn/OAHP6hds2ZNJhqNTn8AZ86c6c+ZM6d47bXXvqw81MvxxS9+sfnb3/72tJnVD3/4wwNwvN9x6v5PfOITA+973/tSU+/hlGzOO97xjrG//du/fcVS8m+CM63ppdul02nrIx/5SEc6nbYsyzJdXV3ufffdd/RMx73vvvvqr7rqqpOO8853vjP1R3/0R7M/97nPvewE5yWXXDJ/KrhetGhR/vvf//6Rl24zdY4LhYKcP39+4dFHH+2emiAHeM973jM7FArpUqkk165dm37kkUems7cvd747Ozu9r371q4c/8IEPdGUyGau/vz/0n//5n0euvvrqU/pZW1tb/SuvvDJ1zz33VHoxXyXiV+39+G1g1apVZuPGjW/0Miq8ArmJFC/+8EcU8nHOecsltMypo1TI4xbyJOsa2PbYj0nUNdDQ3sHjL/6A3qEelpzzVtpL83DzPuFID/nJFEOHJ/B9i4b2NkKxToqjKYoH16NDJTKZHKl8jkjIkFxzMaF9PfgyRM/+Doyx0FY/hfYjOOFq7L4ivswidQdWrgu/4Rn2JEZYMLyacGwCER/lmDOINZZmqZlBzi7xg8YdFHSWOWN1nD80G0sK8tJgFYvUVqURdQnSbhq8KFpNUso34XtprIYadC5GNBTG0lnyXhJhZUjGT7yWG2w/xwSKuduH6W2czZg3SaIpghWzKRiXyNT0uFMb2ECW6fVG0MbgCJusDo5ZIxPUWzUM5xOkVZbGzBCJ/Djp+jjRrEudlaT2hW2AYPDaSzDhEP3eGM6kS4uVRGfzFFoaqUs4ZAs+Sht6vBFaD48QCUl2z4iTIIYlJbYMpIK0gZZCkY6fBoNRT751MTEniWSU1eHDeHIWh71ZdNTFGMm4TBw6iG08RtpraHSqSchTk2HJHftJ7jnEyOWr8eqPe4mLYwMMtdgUSgbtaHwNzWImvpfAtjx85VAdm8SSmsHSOJOjIyy86f1cdsVNr/pvVgixyRiz6sT7tm3bdmTFihWjr/ogvwX8rmv2ffzjH29LJBLqdD2Qr4ZMJiMXL168eOvWrXvq6+t/d6UGKrwq/vmf/7nxa1/7WuP69eu7GxsbK38Pr4Jt27Y1rFixout0j1UymBVec4zWKF9hlEtuMo0xtYwe6yE3MU7i3HqMMbi5LP3795KfSKOHITdURCU0vqeYHJhA6wkynk/RpEnkarFCmtoaSY9nKGkfjY0wCmEk9rFBvJRhXDXQ2LqHnFtNOt1LdGgpumYcWZiLox38qn2o2l0UYnmWHl1HumYHkXiQyJhZbCIyYTPUmOHuOc9z9tBMqqwIs/wZ5clxgfJccvlRckUI57KEkhKUR2ZcYNvjeL4m7KXxiSKkh23lsXUSK5znZGdvAVohfU3jQIZiLEumsYFw3MM3PkIIDJrAVDJwBUrsOUh+zkxiMsTSH7wAwLY1swnnSvizA5tHUTbDqRsYoelYPxuvXM6sLUexYllS5y/HmchiQkECrt6qwq0yFC0bLxzBzhXIWgJVDh4lktrhDBYGWuIoAfa0M6VAac14XGAvacbxJVpaKAURu8hmfwGNoQ7ARyuD1oZsWy1KeBRxTxFyn1KCzy6ajXZsvJrjQ2HFUglVX0M8Kih6aZTRrHYOUG2OUJJxetU8UrQCULVlD7HJSbbMr0GryrWiwsn84Ac/SH7wgx/s+uAHPzhUCS4rAPz1X//1yJTIeoVfn0qAWeE1R2uN7xmMdpkYzjJ6LKg+aN8PZIeMoVQoEIpGER4krBoKhTx+SKM8RSFXwglbmJBCeYpitkhjZxgzNopnoFj0cLVHSAiM75MfG0ZaLRTSUaJR0G4B9EjgxDPcymC8hya3AenWo+q3UWVCUP0UNd4YJb+aovCICYfBeIZYMUZTOoqfmWT55DzqZQIdViggJKtRKg9enny2hBE2AoXyBdXVgkjUQgsfKQzC+EEpVxrC9qktPH4oSSifYv+KNmYeGmCoK4ItwvhGnaJN6aQmqdp1kKpdB6mPTFcCWbjpGOGCR3dbG5RdGw2CY4tnE8ulWf3Q1uDO8RypC1ZQbJ9WWiEsHbRQaGXo+Pnz+JEwo5eei9LBQJVlbPavno/wXVAexjLI8rKSIsvS0F52y1mMLJuB5TuIfAGfAjdGN9Gjm5ktn4AwpEqzGTRriSDI5/M4EeuUANPKF2l65BkmVi0ht3DWSY+VPB9hoOPgBI4NxxoUXZlBRp9J0Ln2ACOhwONdYPATMZTQCGk4Tevv7wW/y9lLgH/7t3/7lU3m161bl1m3bt2OE+870TlnipkzZ7pTAuOvJW/Ecw8ODlpvetObFrz0/ieffLK7paWlEnRX+LWoBJgVXnuMwSsGmbhCpsjkSJ5owqCUwphAokgrH4iijUAYKKTTuCEPrTTK8xjPjyCjVZgQ2I5PvCZM/94Sk4VGYlHIlSYIYzBKoQp54g0unS19uBM+quSB8ZANG+krVjEWmiDV9hwL8jPRHghHor1B3N5+GBiARXM4EO3lhYadvGPzQq46Wp4tqBboqMAKO4EouXaI1FbhTrrELInWGregiNY6jI96NM0MkaOEMAaPErYRCHl6MWXpaVb//BCTDQmqxrIkJ9KolmYcaVPSfuDOIyRRGcKrDzF01Vqaf/wMpeo4fbPqsGybmTt62fymecTCIQSGWZufp2aojxevWcvgglaM0Ywvm0tN4aVimAGCYNJ7YOkChCUoeQaNQWtImDhhKRgXYwggFrYRQBiXBHnm2H20mlF+xB8wNXgTscI8VFhFre0y2wrasEoihjFQM5Bi+Yb9bLxsPp2RA4yy6LhUFJCd30XphLL4FJYMbCUjG3eS7Grlve2bGc7U4zck2WzOYVDPLrsAQX5eJ1ldwAwfgdP1/lao8BJOdM75fXjulpYW9Xo5Q1X4/aMSYFZ4zVFKIaQDxsVzfdy8j2WXMFqTHR9HWjbxmlrcQh6lNGgHP68IV0vwJL7nkyvmicaiCAFCBkHn3t0lisUmojEPbSawDPi+wvgeU+m1UChGSGfRfhidE3Rakk1NzxMTNosKMxECBkKj7O3o4fxMNXgaq6efzkyOTt0O8eBHvBWpIRxqxPghtPCwZKlcyfWQUYvOWB0pO08h71IsaGLRCElpk9EutgTf+Cjp8tb4jxg2texUJycNLE8xNLOWvhVdLPnZLtoOjdLX0kIIG41HSPjMsiYo0AJKoxIx+t9+BWmVp88fpb5ok4+FiOU9Fj75LKNrzkGXtQzPe/gZtl51NrsunEO9XUWx4fTDvwJQxuC3NqCUi4XC10FA1+SXsDfvIz+vnmw0kEQSCC53nidvIjzhrmKpc5CYKDLpO0QdmzpRRX/JJyU1Wp9F3jM0JyMoU8Srq2LPWa2YiMMiuYUjRtPDMmS+SGh4nEJn2ynDPUoHPuyWZVH6o2sYnRhnS3Ecqz9MoX02/dZC4iLN7NB2lthB28CD+p0A5R8wvzZaay2klP97G9crVKhQ4TeE1jpw8jgDvz26CBV+J5gaGuvZtR2v7M6jfYW0bKLJapxQjny6RCFTwC3k6e/eHQQrUmKURikdWBOWfNIiRbwmhGWDMgqNQhuDpz2UKuE4UJc4RnVVFjtawhICFQlhlGKwr5X0WAITiVBMRBiOuzzQvhk9dhYt2Vm0ucHQp5PPENs9wGBsAtXRBvkCcjIzrct5ZJbPvVcdhdoGhITA+3u6+RAjfKKxCMlojNHeLJ6WhGocZre3EcJCGhBCYQsfIw0JkaVNnqSJTDhTIDma4fDyduLhJL0XLsEp+iz//gtEskX+MLyBd4bXM8saQBbytDz0JOHBUVCaeO8QtpF4MRu/LYbX3MDk3HZ0NEzvkpWkqwLnuy56MMaUfcXP8N4RJPpq1QgXHPgxs577BRiDMZqmR9dTNzCCNMFEuzJB4H1Qz+Sg7qBXt/FQaTUuSRLEWGjluCZyPytCB4Mh+bK7kKWD9gg/EWWgsxYTDrNJX8I4MxCeT8vDT1G7YSey6HJAn+zap7VGShlYYUbC2K7LZm8WoaN5wmMpBIZrk19mSSQILnd1dzDr4RewNJjfTIC5c2RkpLr8pVqhQoUKv7dorcXIyEg1sPNM21QymBV+oxzc9CLNs+eQGR2hob0DJxSeliaSlo3npqlpCZFLpVBeftqZR0iJ1gqjDQKJIyQT7gQtkSbypQzKk2ip0UozmB3A3jFGU6PBnexjaKIBZWrJ2rV4bgEpejGOQGsJBpRxmYxmGYv18Z3l/8pkZATfKjHOOBf3zySqw6z7WRNWbQrV1gLJBJG+UcYiBWoPZXlLppOwtoPhE6HQJlQWLDcUTAHLhPAB31Vo3yVBYI0YePZAKDyGQmCQPOJdwnzrMBGKFAncyOKpHLM2HWb88oXYUYtSVQw3YsEktHT3IldpBq1qhkwLQguKbY3ocIj4gR6qt+1j5JK5NNdP8ObQBrY7lzE5o4Wmx56nOpZg+4qzuSiynpXJPWxLNVEXGsWjGc2p6jphWxKyBHJAMbYniSSP7Sui45MYKTh44dnkkgZLKzxTYl3oZxzSszmm2xAYlIZqK07WCMIieM+TtoJybDfH2sUifzPDvBOhi8SyLk40hGeFWSw3cMCcRW7WDKTrMVDTxB3+Su5yniJadj0KspcSKSX2kUMsePFFCqu62HrJMlrjjZAXFHScqMzxFvezvDl6kItbNyGMQfu/fjuZ7/u3DA4O3j04OLiUyo/zChUq/H6jgZ2+799ypg0qAWaF3whu3kNIgfI93GwWrTW6nAUsZl1AEIolKeYmUV7gPd7Y2Ul2fDzo2BOCvePdaK0JRyUkFQqNrzyyMoOpt3F9F1eVsI7OZ19+gmjMR4o4udxc7PAovtsAgG0VaJk7hLAtlC8xqsC8dDPtO2KEk7Vsrz/KszXb6U72c96ITThRA1XVCCkRDfWQy4EQfHfVPt77k04oOljIshONQaDRKoyUHmFbECaEY9lUtSQo2h4h6SCFQBlNGCuY5haCOZt7aGtNM3d2H76x6dazp8/fnjctphSzEQiEkOw5fxbFIcXMF/awx2pn/4pGOm0LGRdMnLcMAK8qjl8VR9cUeHPoacZ1NZM04iclBgjnswgFx2pmMkf08geJncyxhxgzbWw1V5zyHgoRrHNmwyGq144RayqR23mYePcxxi46G786ATqLUYYIJWplgZVyF3vUXISEt1ibELqdHSwjZc3iZ7qTEZ0FAv3qYd1GMyO8Nfw/lDIWB59oZmRlEzVz4uS3KWITB9m59nL26jq+peazTIwiy7qmNi4eFlKUrTAtwAjaD40zXBdGJBoRGH6cvwXb5Hln5ABnte9kvK0DPTyI0L9+gLly5cph4Lpf+0AVKlSo8HtAJcCs8Buhd1+KUMhGeR4Tw0OY8gAPwGhfZsrzFYzB94v4vgEj0DrwqgbwlYf2FMIOZHv8Yp6+4W3kVR5CEbTRxE0dbiRHXW0DttrNyHAwdBlKHEL7SeLxHuxcHxBI9RgtAIVEUVMS5AmzLD+HJYerUek0IqzIFybIJqG57SyMUejBEYq5HFd3z8Vqa6RdR45bORqJJTTG2AjhEhI2caJ4WmOFbGyhaLED8wolLSwcEMEceHIsh+MW2dCxlIOldmr7RuhrdFi56TCTzdWkzu+anqeOCotEvU2qq5lYfJy3pTfS81Q93sUlhhvLOsmWhdvaiCj1ssGbT0g4LLGeZnvsckbffD7FEU2upooePYNur4MFoUDLeoe59GXfy2y4EdmiOTragNvaQKGlmVJzPXbBBS2QUuKLGE+XFpEnCOoFAtc42MYGYYJWCSFxhIUMegvImFrqOAaAHVM0npdmRlMaKWx2Rs4hZKfo9WPcZ4LXt8/Ucrt3MfeH/o1F4ijPcg0XOz9ACkF3x/sYaWyh8es/InnsEAOz5k47JCkT4f3OfwLwI301UzJQFSpUqFDh9eMNCzCFEBawEegzxlwjhJgF/A9QB2wG/sQYc0Zrqgq/XWjfQMgweChFbYuPEDqQIALGs2Mop3yBFwKvWKSQKZEeK+AVC0TiCQB8vxRkPaXE+Aq/WMDzg/5LtIJ8ksKhOVizd9A1u5XBLeM4kSGEnURaWWobtyGFYiJ9DqW+GM2dkygl0Mbn6VndzJnQNNGEzuex8g5uboJwvIWCk6ZkBzqTlpCEZ3RgDY7TmAqRDztoHcO2fJQI+i8FGgLnbzSGJtmP48dRWmLZYlpWyHbqiJsiRnu4XoqerhrUMcmRXBtte/toPDzK+CWzeeHyOTjJWozxmNLHXGQf49zITornhtla6iTtRzFKIH8xxMxIL71vvhxDYLHoEWK7P4eF9jgO/Vh4RHoGqDvYy/iMlSxzdvF8cRlZ7ZCwkygR4uXoYyH9ai6tP38Ce1mU6kUlbHrZKxeRlHG00CRkH+O6ioyonQ6Kf15axgoZ5drI13FNmI3mWoxMkpwWURfs4lLynsEVNmtmPw7AL/R1ZObW0rLvCFc9+C3ab8jTrWvxkOzVkvniAEOmC/wCmVAjjeYwNd5eSr1Bi8HhC5cSMpop48hJIjyrVvNk7zyu2/QM40sbEf+LDSUqVKhQ4X8jb2Qf0UeBPSfc/ixwlzFmHpACbn5DVlXhV0Irjdu3j9LgEdyci9FqOsAcnBhk1C0boBjAeLh5D+UbQtEY0apqjAFf+YRFGNcY8sUSWgh8zyVshamJ1KDDOaxYEWyLifF+8qUc0rHQuHieREoVaE1Gi2g1idYKX3kYFAdrhhhMuBgf3H17yacP88K5Hvdc9CKblxaYF1uMMRpLSOKxaqRjo+JhtIoGvZzCMOvAXupGhxBCg1DkTQGNZk34KZZbP8eWgVHjlK6jLSVVVoxqp5oaN0L1ZIl4pkTr3n6W1R8ge2k1heoYhUQYhAhK1EBMRjAiyAx6g1D9wyxjjyTou/FCZiwbom7G5HFLTCAkNMZzGTCt9Jazf/mFHRx401vocI6xxN5PjEF6/HoaZT+dbC+/EaeySDzLueJBjG2TPWs2zfIQTeoQc+VmbAkCC2kEa+ytrA3toaSPD89IIRDl34QCjcJBCKYzmAIY1F0M6Q7GaeTp1FIOphaSpZ6aUjczFg6SXb2AJlFgrdXPZVYvH7BfZNRUcX3po2RViD3icnJWC0nvMC0TmwEIx6sC8fvyOrbJOt7tfZRlSUNhZjO+LcFUMpgVKlSo8HryhgSYQoh24Grg7vJtARpMH4sAACAASURBVFwGfLe8yX3AujdibRV+NYwGd3wMr1giM54lN1Fk5OgR/JLCLRXRTGUwwQmDKmkwmqqGRizbZsfIdkpFF1tb5D1NOldEa5/x3CjCGGwcRF8nkfZR/HCOoXQfJb+EsARGuBhtcSw8QkGW6KvbzE+6vo3rueRSgwirwG0HlnBJfxMSQ2jWMmL1XRyoG8S3DYfqRjgWHQ36FnMetprKhQkEFgiFABpGRpjZexgwKLxywCX4Sf46DnoLqLJdhJCnFfWOpIo096UpLnCoPzzO4MYa/EOa8366l3nbB/G1P2Vggy0kGdHFhGli2GmhFLEZnllLlZygZlaB8UWL0eXiQ5gcfxx+hJuTP8MowVyxkbXyW1RHxglVC3bRzN35SxlTdbQ4UCeGmSs3YXP64kDKtDBsOgGococo7PAZMoHY+bmhJ2mtryHs2GznKp7xllPAxTM+JeMxzx5iuXyKH0z+IT/K3oBXHmKaQiDwtUbrwBnI2eKRfRGckRTxh49hhQylGcN8018wfS4OmoVcXroDgCZnGIzPwcS7yNkziC+Nknv/DRCLlMvjmjQ222UdH7E3s6RmD/KcKkoRG2EqOpgVKlSo8HryRpXI/w/wV8CUB1w9MGGMmUqH9AIz3oiFVfjVMAYKeYH2SnjZDK6RDB3ZRtuis1FGneTVUsiME47b02LfWmnGjxawJ+MorZFJiTHgjgzjucHATXpfD/5gARrPIWSF8L0s0uggcJWKIpp7W56Yfo6kFyGXAe1OYlkFpCwFrXilSVQuh8pMcMvTs7EaIvx/y3aSCuepweDkPYTS0+u1LBFIago4tmQ27Xt6OPvpn7P+ootwLBOU1J0oS+2tFP2lpP0O3LKM0dQkNVojDIyureLCpm5eyM3lyMw6znk+6EesG81zGB+rnP8EOFc8RIZ6tteew8Rb02jgcnEIZSxy1BBjgjw1VHEUgKwOY5DkqKaGYbrENsasQDPTLVk4SEb0HJ7yOrAsic9xP/MTGWTu9P97l1xEonOIlc5jZHWSfmsZ8YhDVhbxiJEyNUiKFExZjspYDPptcHod9+C9L2lCVjC6079wBk1WFdEjffTNnsWTjeezSXXhMskC+QL7zPnMlxP8T+i7nC+/D8A4HXjFVprdX9CdeA8hy8G2bTzPRwjDVlHPIZmkVeRpFzvpNysRyOAXUIUKFSpUeN143QNMIcQ1wLAxZpMQ4k1Td59m09PW8IQQfwb8GUBHR8drssYKpzLpThK1o4Ss0/fvGWPwXA9HFNG5FMMlBcUISil0PgshxZHJI8R9C2nZWLbELZSAONl0EZUXWFpgfI0MFIDwSgW8Uh47FKPY34fW4xTqWqgiSd4bA1XuzxQaZWBFah6FUJ598T46cw1ETYi0n2EyMsSzTSOs7W1E5cZR4+MAKA/adIT3bb+IpOeQbTAIJVF+qOy/HWBpj4WbNlBMhkg1NOA5EhtNwsry7sgjHNAr2aHfRK+SeIT4c+9yonj8V+hJAKTr0bypm4MrZnBf3eWwysbXOQC8sM2ht5yD9HMYgilugFHTQYEEUoAUFsYoDuul9MmlXCAe4CjL2KbP5z/9a/kzq4GjmRINEdhkruQivkuNGOYS+d90hloZJky3no8UkiIxbCxC5CkR5cSPXpgcNQwyxgx8IoFYfVUIhcNO73z8UCedpR2siDzBsOmkRyxHGlGerYdB3QKqjhLh04avjiVQWhB2JNqEME2t+K4hcbiPnV0r+KJ1BV+0/g8XWoGxyBGznLXyW/SYJWwursJxIljV85AYLOPiisDpJ9DZNCDgYRl8J2SNwwfGP8nHf34fjfNqOVNLQIUKFSpUeG14I0rkFwHXCSGOEAz1XEaQ0awRQkwFvO3AaT1mjTFfNsasMsasamxsfD3WWwHYMLiB7vHu0z7muQqhPapVPyaTw3MVvtH4SpMazILnYSxJSZdIueNorXASCQ4PHyOfLpFJFdEFH0eCnagDNBqB6xVRvkfUriba9DYGly7hF0cfppAZwy8VUb5NzI5QE4tRK5JcObqatw2tZdl4MztrejloHwFSjEcK7E9m0AQOO9Q1YEeTNCdsDIIaFcMqRLAyobL80PFgpHZ0iPMfe4Sa0VESqTQH5nfROy+OFRlnrnMYgBmim2FmkSHBZuYAcJ4cmj6GDjsceev5dHaO0WGNYwmHefYIi97Zz/Lre4iK8HScNzUgdJizGGQuDk45sykpiThFkmwyV9FrFpMyIa63nmLQtBCSNr4JlDf3m/MomhiHzVmEhSIkNbFkhEgojDGaOWIDa+W3mMmu6TU6FKlmiKXyaSLkp+/PUsez5p3kibHK/7/Ue4Gmbp+eh4UERHmFQX9m0Woi4ljTgfKJSCmIhYPBJCkgpiT2RIYXLriE55asZpkaZK4cp1uv5jl9Ix4RduqLmTBxPmJu5nG1Gt+qYULU84JzJdeNnM91Q+fSTxJjQGK4Sh4B4EE1m/fGDlKa3UYxEjqz1USFChUqVHhNeN0DTGPMXxtj2o0xXcA7gZ8ZY/4Y+DnwtvJm7wV++HqvrcKZKekSBb9wyv2+pzi2ZxzlFsnlsxjlEQ27QSbQ85kYz4KAkBMm5+VQWoHWSEvilxTjA1lGJscgnMcoC6EUTm4YowQRVUXTjPm4hRF04gmi9UWWdsfJpgbxLMOR2mFGommiMZ9QSPBwy7Pc2fkAq1KtAGyo2spoKMdPOvq4YqAJPWgojI2gW+px4nFCEQftWCA1xrIRWuHIEnbJRes4lCRz9mylFA5zbNlM9l+4AIkh6haZ0TeEU7J5Vr2N58xNxJggQYYmk+HPrB2kTYifqKCXESkhEWdZ7BCXOVuQCI7pekZ0IKU0UxwMhlREMChDeUodICxtmu1aLCGnP6xpmigRpVNmeK/9GEvkRoTlTOcih+lih7mUBnGMA3olW9z5tITqCFkWxkCXCILECZoBsPC4WP43MdI8r68nR+CgM2Ii/IO3mkdVJ8YIImQoyEaeKl3HqJlBvVWFABxpE3RYSiwpcGwbKa1X/Juy8gVqX9zOU3omynFYa47xnL6OXhZTJAEYhpjDfn0WIRR7TCD/9Au3lg+NLZs+zqfc1XxDLeJL1kKukke40drPu+x9NIePUnWWJpcMT0tmVahQoUKF14ffJjeKTwAfF0IcIOjJvOcNXs/vNUZritnsCbcNY8Ux8l7+5O0MeEUPr5AjV8hR8BUmn0N5CuNrCtk0xkDMjpMMVYEJjq2NRls+Jc8nW8yhUvV4uVqEVKh0I9WD52HG2sikxxjed5BC9146h2MkL72Ee2b/jJ+37+ahBVv56oyfMOBMcHf7j9mZPEJcRah2w7TmajgaGuCROX3BZLkWRMM2sZiNrJ7EkcOUqqIgRXkq3CCMxpFFLFQQ7Lk+0UKOsZZmhue2oMMSOzzGrN2DzN7cT8eRQyTEBABLxNMsP7KHNU/8gqKReEg26maGTRR7Mkvd3qM86d7Ed93LEAjyJsbDpYsZ0fVYaHytmAohaxnkUnE/VQSWklII4jLC1Mc1QoY2urlEfAOA7+tzEXYbIf/EjhdBrRjiUvshHClIWFEsKVFK8wv9hzyh/5QMxysAvrGZI7eQpxqDhTbw/3oXcdRU8ZCaRZEEvwjfRl/sD8iZKrKFIlIEPaOhsiuQJQVSChKxaHmCX1HyzmzR6CfiDLW0s615HivFEP9iX8ozegYORS6T93GZvJ86eqkWJSJC8VMzi7S2mOvk+EDyKN9p2shddUEWdr3swpWCopRcZR2hWeRRjCIYRBqDrgSYFSpUqPC68oYGmMaYJ40x15T/f8gYc54xZq4x5iZjypMDFd4QUoP9HNu9ffq2LW0m3Ul6Mj0nbWeUYfjIAfoO7GBI5fCVDjTJLQW+YGxsEF0uUNrSwlcehycPkfOyKDTFUhGvpGBsPkLY2HGNngz66IxVIL1xB/GigVAXPwr9HD8kWKzncyDUS8IL9BUfi+xhXXEZ142dy837riZeCvPHB87ifUdnMxoLpqUXZaqoCltEHUHIB+vEeENojDBI3yciCliUEALcaITn/+Bq+lYcnzcTQH5RDXULslTNLHKWDLQcD5hzSaVbmZkd4dLd67nF3slhU83eYpKmR9dTtfMAxjgURXxaysgWkqfVZfSo+WgXaqxAD9QlTg9Lylm8gBorTlmPngTjLJLPYQlFylRRVXR4QsxCWsc/zmkaOWKWUTIRGqxahBAorfG1JksdDkUa6CGYiHfoNheQMi3kjCRvbB5Uc/CRvEke4/32LkY9SSBdC3XJJI5tYyGxhMSRFhhDqeBjW5JkLIpjOxTdEkX3ZT7GluSFVRdjScFMmecSc4TlYgSPMAMmaDUIk0cbw5+xic/XbmGDW8P/ZNu4MjpMWBjmOHn+n+p9fNw8xwVygL/wLmG/Dnoz7/beRfEBw8yjqbILU4UKFSpUeL2oOPn8HqN8D8s+1ZMaYKTnCKoUBGfHMsdwtUuqmCJqR6e30drgFnzymUlKdppsPkukHOTIZBhTMuTGxhDOlA6iwFMllOfjaR8jFalMGrdYQjRtQEVz/NTexaqWXlJ+I6NtxxAFn5kDOXbOGGB/ywRXZQyXHGrmwppOhGfxzMyt7A0PYoC3jV2Kb4r4OkHISeNk4I+2z6Q+HCaTg2jUwS64xEdzOAo8o3CEhRAKY0tsr4gUCiMUltHYhQxePIqwjmfhDLCkro/mhjR7vPOxyzqQxaOG+HiBUl01LXv34S/t4m/sF6g3mWDHxjCXRv4vT/qXMWGa2K8ifM1cx0W6jxvFbiwhcLCpYZBmcYhD5pxTZH6mGKWDZ/VNHNM53mX/mKyMsN00cZ08ebTmRb0GwxoSIo0UQWYxncthjKFJHGWhfJ47vQ/zoJrPXzk+Y8zgG2ope3Utn3A20ipyDJgY61UbtXYVy+wgoxqNhBHp4GzYwsbCAiPKnZgSIST3irN50Wrmn+RjoCRCWiSFd3xxk1kIhzg/Msg5upewZfN2fxcRGQIEu83F7DZrAUOuUCAaCrPea+SHuWbCQjOswrTYQfC6OjzBz5D82O/iAmuAzmBx/KFzhOL8DtJWAacSYFaoUKHC68pvU4m8wuvMoc0byU2kTvuY0QalFG4+x/aR7fjKJ24lAv1KgHQ/qf4Mg4dTePkck+4EvudhWZJQKIwMOfjSI50exw4dD2K1AEtBZqgfbSmsuEYlszzfsJHHrUGOqgkeqjrMnv+fvfcOsiw97/Oe7/tOvKnzhJ6cZzbNJgCLuMhLgGACl6BkKzEJJEBbokVZiXKJdsnFMiVTJSaDNstymRQpSgwiSAAMwBJ5F7vYHGZ2J3dP5+6bT/yC/zh3emY2gKRAoETzPlU9U93n9jnnnnD7d97weye/iFmcZ957H83DBzhy5I38I/OjhCKk7LRpdB2z5QR7zBQAf214D8qzKFnghCQMDYEnmTcRchDS28zYWB2Q2QKlHZ52JK6akV24DHAIVwlLrCVM+rzu8w8xt7Rw84ERkNHi8fxO9CfXWLsyS9cFZLNTCFMw8+6E8kMnUMZw+rEv039sgd98y3fA/TtZdkdwcg+/Zu/h/5bVSOuUIff7v80uvw8OYvrs5BKGm2sYtRPYkUZyTvDh4lv5fft2Pqs/xH2s8NfVGT4uTmJHBpISzd3id/mKcWgEQgiUlFUneVGwzn4+mP8LPmbu5dvU5/hW9f9y0U6z7mJ6hKy4OsuuxsftEZ5yc+wQCZ6q9kkIsW2ePu/NUJNRVYEpJQLHJR3ziN2FE4J/I9/Ej5l38Qlz8ObjqDXkObmTOOdQSt3kJWGuRcKdqBp4lORM0eBNUZtNG/APt05dPyVCoEzJLtPlA+oiwcgeapJldt+xQX86rtwGxowZM2bMN41xBPOvKP2tjCJNSdbW8AdDgr17b36BsxRpwurCRYxnGOgBbiNiudPn8FuBhUdA3U7akyA0ZZHi5QYXSLrFEKlruDTFCwJcEI1WaZkd+KwMNli/+jTBng/SyfYR1mNOeZNMtG/BihLpfD5+7H/hzsWz+OVZ6ncd5YiaZ6WbghFM3/F21EYfdM79yRHenh3BEwrqOcOeRggfpQwejq2upd8ZMLNvgoQc10+pa0HSiLYv/lxneK4kcAZlwaEpfI/nbzlJNj3NwG5isTRlHeHgorsHT+fsSj7L9MNPM/1wVUqQ3R+xV14mcpreeo36pavcy1Xi+Tr71BkuuLuweOyksij6G/ox3hpfZcnOI+UsPopljrHsjvJy564Pl+/mjXKJH/SeY4sI4wQ1NAUxUpasiSYvMcMgzWjVYiyKfWKDARH/gDfzW6KaeuN7ikI7CmpMiojvkec4LiSfMu/lk/YwF90ETQp+Ud9Ok5IJcv6V91ke1bP81nAXH6yvbK/H9AZ4yoN6RENERKqKPu71Mv632iPQ2+DnvbdQp+AuuX7z9aUUpVB8pHwX38YZvleu3OQkNEhT4jDAWIunJFII/vHkOXzh+NbaGkbfLBiPmQ2+zw2pWZ9r2rztDEdYwLKL0paMGTNmzJhvHmOB+VcMZx29zYyVCx2GnYyCJdL+zQLz6tkXKIscU2rWN5foT/YZFAOatkaejv5Q50NklJH2IKj5uK2SSAY4pchNTqhzVApi2EFOVjWMutDk/RQ9MYOQdUT/AAiBG4ZM2GrEobCK85Of4vRCAzXcwgLCFjDcRNsY4QTKlyiVMcj7lEUPX3q0wqrzOQx7WNNAUuKsRfmCuBluR/A8V805F0Flae6cQ1iLdTmSAunAmJxcGFb2zRPLAO2qEZSFLanJACnAxhFLH3qA+IkXmXqpsiv6ePR++ltP0HxpyOTy8+RzU2zdfze7XEpCC4OPdfB+cZ53Fi8ghKDDNB8uf4J3iAv8I/k7TIj2KDV8wzlzcIvYZJ8Y8DPlXcyLIZnweT/nK+9MBN/hX+KU6vKr7h7utyvcIrd42H4nn7Z3o6m6x4UA3/PoJylREPAR73PMiEWaLPH2/Kf4m95LfKu6xJKrc9ZO8Xq5SkyJdY5nmeNCOrctMKMgoFdqPGORjZhp1dyOND6aT7KEz3SgaNuID+jnOB50qqhlaSAOQUlsVvJg/UUO6E2UkjdpannNhN86pFS06nV8q8HBgWwT2j3Yt+um4/Qvw7dzm9nkB0Y+mi+4OzB/vMVJsQr37/66750xY8aMGfNnZyww/4pR5IaNhT66sFijsXmOabfJOwMWLyQcvmuOzcUr9J57FrVnD3o4ZFAfcHTyKBvrKfpa5MiWyKJHb30Lq1N8T+FJRWL2oPMWXGkSRkvIYIgQgnS1gcuWcaWmEBHB5B7s3BliZfEWlinUacLGizybPM3Eap8X7ij5/PEtfrD77moqjE4xNgLt6Fx6FtorxHOH8KU3Mvp2CASDbg8hB2BKhsMSGdYwg5z2Uo/G3pgYjxAfIwUZJc45PCkprWZKDsEGlM7QTIdkXomN5PbQSIfjmLfOneIT/Ir5W5zRu3n/gS7PnjrFL5jTfG98HtWdJly6jLOCYmaSO9QfMisqT8xn3Lv4NXOCRVvno+KLCAHTZPxY+Sfs8g1gCci4UWl1XcDDdhcPqEv8gTnI826GZ90s32mfpaY0gyQlCivz+y+xh8fEDtZNk78rnuFX9d18QF7kPreAENXQLDua2b3qYm6Tj7FTVHWVLXKesnPc660xL4bcK9e29+EhvZcvsY+/X7+w/TOlFE5K8KqPkIu2hfFjQhXxU91qGtCDMqNHyL1iiTN2JweSZWJbQuiDUoSx4H1cIBMGKasHBOdclYIfdTRV1k1VGlysboI2uEYNwpsN/52TTJJxmuv+o7fILWpHpsmGPpMqZsyYMWPGfPMYC8y/AvQ+/Wka970eWW+ytXSFQTtHek2GvZzV1S6HIk3eS8mSkvbKkDIv0FmG0CVFYZkMJglUgBsWlMKQDUoiHC4f4FxOWeZ4/RxdzpLwumqjKfhej1JA9uR+TLqMyb6ElB7RRoqUs9g9LeyeGR7d/SRf3fGHfHjxXez1WvTikrt7R5mw61W3d5bjYonXXSHzJinyhIlI4flDnLYUUtPO2uSLA3rrVfo5m/TpdCxQWS0FsU9OSRQ1iK1PrGKGbGCcxZNgKbm7+Rwtr88VexTvkSX0LsWjx2/HppbdcZ+WsuRuB8sc4fP2CB/9+C8Rm4Kf++CP80/Dx3EI9GSDU9+xODJKP85LztJkiyftG0DAHjEgtClh2aEIpkizlB+q/waL9ijnzO1clae3z5tz8Cv6JI+7nds/myKjTUQNg3UWT6ntaN+Hakt0c81p2eYnyzdQ4PFd8izTsqwmE42E2oKc4n8v38JecYL/2fsMnqhxm+zx3Mhn8uW8kUVKqfhitguF4/54a1sAXpsJ+THupauja4ebjzQvcZdZ4Q7TZSmb4mf0vXxUPMzdchmMRUvFr6g7uc8scdBtVBFmUY2QrDxBK+t2gbg+39053LVOeXlz+bgn4CfsF1FSwMg2KWTAviNXOL85HsgwZsyYMd9sxgLz/+c457D9AfrR30adfh+bVy6zsTBgYsft6MIw7BuoSYw2mNKyeGaDbFBitaHWmqA3WMW0Ja62A7REY0g6GZG12MEmttcmntvB2osH6VOZX4fqaer+Jk5OkZk5sq1fA1t1UzsbIpzGmRWknCLPEw70Woh6kwCYiqaobSjSqwW3TOwjtQmx1ujdILQlZkg+M4ftlGycvUhr7wzBTI3O+TVsppmdjZCex9rKgLgeoJ2jPhERxj5Dm1I0I+JOiZAC4SrrnlB5uHCL/bXKgmmSR0neFLCpmiAdWMF9wTn2eh06boqfKH+YDJ9H3v0An+7t4Hk7g/Sgqt6M+CLfgxgVFLbdLXzS3U6dEgm8XVzBmTZOVsLQOjjHMc6Lg4Qv82rsEfCkuy6OdjPgveoKb3SXsViyXON7HkIIJhp1plzGD5lH+TnxZgo83isvscf1+XvmnXz3cJUPNZarfRJ1psj4HrWAE9OUwLepC9zPItoYkiynVa9tb9fD8YC/yD/RB/nXvSMo4XidXMM4R24MIfBh8RhbtXnujIfMyoJYWISoMWsMV/IO/533JCeyDUBgnePXvdv5gt3LIdfmoBjZtKuq4QdEJZq1hixHthpIKStx6a6NPLq5RlUIcLIaGnkNiSG2S5z1Tl577BkzZsyYMd8kxgLzLznn1wdEvmLP5GukALXGJkPSzUuI4ZcxQUza7zGxC0xpsMZgCNhaGKBLnzLNGWxlTNbmaE7NcHnjArbbIPVGqcvIVjPEhcAOO4i8O6p5rCKHYfgEkT7DsLifPJvHOcuTt4V0xQXuXf8BppPD2PICg10b2Pwl5OPrBJHPmxt3YFWBLR1lPsDoBDUZ4ieQlgl0AqT08MsMKxKcKZg8sItaKybrraOHGbsO7aHl9VhPNc0dIdNTLXpZSaAkBosnPHzh8xvBSZ5z83w/v8unxD08Kk8RyQw/28MhlTAdC4qJVc47D7KqHvCJ5AB7Wx0mRZt5cYnfM7fz/tYlfqh1Fbh60yGfY4ET8mG+YD/EtOjQYxY9ms4tnKUUAaFnMEphcXxCPcAP258jDC1PuQcYUnXGT4iC/8P/DLpMSFWDSVWVJxSlQwpZeVHKylVTSYmfbeGXPf6u/wTrRnLY12jruF8ucswvuKxj/lO5hw/KJ3lL8Pmb9rkmdNU0ZG3VwGMs2mjCIMDhkFLysZln+OjmbZwtG7zOX6XnNWiZASFwgC5viBW+97KPFCHwnONOuQ6isnRacE0esvv48dpTnOxfIZdVhFIgcM7iBAgpcGmJKEqkGAlOIa+FYV9xmUugVBLV7sLMJEhJygSfeuxN3Hv1abjvnX+Ou2rMmDFjxny9jG2K/pLz0mqf56922RoWr7rc5gXrq4ssrq7jFp+AtAMYGpM+urQ4U5LkHkm/wBSWMk8oMk1v4HCAnKhjlkuKdiUALBZrDHkhOLNpWU3XuPxEE22maUW/QzZ4DJdrYi7g9AJ5///kpNdiWjW5MnGW8xN/DMEudM0ndwVWOIR2lEmKCOv0Fq+gTU685zjSc+AMVkRoG1VRqqJElgJVphDX6S9vUvRygpkQXZasrSQQQDClMFzvNLbOEQmfmgywQcgadUAyQ5spN+S0O0/pFFvBbrJH1/A/v8Jbg6e5O36RnX6PBT3Fp/K7ecw8wD0y5p95j/AJc5Bf0rfjiZs9FrvMseIOs4tz3CX/kBet4nk7TeI8vt+8n0/JU8S1+rao+q7gcSbFEBB8rLybZ+0MAIWrbH+aZsCM6Vx/L9YhlURJiVKymq9OJV6RHlPFKifEFqPiVD7kn2fey3iuaPBZMz+a3f3qvpDWVeI1yTJKbciKgqIsqyk9Aj5QW+M/J7v47WwvfxSc5A+DUyzaOs8xx3nd4Ic3bueporm9PjH6Z730+QN3iL6IaLmcB4PzzKgS4Rxcq7EUVVmAMQYpqppXoVRlfyQEKHk9cnntxQDGglLVVxhW3484sC9gsH/2T7uNxowZM2bMXzDjCOZfcqyDtNB005LpevCK5XptjcHWBsolGLlMzwjW0hr7036VFjeWIrckqx1cS5D0LmGLhG53FWsMqcshczhdiQWLZbiV8syFhA0TUPogbB9FH1xBMRyQzcZMqk2mwz6X8yG9i2d4lzjEhl7G9np86fYXeG7fBY5P7eHbxd1sLD5NMRzizzQJJ+awW2lVF6l6lKUiDOs44RBGIl0JeQffgiugs1GZanuzAekgYdA1zO6sRMjQ5FinAInD4okqivjXwnN8q7tMYjIOumXuEx3eHf4Bq3aa/yH7Ub670edttNktN9kdbnJXCLnzOGf2sMxpPOE4LHr8kVUsuOYrjnmfWa64W5lhka/YD/Bv9Tu4R67TGW3fk5IgqiN1gnOCPLqNR+VxrrT7PMRR+naF2+Qm/87cwiXb4qfF771iG1II3Gju943pbDlqerIyJC8LSuMwXsi/6RzhA7VVfn7mGf6vzaOcMUO+3bv4qteUMaBS2gAAIABJREFUFILA9zHWYIxBG4sazRbf56V8b/0qw0LxWXUAFPzeyId+zyBlyURc1jVOByODeSHAwVrh8xvRaQ6VfY73r7IVnuRnBrfwE/kllBoJZCFI8xwhBLUoxAiBU4qpRqMSmGLUaZ5k0GrARgfmpsBZhK+gHkNRgr1BYO4+x0bt1YcJjBkzZsyYbxxjgfmXHOscvbRk7YlnOPSe+16x3GUJJutg0x4JNWycojPL1tJZ/NBguoZhJhC2TUyP3toV8vYqC1eepvHEBOneStiZ1FRpcSymKOkNJe3hFr4tmfSegHSAjWMm9u6rgkylIBCKHXuOElw8R9kqqIVN2jtCskZlXv5i4yrL/kH2tQ5AOIGfDwgaM7hBF2cdJClSVmP/dJGDX4esTei1mZV1TGuG+qkMna2zoWEyDJmZkGTSYZxFOYkejal0zuEJxdB5fMbuY8E2+c3wlwDouQa/UHyQebXMFTfFxslTLPRLzg9a1ESHN8cXWDMTPOGO8RP2PXy7Os93qAv8oHoWo16ZrgWYE1c4yFNcdrfzv/pfJkaT4vE/JZ+gFUbYYBLp+hhR3YIfz/bwe+zgF/xPk6P42fI0t8sNjqsOOIkyCRRgVQQCJhp1Ov1BJbyunWshcUJgnEIISV7kOFF190+LkjNlg5PBAIugxqtHvHEw0WrgKcVau401tkpRjyKHdwR97gj6sLDM905e4p8Mb+WymOJeu8iH6+dJwhn2e+n26q5FMA+ZDX7We4h1QhbUFF2t0E7gS4m2bhTBFCilEEDg+5TDFFePq8gsjKKXAiaaVSf6YLi9z0IqbKuBMxbR6W2f88z2OCePcNSOZ5GPGTNmzDeTscD8r5Eyg8tfgP1vgqD2NV/qnCPPcvTCFZy+F/GyGjh79k9AapiaQOsSkw8pS8Ng2GFgfWraoJs78bMeTkt0mhAKn91zp2jMzSPEVdAaPUgQjRqlKdF5icxD4kKRZCXaOVTdZ23lCsIPac3NYJRjbfUcQ78g9gOyhuAX7/wS7118Pd926XU8YwwPTzxErhKEnEQnKcvLFwl3H8GnxFM9EhugZH3bhkh5AiUsUkpCo7HJOqLmY3OLsgKFJooDSldSGIMuHdey1w6QSJZcnd8xR/l+9Swfy7+HD4f/kZYYcIfu8RH3fXhW8xuD3WjR5gQ9lnREpzjOVqn5af+vA3DvyHZICYd6jRGEl93tZNRpskWPeX5a38Ml1+LviC8z7TmcHyOdRYyE2ym/z+UEUjxWXJ0n3Q5uZZN3qkWsUUjho0w1GtErSpQO8ZRH4PvXLgSEszgVMMxLGtJDuAwENIXmR5sX+Rvrd3NO13kwOMO+cp2X3/7amCrlHl0fOSmEwFOKGzPqX80n6Hs+bw0SPjL8Ck9nE7xNXWaPmkD76U3rFMaAA13m1Cdjfr1zihcbE8zT559HX8TLJWYkLgXXpgSBQlQ2SKMIaGWyWVX0uNlJRJpX6XCuLRulzD2vGhJQlpRa89DCm3jrk18kOzH4mvfRmDFjxoz5i2UsMP8rIx30iWUJq89DczfsvPVrvr4R+gitscMhNk1RzespW2ct5doGDov1J3A1D+1ybL1FnvZJygah1RSloKEzdCERxhDjQ7yH1YtLDAZXaMwexOSGeErRt0MG64vknR5BvyDVd9PLdzHV+CNa03N0u22GnQ7hxBxFCFcmeuzIW8w7n5mkRk2HfOrAE2zVDf/tM++l5lZJdEq3U3U4m6vnmazNE5QJXmkQ0lK4SmMI6VBYvBKUFChbsjOcY6gGLNmtqkEEKBNDikHmgHDgQzaK2B2TXX7WfwgfQ89Zfm7zXRxo7EAI+Ij8Kvf1rjDx2a/wm2/7duoTTRKbM9Ga5tc7h3g3z/BGb8geOfxTz6PBZ794jja7+Yy9lbMjC6C6KEFGCBWgZGXDA3DCH/IfxCz/oLwfgAfVi7xTLV5741jhIYXFCYlwGl/3mZm8bo7vF12EM4jmbqRoAw7fJJRqAqSgLgz/dvpZ/vut2/iEOsiHWXv5LuOcIw4rU3qpM7COQa6phz7uBiH9i70DrMmQIlrhpP8U70peRHgB4mXWQVgLa1sIqprKX+4f4UVd+V0+4F0AIbcjl/IGkSmFRAmqmkshqjpNY3CBj1ASohC7cxbZ61/b8arLHMBXYB3GWGYmJpgxHVZ680yGN89pHzNmzJgx31jGAvMvkDzVhPHXPqTGWK48t8nUrjpJL2f+6NT2MmsMC88+zZGTh1HWgHnt8XadrMPEaHrNlA9mMCBtd2k0m5jS0l1PEYM2rj/A4jDWUBpB5hROOWRUw1/axGhNGDnoZxgnKZOEsyvPUmvMEdhpis1lbGsvatbQ/iqok4LNYZtheZFJfHTcRA8fxZUFtXqLbr9LXqSsrFxiqjnH/ESdOTFNuJHwN1+4GxPPou2QZ8J1bKkRsiTXBhDMtAKGEQSijSw0ntWgLNZKSrOFFQExMOU1ccIgdIa0JQ4FWLAGRxXxCvEphUUIaJs+vvBwo3R5TWimWGZOrDDwZ5AoEI675AZxM2ThxK38bngb+3icmurT8Fs8JQ/zPvcSB9OLUItetZP55XzVvZ+IAafFBv/C+zL75IC86GC8Qzip8JRgNDYbIeB+LrNT5iT4HBa9a1fFyEJeYFREFcutPCK3x/NQufeUfgMR7yE3PsoD19+qxBsCJeCgn/Kvp59nZahx+Sv3d9RvA0CQbVJkKcqrg5CE/vU6xp+cOsuPbN7But/kZC0k6AeUKqj264Z9EhsdXBTCcICUAl9YXldr82D7K4Q1H0Yd8EIIRKcPRiOEoNWoE0DVtLMtMG0lLE8erqKUw+S6I5FzlfB0DicV1lazzeu1mKZ5BnfLGv1oLDDHjBkz5pvJuIv868A6y+cWP8cXFr9AkWkuPrlONvzaM4/LzJB0CzqrCUnv5jo4U5YUWcLFZ55iOEzBvEadHPD46uO08zbaWjxn0UnKl85UUcBhN2d9ocfiuT7LG5LCQKoLNhJod6tWHYYZFAWKBF/lqNkdmOGAgWshw9cjvZ3M7LuTxqn7ECpE9yzZGpjFAZ2FK3i9ks3BO5AixZXnWFlZpigKaq1ZbFHiSsMw73Bqc5LpohJkUgisLdmzNcEHFt5APUtwOkOFDeLaNBOtGr4HeKByjbSOoFlSKIOn+xQUREoghU8eTWGsZbUzoHQAltIWWFc10eBGl7YAJSQeEk8oflnfyjk7wZw7xy3qBaTyCW7oVHZTE9TeeCudqMlnxFEmvVmaCt7hrzBPDztM6fX+bOnWkog+s/jCsk8OcM4hBbR27McJj2YUMj3RqnZTCI65DT7kvcTf8Z7nhGxXK3EOJyqhZaVHqQ0GiVMh8eAKwo46bFAU0Q6cFyAQJFmBFVWX+Y1J/GP+kLuCDrxqat9tp+yN9AiloB54SC+oZo6P2EPCP5VP8MF9Kb7LQfnsmJm+qbO7yAr6pQXf3059fxfP8N+op5khBSGRgQ9iNBay1LgsQwhBoxZXEnrUNS7WtiqBGfjVlxSvMFoXciRulcTkOfWRAf1VK1mOW7xG0/yYMWPGjPkGMY5gfh2UtqQwBZvpJp2oR55qytwQ1V+7a1UXBl1YnHFYc/OyssjRRYHxDGlaUn+NCOagnZOnJRJJUhhCaxgOc7yyWqFzMOwU2F5OwiRdV5LYVTa7EWWs8J2j7LWReYGbCBgO20xO7cbNTLH6wiepTd2BCwSD/hpm+SJJtsXsG9/N7Jth8MJl+u09SFfHUsMWLXylcDjWli/ypotrPLN7io+/ocPl3QlvX8i4e/MwFg+JRRceghiTdpHKAAX4MXErRthV0BZiRVkL8QdD8H1kIybYcrS6ObFQKGfJjUXLkDBPGAqBFI6+znB5SVFarKXqfA+B1OFCgS9qPGdnuJ3LXLaHeUTfjqcs9ThmkKTU45j4mReJGzXeNj1Hl4C/594La/Czra8iixWMkvzpsctX8gPFewD4mPwtVNSEfAufEjeqma1qHT2MsdVc7m0cTno4p3FOUGpD4HkgFFYF1616sBgvqkQyDm0MkZBMh4J4ZGN0DSHEqwquKoIpCJNVcgOBL4kihV9roI3F90b7tbHF/cEQa2J6aKyUWOkjnAQsIMm7CUUYUlcSZ6qNeb6H12rg+sOq61spcCCNgdDH5dcjqAKwo6YfcFW6PbjhvroxguwcqFE1rBRYJfFGI02f8+7nCxuKH/vzna4xY8aMGfN1Mo5gfh0458h0Rq/o8fjyExhtWbvUY+l85zV9Bo22lIWh386QL+tALpKEMstY6i5xJt96zRT5mWcX6F00LJ/v0880MZqZSBLKapvWWJzR+OkWiY0QIqSwFlNq3MASSEGeDjFBhBWQpn20ceRlgd+4hbCmKMyQrFwh76+ih12gQPmQbd2Dc3NoThC4F0l6O4mDCTb2Cua3tpjq9OlObXGiqMYbxoUC57CjWkLhNE6E+EmOVZUJtxEGRElcOrxU45RExz5FM6IZQBhuoIwj1I7QBSgn0MZSEiLKhFxLfBRWNUgLjRUCW1pCXyFkNTdbOtgg5l/5n+Pv+7/MW6I/ZNfFdU7/8bNM/s6nmX36LPWXLiMXlpGrm3xkZomn3I7tY77lQnAWpESOzv2fh//Re4wfEV/FeRGI6pjcePaFEPieuqnWEUC4kcAUHkmeVz6VUuCkhxX+9sSgyk/S49p4RSkV+BFNN8Dn5icZ8ZrpfTfqFneUKA5M+MyKPq1QYm7crShCHNuD5xLwAgQeTvhYFPLyUrUmZ1CBR2ocaV6SD7KqflRK7KG9EPgEcYSnJDLLIQqpByETgxSSDAlIpXC+h5aKrX52s8CUNwtMKdX19LxSOOvopiX3Bl0eTL7CazT7jxkzZsyYbxDjCObXgXWWzGQUpiCxCaa0DLs5Sa9g16GJVy3TK7NqJGNmLBM7rneIW2PYuHoFqzVZmbJU9DmYrLC0/BVev/v1ALTbF3j+6hZFquinQ9qrKaIWQjJA+B5mFLVx1hH2XkKsvkg96HKlazHKgrU4keIVASLXaH8aYzTaWJ6/NCBNHMr/FtIErHiUfCiYaA4Rh+YpOz4KgxKX8MtzZN77EKIG2adYKVY4vnSefgP+2fdP8NLOIR994jjHFw4SZD1qeoPO3BxU07pRtqT0fZzJaVhHX+S0ZIjvJJ69oe3bl8zFMb3hgKweMpVtEtcnsBlIKbHO0fdnCTyBxxQmzxACPAe+8ok9SarAWEuPJp9Y28e9Uz2ceRfSi5naOossNW7fLuKXruDW29gTh7B3nsJ3gr/VWOC4P+SoN8QzBau2moUtcTjnbhZq1lbiWb3SixTghGyjyxS8KppYRDNYefNrhRBkeYHvKcLg2jKLEx5FNIMu24QirxpahMAJnxtDkW7UNIMAqXxMNI0VJYEeVtHO7e28+vU8kqpoJzAypBFDo1ZjtYRCWwa5ZrYRVOWfno+wFpRHVp9HTJ8kO/8wNWNpQDVLXEpKINAG06wzcIppUUligUB4iok4xkkFUUic5xBOQl5CoPADHzM3g1lrE3f6lMjrH1jX6jxNUenKa1FfIcCrIsHOQcOu8KaZx1gv3/Dqb3rMmDFjxnxDGAvMrwPrLLnO2VnfSbKRobVBaYkfqO2Zyi+nzA3N2aiau2yvi4O036O/vk7YaMCGJc8Ng8EK55Xh9I7ThCrkzJn/zMWVveyMDmJ6gqJmoAZyOAQ/RJdVPZ7Vhuz8JYJhFyc0xjm0AxeEuLKHXeuiCosNdtMevI72oMSYOs7VgBwI8HgdbgjWlSQXz2Hz3RSTfRr+sxiGRP4fE0U56JzH9rX5vod8NvYe5HAacudzCq905J5lX3uL3QsLPHHPHJFIEUKTxT4UGuE0trSIekHLj2G6Serl1KkihEIKpJDMeE1Wggzb8JFRDZH0kUowTDM83yMOQubVDNqtspUlTHkNaqLOqc8/QX9nk24gmF5b4D0bXyI8ppBFSTHyGC9/8EGQErt/N+rRZ1GPPI29/Ti+UjxYX4G8QCxsUE40q0iskkhttiOYwpQ4IVEmQ5qcUk2/5vWijaHWuPZQMRJEN1wmVY2qJS/stsAU1mKFRxnNYYdDhIFaFCG8GOsKwnSZtL4XJ8CJ62MUnbOV6brwX3EdymuG5VClnkcpZlwlcruJpvQdIojBj/GMJdcWKauHF1EarOejKLFBDVQI0kcZiRf66O4Q4VV1rcppvECids8SxyG5tkRyJIKlRHoK0c9xoYKsgGYDuj1EKpg+tJekVSdfXCeOAkpjrn9gjWoug3NnKHbsRdTj7cOZaUMr8Il9xQtpk4Z/AJ3Aba95ZsaMGTNmzF804xT514FxhtKWTIVTGGNZNleJan71N/5lvs7d9ZTVi116mxnKk6N+CIfRJecefZjll85S5hlGG4r+GsXQUuR98nLAI0uPcKF7gbVhF5NbttI2YsKg7WicY5aC71EWGnvuIezWFeygTzdvUxZDtBNo69Cumi9tshSjHLYIMCZAqmVcuICx58k7P48Vv0khfxdff5JArGMGCbiSgEsMi/so1JvJDXTaW2ymm1zYU/CFB+7k/JE5nmme4bt+/ynmVq+ANEhPUfoex196mju/+EXuefjzSFEgpUZgCSzU/ZxAavB8rC+J6fC24DHmZAeBYDqqEXgee6KdTNamqTUb1MKAOFBEnuJf2jfxO/oIDVnDswo8iSfB1GIavZzdV7aYXGtT7J5l4taSvHtDqnXUqYzvIwYJ+p33VT8bITbauHoN2RtUY5OEqG6azQ7kJX7RxS+6OAe98tVrG68hBUS1xmjFAiu8my4UcU0g3hBilLbAyet1mhJHEEQMZm5H+y2sDAmyTbxiAKIyWHfWIpVC+QFOvrIeWEqx7Q9Kfwhbve1l1ybmCKlwu++CoIk/mtBYk5Yizasuej/AyoC8eYBrsU8FNOSAstsnOLIPfewA0awmcgmNWkg9DrGu8pySSjG9dzf4Pr7uE5UbEIXVsY8jKEq8IKA5M12lwF/eBV6pXYhCZJHj26rxKk9ztKuOoVICq2b49/33IaPxuMgxY8aM+WYyjmB+HTjnqPk1lFQYbdjS67joEAzlK2r02itDlturkHnsmJvGaIuzkCcJZZ7hnMNaw4sLm6jhEINhNe1T1usM9ZDL3cv08z42TRjiE7dCytJgegWUJUJ50F0ku7KBlXdjbEka1VgatkkFGOtwGPKkQ+YM4eSPIe0QISy5O0vh+wi5gvID8BxOCLR/lK47hlcDz1tE6YsYdwLhNnhq5zko+5gsYV9vksPDWTo6I1LTXDjWoF8L8Lw2q0ePMVCCE2dfAsB4iiOXz3B+/ihWgVf3mPdnMCU4rzLh+e7wswA8Z/dSGdlI1DWvRCWJds1hR7OyE6doUDAvBtRtjLQd6l7EvmcvEy+vA/DUg/dwqTzK6WCJvNckOz3NbKuFm7sebXQ7prEH9+D27775HAcBtOpVCrbbxfoeqjS4eg36fWwzoJ9m1HyDp0LSQlMLq9sqLyvxGPrVc5xwBnGD4DNC4azdTu9e84G8aftCof06oxdU4lbKbeFoZYgyCVZFOCGRsoqee0HEzMw0fqcH9mY3gu0536aoouj+9Y8BIUb/SA/ZmAOXUE+3iERBvWyjCx83vx+UwjqF8yNAYHWJr0u0H5NLyd5je6lrS5b4TDZiolZEHsWcz8rttL5wFjyB8Wvo2iyyt4UN/crLsjesRKQU+EoS1UNSIW98E4DDeT5e3sXXgN8CTxHvnsO1B0S+Ymee8sH0OXaG3/LKG3jMmDFjxnzDGEcw/wtxzrGarG43ZRht0U6jrQZeGclKegUX1i+zMliumntGEUyrNboscdYwtXsPWZGT5EN8GZCUJWUxwFjDoOiRmwKdZ5hRaj0vNLZdCUyUR9MlmCLFpAkGx0baobAFhdN4zkebnFpzlsbE60edxA1qtXWccyjpEEVapYFx+OXbcO4YCxPP0ak/x0s7f5+i3KQ7+e/43JFf4+ldF1mN2qzMZnzX43UOfflRakPNt186zer+O2lPNSlEhhGKxjDF05o/ecfb6U41mUwsKB9fCWToo0bDWnBQYvhyeZxP9u/iqm5SNxvEMuDE5H7qtXj7eCqp8DxFRMmP+4/zerWKwNGIQ6bjmNogRd9xgnz/TlRm+SXuYcfG00z+wXl2PfQoLo4qI+9r1GuYB94C4ctrKB1ufifUIoQ1uDCAegSBj/RhaBUISSkClFJ4+RZJXtXC5rpKLQNUlgGCor5ze80bQ0M/uy7+ts3GhRilrgEhcPJaF7ismnpuqN00XohVwSjKWQlM5fk0JubAmapB6FWuX2VyVNobjTgSkFf7UUUwFXk4XdkHBTUk1cQiHU2DLhA+OCTGi6gfOkW91kJsbeKaLfBCCH0CJZmIFTaeojkxSaMWsGPPDrzAr643ndLqn4O5SZz0SecO44se9uQh7N5d21ZEbtQcplp1zMwUOFNZMwmBEA6nPEgLkFW3ucPh75jFk4JW5I8E+7jDZ8yYMWO+2YwjmP+F5Cbncu8y1lqcMRhjcEjydICflTfVV1Y4ylQzVAmDYkBEjLPuht8HL5TooiTJE2rRNIWzSFOircZZTQ2PnikZGT+iB11aaRebG6QniLJ1hs9ukNUWGeQ9MlugncXDxxcxaXcZ50W0wkV04z8R2iNENUk7yxFWEKgAQo+8TPFUm8zbIql/hmSjyyIpvQNzfHnXxe139P4X9xM5wY6VLTQ+qR8QCgG6wDcprg63fPnzrMzO8NkHjiFExPk7j3EwVMQ6Qfk+kZup0qYIcm1QCF4oj+Ks5a3xMxxLvsDzrR8hDG5O9dYeeoSo2+fFt70e/4lLTC8ssnjnLRyajJhKBO473gnW4v/WH3HgzBr/+NYvkMhpmvU22a23Q+Nrj+AERtY4AW7nDGJtk0goknqMmJvGuRL14gqFCqkrKGRAIAWBryivpYyv6VerCfJNclHHede3q15Wh1uJS8BBkG9QhLOVebkQWGuQEhQaq6p0sVUBVoU4W2KljxMCISWeFyCuCS7hVZHCGwzQr/lVutTAZK3K0vcH0KxtG58P/R1IZ6t0OYLIgzycRvswEVqc9EkaBxCtOaSQGAHJoTuoXXmEWAo8CZQJxA3m5vdRj9rk4Q48T2HLgkAYjD8JUuA8n2J6P+6OkyhZYqSsakql4HInZZ+vUHPTWCGoDa6gyiH9qVsqz07Ph9jHOVU9tBmQgYenJKEnv0bH/JgxY8aM+UYyFpivgjUWqb52cNc6SzfvUm716fQGGOODsGxdPovKPZw7DLDdbZzrSigWpiA3GZFXwzlXjXMscpTnUziHQeCQlLbylvZc5bdJlpEtDECUuFhX02v6a1W6VjsawxcYqqKqsRz9L32PltdgkEhwChU2sbWQBReRyXVOilUyswMX1GC4hTM+Yb2J1AM+c+RX8YTPe84fYatvWZpN+fKui3zL1ePMLIQEWtBo7WX/808xsbXFY+94X9W5i+bomSfYsbTI0oFJTChoTmzyromX+I+9/QjAWcPOaILJZoNuf0A/SQm1g1rGBy4/ydJwlrljCfNqg43gdhLnEWNv7n4Wgp4L+H/K27jF8/jb2VkOPf4U7NuFf3UV/be/E6REv+fN/PvOLvbRpR3uZPDeQ8zPzf7ZhIcxVaRTSggDpoKQLAhwYUi62aOmPDw/RNmcfqmY8SRKyJHVz8hAnCo1npgQ6StuTIIL6aF1jrWVPZAcNTVZXWKTAmZN1WENZMMuoRcz0WzhvEpgpvX9+EEX1T6LvSH13prdg/J8SmKsiqn3zqP0AONX9Z8CcMO0em/7dsBKm6zvsIMEMTONEFBbW8JOS5isoqX7wiHr8R5WVB2hHEYFdOfurTaoFE6XFDsPkvkDZvpPM5dfplc4ZDhL6+13IpYeRfcuE5mEofEqCyLhUUsWSZRH1thLnu9G2pTSOHwHVgp8pRCH9uDtnIZeiXCGPJpDmgJqAW5oqhS/kOCqGKYfeASBh4fbnm1eFq8yumjMmDFjxnzDGKfIsy5c+Oz2t4N2xuVnNv/UX9NOY5xhLp7FFhqbpohOB2M1RpeUuYViyMLTi6xf6ZOVKf4klM0EGBlJW0extsrw/DlMWWIs2NY0piHxhEBb8LCUtkQXOVgBwuFUin1+gaQ7QFld1dwVPXqrG+T9Ap0XlLZEeB52FCXtr6wQ1Kb57LE+jf6Q6TXH+srzDNIuSIcbdiizNoaYrXrOlVabyPhIFXJ0+jB79C7u7B3knvYemqaFzHKkNCwcvoWn7nkdVlh8WXUsr+3dA8D85Q6dnRO0diY0ZYYvNbU0wX7+Ilcv5URBQC2KOOU9y+HPfJHJpxZJnw6YOt9Df0rz2PAEy9Fb+MnOcf7h1qntY28cfPW+d/JTtz7IP//jj1GbiWifPkk2P4NQEpHl+B/7D6ANW40pvlQ7RJeI9zQ+yengkVcVl9VxevlJthCN0tGBj/QU0veRUhDbHq5VxxkqD0gvxvN8Au96g1DVKS0YpCUlkkYUIUcNRKUxeIFHwwM9imJWzdwKL8twcYQoctyo7tA5iwsaRLUmNqim/zgVoP0mbrmNK9x2XabnB9vNOsZvVDZCTnMjwoGLYvAEdvcsLvQJfB9pLf7SOrbWwPV621FPL6yj/JAqOV7cMEEInKrmf8sgwO7ahZybRSmPydYkp+58M2LHMajPIbwYVIAzFuWrSjwLifN8nOdRhpMIa1gb5vRKixWSwBOo/fN4UYQDtNfA+E2kLRDH92L9AOFJxFQTgG5aAoL981MIY0e1u2DMy6YajBkzZsyYbyhjgZkPoLu43XiQ9kv0tbq5MoNi+Kq/ZqxBConyPWxRMLlWoJKMIk+xRrN6qUP24ue5/IVPkPYLlvrLOOVoho2qAUiA05r0mecou12G3SFGWxCgqdKnOtUoYyhMgTMlGEHkBF4Gg60etv88QdnB9jtkxsNo6AuJXl1l5sJ5lDGU2qKzLZy1OJ3xnpc+ip5O/WWuAAAgAElEQVR9C1EcgJQU5RAlIWxOENVn0E7zqdkpkqDkLZvHCWuT5EXK/rMl9z7eYubcRQIniZoBUhn8WJA0Z7BYzqkWWht6MxN8+t0n2NzVxKsHzLkuDw9OMR0rJupNrtR3cBGf/4+9Nw+W7DzP+37fdpY+vd/9zr7PABjsIECAJEiQ4G5TFEWJoShL0eK4VJKlyE5JpcROHJdSUhzJUdlKHNoqh2Eki7QoixRl0RRBQiApEAuHA2IZADOD2e6dO3dfejvr9+WPc2fDDEAqIsE/0L+qW9PTt7vP6XO6bz/9fu/7PDPdc2itKGzAyP4O8S7Lb7/zx/hf7voYHT9kfTDCbRu/y/9sPkGG5OFBm3+yup9feGknC48ex3kGXdHcHy0yOLCD+uk5vBdPk3/gAYob9oKSjKiMf9M6ylvEC8wX0yyLXdecS+dgqZeyPnhZNKctow6BMjfb91C+oTU9ifICikqtTKm5uFTd3I7vBxSFu9SDq6RAK0GBwL+iv7ObFIzXKjSKZWQRX7peynKQCWMQvT5XvkWV0qThCKl/RX691BSVBt1wD1Zdndhz6bWqAkRRlE80zxFzi6AldmIUaXNM1kEoSX3LBLooQCt04KOq1c3n4UAH2OYOBrpFXNsB8orFj4sC03gEnkbWJ0AHCAGBZ6A6Do0tYPzNLz0WrctBJasMzvigNFYFrHYHSOtwQTm0FHmaXWMRUoLuziKzHpmpIYsYKS3WD0A4ZKO2GUdaemyaSgDWEnoKh8Bd8+1hyJAhQ4Z8P3nNBaYQYpsQ4itCiGNCiGeFEL+0eX1bCPGXQojjm/+2vtNjfU+wGRQJF3Mb1xf7pdADOPElOP6l696tcAXOUqbYpTlFkuIGPdK4R5HnZElOt5OQJjHWlVXIQZYyc2qGoshBlPdLlhbRytA5t8Ly0Zdw/QLZq2F7NbJ+gc569DrnKYoUCkeEom2aqAzSIsGRouM11rMR1nKfhSSje/4cY6deYuz0DCumQz9dAuBbW85zcvRhovwsSXcFbTwmzr3IgaNHqRaOWFU4KZucW38Xd5z8rwmLkKwoSEUpXPL+Onp2jqyzQKWq2SZf5O8u/SF+vMSzss6ng8NI2cejy9trz3Pi7inObg8xKmOrWaZt54mRtO6Y4Ff2/CnvLf6Y8/FZFv09nNx3Iw+MP8V4tMHp6Z18/AM/T7H9Tv6DfR9K1bjdHeF3NvbwVNrg1uwC75j7Fu/2LzB/92HyRpXH8lH+1zf/FEsfeDducgz75juwCP68P86Mi7jNPIoThkG475pzuT7IUJsV46tfG1fGEzqoRrS2TmN8D2l8BtLHr7SQ07dgpYeSEiPB05K8sAgESgiMLG1z5BX2RwDtaojx/Evip8wqF6U/qPRRRYbd3CmtfZTx6DUOwpXWQ0LTa+1FdtcRccz1KCubDpOtY3rLePFK2SWqdLnULBySAlWNCNbPIZTm8PY2KorKY5D1yv2XCqcNedDYtFi6+PgKihxhDLccOsiOycnLAvTi5LdzSGk2WyQcSmsKFeCEwGpTTqVLQ5rl4BlsvUZRCYkCTT0w5IWj4vpkaUruN/HiZYQrKEwFq0KcLPtKlRQIKcooSlumOeHKKv6QIUOGDHnt+EH0YObAP3LOHRFC1IBvCiH+Evgp4CHn3G8KIX4N+DXgV7/ve1NkkKdgc1C6zAm/OHfRW4Cgef272YLkJY/ValoO6uQWFYTkWYKJNP2NhLXEMejlxGmPpIjpZBlFr0sW9xEVgc1zLBYyRTEoKNQanlchTWo45WMzS5QOGFcR59IYCkd/ZRnPVGkO1ugrh+h3IbcUnk/Xamy2yviJM8xOT5AuLiCCAT0fZm/weGLLDJV0ASP346U57UFO3yZE2YCltUUeG9nP4VNn+OxLn8KzOUfe/TGsbzGqxpa8ihQ5F8ZHGLiYbTMdticzzD/b5Pg9dY6qrXzQfo2fanyGb/QOcsifI6VCYAecGkxwU3WR/fLbnBe3E1PhzKl7udA6ywdbn2eGfTyW3sFfuO3cpte5j68zVR/hqbTBP0t/nN/z/wu/bf4PfrbZIdOjuHEQBz/Am5zj/IKPc45169EfbdFvWxqU/XZn85D/q7OD+4NlbhUjJC4g8K6XtOPwjSTOXiZCrqhguq1TuOkJ9EXBqRVds512PmBD1IiLC+QriySDAWHUZLWf0a545NaWs81OoKQu9zXONgNnFFL7mO46hFU8Y0izjAJwUuK0ItcNAISUVGqvYOKuNE5p5OoyxdSWa35thcIpH+EyRB7jfIXoW6z2EcVmb+ZkE7QikwGZH+AHPkJKstmXMEKXVlGydEdIoglscXlYSeDIKxGyWkW1JqE+Cd/895D0rhKYKO+SzafRikJXsLUaGaU1VLcM8EHXGzBSZzHO2bb5ZpxqBuS1iMWiRu7VsTpE2JykthWR5OiL8Zti0y/UM2WilVKl8L/ueR8yZMiQId8vXnOB6ZybA+Y2L3eEEMeALcAHgLdu3uwTwMO8FgIz7ZWjp2kXTIC15YfUsfNreAsd9mx/BYHpClwO5+cH1JMMUQh0s47rxhhfIxV0uwVZ1qfXWyNOe4jMYgtLbnOEgHh9hUG/T6+TUdiCwllYmUGYdQgi4tQyWK5ikrNklQp0PbAFJ3tPsgtDlFnyQtCnRub5OAuDQpEEAedGA1ZEFZFDM4dHm2u886U72detc6a+yFufnaHZE3z51l10I48bLizw/uTj2BNltdIKgRQFTkomTz3P9PFnyKTgazfsYudKj73nLlDf3eOfv/sn+ZK5g1QZ3pt/FS0KJswSx9xubhEny4noYIJHem/hryrb+W3vX5EXkjOnJsnmW5y2UwzO9dhTf4IX3/kgIzIhLlLU3CJ3f/ULfPqtbyRa7TI3ch/NuW+yfhTSd74NfA8pBGazz/St4gzvCRZo6+qlc3SXfYQno09TsUucNm/k7GCU6c3fXRyqzq1DS4lR8rKl0EWsw/mXBWVpJQ4yHyCExOoApTKyApR0DLqlT6kftVAC6qEu4yxzMHhIKYmzgkFaMFr1EEkH6YU4egjA9wyeqTO3tFCm8mh11fCOENcuOKj5OZzv4wguVeGvQWgK6aM3nQ6cH0CvX1ocpRnOk4BASOjnmu7YYcLbbiU9cQLVaGLPg/IFoVEIoN/cVw4+XUSqMs3o4mCc1OVPNMpFE/Zymb2sYAolUUoxqG5D5z16Bx8AYLFfcMATiPCysXygy8taSoRfY9m7mUhHFCos/T+DKt32QRpyftONqPTNtP2EfHkNb2qcmtGMTExe/9gMGTJkyJDvCz/QHkwhxE7gNuAxYGJTfF4UoeOvcJ+/L4R4Ugjx5OLi4v/vbefLyxQbG5BsQLwBa2cBsEXZH9nrD+j0Y8ivP31auAKXlRPnFBZXlMubutksP+i6i6S9LpCxdOwbMHsKt7ACuaWX9PnWzON0l87Ti2P6OiAJO2hpKZJZWLiAyzXNtIVMFf2lHvHxVWxvguWkxh+1vs7Xt5zGyc3l+fnTdNKUwgliW+eJ/XsoGm1qjW0Eoso9J2b44ccN+5Zvpuh9gL2r+1nZfTvP7G/zn++YxTpBYyOlm0hWI/gP90vWP+KYeOYJpk4co1MfA+Dkzh0MlKBqBux4YImJO9b5QvAGUmX4d/Jf8CvRn/GH+QPs8+d5Vt7ImmjSEVWei3fxotjCb5nfYyEfYzUbxWtY3JlVBufKIZJP7H0Hv5vfduWJxoU+lRMvIT//KIv5jbiT84huD/3H/wV56jRQDsU4V/Y8ZtLwH3tT/NuN7TgH0mWMFicQwiC8BqF/OQ1mqZfSS3Oy3DFS9ctl7CudpYqiHIy5wh6psngUl2cE/QsIrXGinPoWShKGEcYPCMMq0iZIKdBS4GuFryVOefTru1jqpVQDTT30oLUDEdTJVXT5aa9uEArI6g2c97KYx5cPJ6UpIu5jo1pZaZUaiquHeS4dS+XhcgsrPYTvg1EMBgnd9T5OqNJb3eWQFJhmA3/bNqpvehPBwQPYHJACT1FWJOXVfzac2hSYV9ogeVXwosui15X56AKLlOUxK3SF1dE7sbr0Nw19j73jNW7b3mK8HuAbyb6Jy8dGCuj7YzihKXQIztGXHhs5CLVZwaTsX/a3TaCbVbQAT6uhXdGQIUOGvMb8wGyKhBBV4DPALzvnNr7bDwDn3MeBjwPceeedrxLM98rYOKb7yCOoKKI2tgCVkc0+LVf6EjpBRTs2MkueJWjnsFnG2lPfZGnPCA2/QZ4VYAWucNjEIZwjyx1KFNikzyCfI+smSAGzSycpYk0uHUjHwvlTiGJAuF5BZI5MCnJVEKiMqDJJMm5wuUNC+Rguwy45NtKDVLJRPnRugZ3LfQQONXeWXUcfg6OP8Pitt7BSbSLdQdY3voJXey+yOc3q1GfYPh9xJriBXPRoLp7muZFlPn3HCmPdKrfvWeTA1kVmgp3slqe5SRZ8tnc/O5Jlev4oG5Ntvvz2BxE255bwOd5RP8ZD6W0cObmPb3k/R2PngMSVht6fLB7ko/rLnE19Pix+i5+LnsCJcxy2cxyN70bmET1GaN+qsPss/0rdzBf1Tg66Rd6fPw0epaaaHqd43/2Q5dgb96JOnmb9BZ/KHT7JmZyx/peZcX8PLSWJK5ehjxSjfDLeCsD7KvP8au/v8QX9GOtmH5k3RWtzldRZCI0kTi2+Bl9LIt+nn11RAZxdwHNrqG6AyA0zwX7yTJJ3FvCDKknUhlghtUYLqLXHCVZ6mHCUvLeEMdElUSOcI1Yhsa5TC3IqnmLXaASqhrUhzM9f3m6aIaIA12xCvoFLNl/iolwmvxJhLbbWAGOwQYjuLqDOrVM02thWG+scSW4JjSIJRtGnTkBUKSfilSB3Eu3V6PhbqLBC2J2hZxRbp8tYRWEMettuRFCHkYNlP2ngEecF/pXT8lLh5GV7JgD2PABnHy1bT67Y/zBbY12UVWYnNEnlcmXRCUloysf1tcRTEnXFc9ZSUDhBFrTITR3XXeKF2iSiVWFb8TXyokAIwe7xKqZVQwY+viz7YO2rZXgOGTJkyJDvOT8QgSmEMJTi8g+cc3+yefW8EGLKOTcnhJgCFr5f209OnCCbn0cf3F9WKIMGrJ7BNvdfStgx80+higEuT+G5P8WO3sPa7Cke9p6m5tWYXt4HucClDptYtJCsDlIi67CnWwgnaNfWkDYj7WwgRRMpU6SR5GmC6yxTdAcIVaefpFiRUBhJnvdxZ86Tt3OKqI5X05iwzvhczu/c8lu8/7lfYmzm7xBUvkBcF6ReSHzDYXacPslNx05w5PBPkUT72GmeZ3TXr/LQ4m9R3bOTCddhRc7yNeP4Z08eQ2ybYOJggzf0M748vcCLszdxq5fRcmWms9A7yUctnekpCtcjtxscClZYSKb53MYI4sIG7z/yNc7TorFzgBOSP+g9yDSKfyF+lOfFfo7nNfrZKOcqEZ/JD/MbG3/GTtshnIKMCmyv8ZY0Zjyb4d7uU1jpsM67nGZjTPkTBmz3HyKPEpqj5xH7YEUfQLkY3xi6nUWsrHCPt8zh6GliJ/kHy4cBwTnvAIW6Ooe6cA4lJb6GtLBo6ah0z6FsA5xCuAJ8jXURWXM72vZJ84yJqMIgXiceuZWBaCMWZiGM0EXOocixsnUrrrOCW5pholq/tD0pwZgqC52E0arHzVub6E3hZJQG8jK2UXkQ+IixGoU0YDQivpxydM2XMFvgKhWSw7ch4gHi6JM4YzCzZ7GtNt0kZ62fMt0MCc/OIKoaF1Zg91ac1GXl0AuJ+wmhA1upk0aO2sTI5X0PK7ixA1CbgDSl1Qg5mV4tMG1UxfZj1JUCMxqF6dsg2lyIcOUSf2qqCFkaoLuXLfk7oS5VaUerPq3K1X2TQkCxuejSVxEyK9gx0eJCorAbin5aVkdDr/yzJgMfm6QIyaX0qyFDhgwZ8trwmgtMUX5K/j5wzDn3O1f86nPATwK/ufnvZ79f++DiGFmJIBuUn1p+DdZnKBZPAW1sMiBxBTrv4fIBbMxx1j3D+dUztG/YV5qspxtQKDi/hghCvEYdc2oCaw0uWMF3A/rdDcJ+B1E1yHoDcod0GXncQ0tIls6SterkhSSOY4qVk0g0IvDJF+foZn0u6Ajx1CJnJhwfeP6DvDD6JIvpUXI5z11ro/QDzfrW7cyNj6I743SzL1DtLDM2Pst0p01U/QvMi/dxsnUH49GneJfJ+NQND3JfMcPPHN/C1tZX+PnxKrsnBvzbxgY/9NKbuVlW2OM9RX4zROkst/3J48xuHeUdb/o2AL/R+wnGo5jWdIuX9m3j8Y07GRkr0APJe7JZhDPcP7bGz5snSboJ/9Ldxbr0+KvaTeweHAWtISvPxc1eh5u9DrNdgaTAWXvJoPwi8tkTzHw9R3z4jXQqGRtmLxaDcgO2um9yd/VxHuq+kxvzJ2mlZ5j138hDwR8wKrqcqX7smqVl5xxaCZQo+y697iyyNobuLAEJXrxGFjQptkzSax8iWvo2kYatzTZPzg4w1e2IuA9SUoyNoI89TzixlcMf+iCz3/w6cxeOY5dXsHWJrI0jEIRhhYFzBEZdEpcAvu+Tq4iwiMlFKdqEKXsvbaWG60kG3TWU1tf2YFpL0RrFBSEuCMn2HsBJhVopXQOUFDRCj35aEFVqwBpWe4hqRF4dwXo1BtURiAcIlyNbTTrrbfxG7dImhNZcXKZ31uIHAXlxtVhLD95EZ7LL6MvDCRpbL18WlDnsysMfzILYVQrKKxECeUVLwFWCFVCU3pgAGYa6Z3jbDVP8p6eXKVD4IiN13mWDe8/g+jGyPFRDhgwZMuQ15AdRwbwP+AngaSHE0c3rfp1SWH5aCPEzwFngw9+vHbBpilAKlyU4C3OzkkbYRG4sIPIKbuYIxcgqG2qC5c6AdiXh2aUnYGOBhryNC8urxCtdamMBq88NkCZAFCnS5RSySxE9xWR1jPVTHbQ1GCXJhQAsEkmS9AlICKTPUudWEIt0gmcI05gCMM0xch2Q5TlP++e5dR0OpO9A+zfzpu4R/mos47al+0mLL1Drx9BN6dU9do6eY7k/wllvnsejCV4MDLet1ZmY+XNaqy8wXnua6Rvm+OTIh3h/7c85n02zzc5x08yH2dWRtMxJanlIGlaJ7Am0zTji7Sa6fSvzI1N8o2u5p/oMW+QKcb3CscNVEBDrAVXbZmpQ0NMFWiq0ktiFFf4hb+ZwpcfkyrO8NZgvPRM975LAvIh2KeQxnSynElzOHLcWsjBE7N9FHO4g3ZwGHkm+xZb44Uu3i13EqD0OwPakNM5fNHdc27dImYxYURLtSzq9BJsplFdBu5zOQBJ3HWZfA7vnJjrtm7Abc0z0XsREhxBRwoYZQ+g5hJDk0ztQzzxLZc9upNYEE1twFR+ZD8CFkHboJQmjtZCVvsDTV4swqRT9YIJ27zlk0iWVDayDXixwY7egF57FFhlKm2sqmMIWOO9yX2m+dQdi0L90nXMOX0viNCerjpFHAhlJnNBYUykFnR9hswyEJNE1srBOODZ2eSPGILSm6HQQSuEHPta9TK1pTRGEqFfrcqm0Qfv0qjtJWSxF4MsEsxUakfdg9Qy0dlx9/6yP9Wp0U8cEUAif0PcxxgMc3Wg7kmfRRuFt+o1Kz5RxWILhEvmQIUOGvMb8IKbIv8ZVkwtX8fbXZB/SMuWGLMZax8qKoCMrTI8twFJGVhQkJ59n/UyHY/fdzf5sHj2zzIIY8Hvf+Kd8tP0jmJVp2vEalZV5XL/NRno7tvUcGevEa7t4bu4AteIIbW8R4RzWWQQWrCMQPi5ex0pDkRtkvMSLrRfYsms72xdAVyv0Rpq4+QVuP5Ly4m5Nky77Og8jsiVG197HBXK2NDPe8cRXGaz4rAR7+Oa2jOlwg9MHM74+Wi517+ps4+Qde/GemeX5eD/3Ppry4QOfJa1pUuV4Pt7FR/TjPD1W8K6NuxlkCTqSPBNv46Pew5yTp1g4vIWZ/jZm1ka5kLWReZNqvUu3GFBgadSqyNxSiSoE+Qp9pRDWEUuPLVmXH5qMaSw8jzRNyFQpMq8gziy+79GzAs8WZca0LUAqFnsJcnyccOvVU8CJamPRnPPfwunuCGN6jhe992G9MbSLyWREJutcD7feRWGRkyNUu12cEtjmXoQ+T6PYIPV8fLdKXwjirOBC7U7GQ4e/983EviTLHabWJFm+QKYNlSjEbCnn07Uf4m3ZhrIF1mrIevhG0xwZh/4A72VVPikEuQrLfPGNHm58irzIEEGV3KtSBAFivc/L3zJyfg7V3SDds//q56bKDHIA0e2iWw1cPKBvBe6WB4g6pxA2xdk+wjOYepMiiXFCsmYj1FvejmlftqAVQmAmxknPz6GiCC/wr/ULBawDo19lZnD6tnIoZ3EaeeIoAntVBdM5R+y1kNUpWD517f1tTmJa4DYrmNIglUZrg3NwcjVnREAh5OUKuGdw1iKEGC6RDxkyZMhrzOsyi9yur5fGzukA5wRFXsb9Lc4n2CzBIejoLXTjZ+jOrRDJDfpnl/nfbvgWFPC5hc/xC/lPoo6fxEs2iIutOO2higHkk7jeIYJgHdPb2PyQy8oPOufQWYdCR8i1ASNPPMrxXc8DcOBMi//4tqe5tTHG3UsVmt2zLK+sArBlWVF4T4DcwaP+br4UWKL9v8n9Zw9h73Q8vPqPyTceQgjJ+6Yf46/DOr8xa/ji4A4et4d4orIT3gDvWXySB594gmyf5iO9/5GtxSLPma282f4+nx9d55fnyyEJJQXN2PF8vpe07vNQfJBHskOMRuuMD3bxkeQ4kamx3O+BBS0kKsmpTY5j5xcZbHQQYUjdh3+eP4mL9rPsUiQDUBLn+8Dl6XxnLWM6ZWB8RJYQBT5hf5Z+ZSt6cxpbXjGokeSWTGyn2/hF8qIglysc9r/JPPewoVqkLz/hV5BkFnoDVGgY8RWu7lPdO0663me8HpDHOSsbklz7yLTDmZUeFc+HG34IGjUq84v0koRyxkuTCY0XReVkNiCVZlA4KvU6xAHkGVJ4eEEFX8c0K+aq/RFCUOgKmY5QDGBqDLE6izAe8dxpfBzeYICrXZE7UBQgS7sh578svUeVb2l1YRZvbZ12PWAiW+NkNAb1XQzqu/D7c0jWqFVaSKWJF2YZOI8LZhcPbGlcc8z8AwdIZ8/jrKVR9/G1JCss5gqxbJ3DyO9gSiEE0+0qcyZCuuyqHkznQEldTp8H1/liYC3TI3WiZb15e4fejO2UUqB0eVlcMWwkPY0rLpvYDxkyZMiQ147XXVRksbZGsb6G9H1YPYd1svxMFvDkapcZdx7nHHnuUM4RvPQS88+eI+0l/MuV9/MP1bt4i72RP3J/wmpnDash0wVe/ghi/S1o4aD1Jarhszid44RAWLDWooxG5wPEfMogeRtz07djihwvl9TDj/D2M+/ghZGYP9tzlHubj3FoZIPVbbuI8n3UFwrW5k/zkmzzYP4UP/Hsx7hx/mN8KvkVvrLrCwjToBoa/mntDkbP7mVu+T5ayzfwlNrKvdkMP9J9nB879TAv3HkvP177nxgvunzRv50ZOU64tp8oU3y1OkPNdAlCzaHqKQ5WTtDLJcezUfaJGR4NfpF7gmMgFVYYtJYYLfD7KXGc0R9pI4xBNmrIbh+MhtDHS5bwwgjlGVAaUQ3KKubmhz/OIsMGmWlQ2IK0KKt6Ik/wKWjmy5eWh9Pc0onzzcxpymEdP+JIdj8XfSpfiSSzdNO8HPIxCpGkbDmwldpNe1GNBnqlQ6NWJQwqZKbCEbsXa+GWbU12jZWTz6GnyK1jtmdZHBTESCqtBmLTkF1qhVcbwdbHN6erDaI6gZYCszkZfQ0mJFcVkAZXDUBqhPZASKQF6YeIJL4UZ6oW53FRhPV80FcLVpTC1pvQ75NIg+quY8KA/o7LCUZJZYpg2yGCkcnSwsg5VusH8Mb3XrOEDyArlfL4W4vyPQJPcT29pl91jXzzqWpNsbk8f2UFc7m3+YVj8nA55v9ynC0z1inF7PluQceWol6J8tgalxAUZeWe3hI68jfrvoJiKDCHDBky5DXldScwbb8PnlcKgsE6sY3YeOEMST8nLSp0XA8L2EFKTQkCLGmckBSWfgHTL+W0Yo9j1RkeHj1PYiRK3EKhbgSRUYR9siCmsBm5MzgBOIG1AmU0KqiihMYWMXOtiHT8rdxzusfW+SPsvvAgH3j2xzkX9fidKVDVEbr+NGl0iHpllG40ybvN1/jX0f/O2/PHCOIFqnGNm9du4pd2fwIR5TwycYGzgcRmVXa4ef6H1f/EA/FJ7l55nonzF6inmp9mgVuL49yfP8VH9ZfZV425a6HNoUEDrSReZ4ULpqwifYSHeMT7R/yWe4Qj/Q9wRyhpeV0a/RjjS+pSUIlzpIDcM/j08S+akytJqjWugPqOnYxuG8VpBQKM6EO+2YjpLNoPMJU6OIcnLQWGvLAEJCilaFc0aW5ZH+QoKS71+wkhqFVCZG0Xa8FNr3ru09xS8zWF1iijcXmON9EEoTCTk0jPA+0jgypx0EJE4zQjw4525VJVzNeKwjqiSoi/52YyB2PvfhBVKwdjpFR4Y9txE7uB0n9ShLUyTUaJq2x3LqKUph9M4zyDzzqtqfHSkkgq7I7diCBA9nuIeFAeLs8vh3vCEGeuTag5PrmX85nE+j7CD1DjY9fc5iKm3sZrtHFCU68Y/OsIzHLQx5Vxj1ojN50WrHOkuSXJClb7GWnxnSdptFJklXHSaAorL+/7Si+lERrQ189Tx1mE8hipeqz1M1RrB6M3lgbtoVH4pBTRKF6gy+E9m6NUWTGXeTGsYA4ZMmTIa8zrbonc5TnCOaCgyDJmz/RYudBhz7YuvtwgzzOylQ75Yh8vzfCloufg61uWCLyU+1em8F7q8bZwN1/Z+xIHFmvU7DHS1W8jQ41Q4xRZwWpvjHSwRiZmOd7o0Fz7ANX0BCpuk2W3ksVfwFU1SuwAACAASURBVGbH8fVNPHfHjQSrp5hY+yzVdsFPPvPD5N4zfKOSctPGUbK0ifSqTOo62/IznEj384KuItvfQC3DeHedr9wU8vDep/nZb72JLOlggwSdWFTYQ9iMtXabx971IdrRLtqiw2oa8xaeZtxYEl3h3t4IlVySKolSPhdqW3gsvo3x7hepqZxYbGOx2I4/IWmqc6Q2o7Z6ntGoylhlkvOtNkL0EKpgpO7ByjLSKOzGGt18O+bAAfz+DEutgmq1iacWkXmC9cuoR2MMe0cmWY/PYjsd8lqFbp7SDmCy3STTinVf00tzIk9dFesohCAKrxYm3STHSIlvNnv2coeD8r4XowTjFKEVKIO/fz/pVzUoD+pbeGnqHrRWeEpdNc0cGllWQJVAUcYkhsFloeQFIX5UxRYFwq9gTRUpNb4pPR7Ndap8zjn6cU7bWHACVx1DxLJc7q01kMpgwxCRZ4j1VdTKIulNtyC7G3CdimhRb+I364S1CqqiMHfdQ35+cN33gxACaXwcgm2tCq3oWsEqtC71pbWgFEqUkZELnYRBWhB6ij3jEVn+nUWckmAPPcByzb/q+mbk8YbdbYh8MGFZxby4hN5bgs4cTN6MQDC7NmCi7hO0yr7ctx4Y57F1j9rW7chkqRSYQQMxWCU8sAOeP8GwBXPIkCFDXltefxXMNC17v1zBqcUNLsz0yK3BdrqEZ5fwzq4zM3+K/iBHNGrgaVw14Hw9JjGWxTWL6kXsmW/xwWcP08rrGHkGR5+0s4K/nOBvaLywiytOsbIyQ/3sGpWBz2DuJGftETayP4TsLLt7h7nQ/jP6oWJ8YYEDz/wVB4MLhJ37ebo6zR/vPM19ow8RZI7MVFhylpMr8MypHdzxn7+C//xfM9c8ybrd4L8dH+PbjZivsZeOqPGCN8L/3bqLOe2TxRsU0kNFNZS0+Dojk32csPjCo7GQgUpZK0Kc8pAoZKPB9Og0X89u40T4LvboL3Fn5f9Bihxz4x7c1Bi6gGYClahOpdVGpx16B26GsSayGLBaCNLDN2NHGjwXvaE01p4c4aUt76RX206yugEbXQQWITVjzQaTLqURxNi1HtIVNCseRmv8ok9NphgpGav7SAli5gJk1ybXWAtZYVmPL4+qrw1SgiSmsrpKWPGpVn1UvVJqGKlLESUU6AClDWu5phEatLzaLsdoicOhRGng7RCXzMEBTBAwtXc/QkiEH2CFKZNrENy6vXXdCuZUMyArFHljjCRoszz9NpClwBRaE9baNMe3I9fXUMtLFLU6TkqyfYfKFJ8ruDg5HlQjbtk7xeTkCGZsFHudSudF5GZF39OvsMStdVmJLwow5lImOUCzYtgYZBze0uDgVO3697/yoaR8xYnuSz2dyrvaV6i3ALVJCOpoJQg9xUacXzovjYrh7jvfyLbb305N5eUU+mbEpqpFSK0ohgJzyJAhQ15TXn8VzDhBKEWeJQySjO78WYxoMLdQIOIcl1uS/gBrDcJoBkXBufkN3pOM0dyyj7U8QTmFVjfR7p1gXbwF0X+IsFJHZQ7X7RGMS1S8TOR7xNE4up+S6YdhfZ72AOZGltmXjzDnPcrnbljmY8dGOXHDIU7qjHcGX+VN6r/j/x0RfPDYj3Gk06bp/QXPpmM8Go7x1uR5/JU+Fpirtel4fV68tYfM66yd/DX+OpLM+hG3cRwtE0bsColqU5htNIxDuYJGmLDUVxQ2xtvQFPUpiJfQNZ+2SBF+HVVRBIlkek2i63XOp9uIqjG9eoVWvUbYnaM+WaPeD/C3jNFoNYmSlAXRprLRI5caojZ5bZxddcvRXLLmKvgmYSXzaIiIeq+DchbabRCSdGaewAvIdk2zdCqjvTiHmW6C9lHxOm1lWZNNAq0gL3BhAGlW9npeQWYtFaNJxMUeT4dnc6QtqI/VqSpFuGsLRX+ArPilwDQG19hDmimU79GIfCJf0U94WQVTEaeWqq9xlDnmoXd172etvWns7nl0F+eJGmWevXgF84RG6DFbOFb2v5t0657ytlIhpEJqjyCqlV+Kul2KRhMXBIg8J5/aes1j5dZR8RSHd49Tv+0WhO+T8Mq2DQDh1E6MP/KKQzpCiPI9M79AGASoVJBiEcD2kQrOQdXXVw39vBJSXp3IeQnH5equ8sAVXPrz5DfgwHshGsVfXmKs6rE2yK6ybWpUAxrhFPnu3VAMQCrIY6TXRJhX780dMmTIkCHfe15XAtNZS/LSS1ilOH3yOfI4JXYJwivoxAOEEYSJozA+G4OMjTghUBU8zyDI6K7n4HxyNwHcwAkzxsF+QLJ+hrw2xWCwTFHkqAUflxQItQWt342I6lh3ltWJWSoLMbuTLXijbQom+fDzCUUyyoafs2P+JOtfNzx++wf52JF7EWKdvb0/ov74CQ5ygo82MybuXOPfuHuZ2XE3It7gQLfC7sRy12qTExvPclNxkuPBKMfCHXwo/Uty5yMbAlWE+F6MSB2eVCghyXEU1iec2oN+8dv46ymqGuAKiVcdxaysUGmO4y9tcEEeZqN5mJGoXGqt6ZipiR3I8z3aI1W2TTWZn13lpG1hijNIZTCNFmN3vp/RmmLbiR7JRg2JwTeSuJsyWpFoGWPm5rFSw9gYenISObUFLWJanRn8ahtsVvZGUuAVAt9IFGA9g8zLeMc0t3ir69CskeQwUvXIujF5p49cXsOTknaoEb5BAcHuLeWLYrAGypTDSe0x7GBAvVmlGRkKW1bVrhSYo1Wf6Wa5HN+Jc1rRy4ZsKCMRK40GS9lJIj+kWm1gk4Rs5hz+nr3X3F5LATiKsH7Jt1NIiVAKoQ1OGxAC6/ll36XvI7LsmscByAtHxdNMvPvBS9epbvKqClNqgwxC1KsIRCElZnqq7FU918O6clf3jlWp+ZrI/+7+lJQV3GslpoPL9kLauxwxWW68zFkHDk7V6Kc5/ay4xogdZdC3/CisnYX+Miw8h3DLNKoBrbHKd7V/Q4YMGTLke8PraoncpSl2bRXrG7LOIlmjSZ5Z0jCjm67S8yRvb/wBd0SP8PlwL2fnF1nvwcruiMGao7e+jOdgRifMqQscisc40pjnqfEf4feaDzIztg2BpejH2CLDOR+okYuEU7rKWP5BwuYvM561eHDl82yRc/z33qc4GjT4pH8HO2qn0P2ClUGOSde5/+F/wnKeIbRl7PAGeV/x0sIkOEvSWcLUGigTUB0EVNc97o3P0BQrbHhVqiYnr0b0tm3hlolJfNVHC4eUBQJLXURUlCGrR4h6C+kMIhD4U1vJswzd3o42PqYaMogzApHSyOcZ779Iy4eoVmdqew1fxkijkVJQDQyJjBAiJ23Vad/+IDsn2phKgy3NkDMjb2Jxx7t5w64Rtk+NUoQhiQzReQ9RgKpVqX7wZ4n3vpu0upV2IFGN6bIfT5Wm2tvaFZSQGCyrqb00Wb0+yMh6A9JuKYA9LbEr62TL63ScgEpAvV1D+h7iSh9OV4D2EFpTf897EMYgPA8tJVKUk9FXJgtJKXjTvjFu2tLAKEk9uFZgArQmp8mkZKRSZXrLNtxggPQ8ivV1oHQzyJeXcdaWQkkInLy8X9XdN4BUCKAYHS+XqaMq6Y23kt5wC9nW7dfdbm4twcsqdi9PRrqSufUBxxc6LHXTV61yohSqVkNVq8jNyXPnyse+YbrxXVUvgUtT3dfj0n6aCIqXtT5s9mOOVn3u2NHC3+wFvXYDojRpr7QhqCPICCuGxne5f0OGDBky5HvD66qCCSA8j/XFGbLBOglVchPg+ZrcM+SF42l3F3vMU9waHmNMrSOY4zPmMIf2P8J9Sy2E7aHEAT5XqfMzgxcZTwxJ9Xl+eurTvL/bY1vNcXR1Cyc6I/zYzk/yj6MXmMtHqS18CJu1qcrzTJ78KhdSxZ//+GkmB5qR7gJbZYMTjVu40Xuc6vxxJvRRVqYnWdx2iE9vu526G/Bf7ftLXlxpsv9Ej5dGG0hjwBZYF4JNwTNIlXHzlhME2RheapittMiq29m5+AKBqdPNcnppjEsk0cYAOQ3ODzEqxNQa0IjIli1TzR3I8BTtumbhfI5nckQFnN9kvDhPONYEIdG1OWS+AllAxfXBryKjEYLDDXYdOHjpuBst2Ygz9oxX2T9Ro3j/ezjyyecZbAiMzcCUFSbRGIO0B35QCi7ll9UsZRDO4m8uowpr8T0NWcZiN8UoSeIERV5QUxC5AiMEIyNVukjQGj3aJNy/o+wlvEgWQ1hmb8tKpawa+j71QCMQ7JusXiOeGqGhERqsddTD6wtM7Qd4UYTqDMjm5ihWVzGTE9hBn3xhAYcrz59zqGarrOldsUStPJ/63sNI45FNR2RZiiiKMkv8VbCOS4NNF5FCvMK6dLmkftfONhtxVk5xvxJSISrltrUUnF3p06x4l6brv1uuqTpetZ+bFyot2JgF6pe+QFyZ+hP5mqqvX90WabPqKbRAVgKKjc7faD+HDBkyZMjfjtedwMTmpPMnSIsIl1omFs7Sre3ABjE73TxH1n+EZ9Q9/GL9/+TM1E7+yu5h60ybfXOHcCMx3azLRGUHv9D9Ip7eIJuf45FblvhSo84nGnX+/rHbGLMFzYbFiKP8bv9RvtJ/J1+Uz9GrJPzdM/+e7nLAb/6I4khrwNfzH+IfyFO8qPbx5eQw3BbwwGNfBuD0rfdhxRjb8gyTnuRUb4y7vv4SAuhO72VNuHJ4QQky49AmwoYh3oSicspS0zUW9+3m3FnDwY0ZqG0F18E5g8TR9qpUqtP0K1WiTNApusxVO0xIy3h9ivDgbiYWNojPHGfkoGGlnpP7oxi5AToEHLW33IPoLUBvBRWNcEOzxYq8Ad05d5X4MFKSFY6x6qZ34cgIF974USa//SRFvgTSoEZHy6VhUQoslCmXS2U5r02tCd15CJpM13zOVZtkZ2YhL/BDD9+z5FIwUqSYfkGtYqhXfCa3juNNjqBqEaoaXvVaIB9ANHrpKhEEmIkJ7t5dis5Xq8xd9Ma8HlIpTKuJkR52EOPv2YPNUszoKMXyMi7LEL6PSxKkLVDxYDOF5zJeo33Ff/xX0ohXYZ3bXHK/jHml4R3K57etXWGi/gr2QJtU3nDXpl0RbCQZVV+TFfZVBeP1qAWblkfX4VIFM2hunpsUFp8vz88VAjMwivfePPWdNyYNFBkqCq4S70OGDBky5PvP609gFjmdHqxmI9TnTrLt2FM8FUgWD62xGh8iTLdi/VX+3eqP8ZzeyVxP8ztf/dcsVdskSwnPbh3jzdGvs1vO8qnlG4GQ+xc1jXCUQMR8/NC3CArFz39tBx/nQR6orPNC5+f44erv0/Sf5hvjt3O/eowH7K0MXriFuzsX+On2Q/w34i/peTUeWykj2F/Yso8/bR1mRYzwd8xzdPJVus2QXj1gbvcEvXaEK3IsEiFy8qiLnspZEw36Imci9NCp5ZbWG+jOP490KWJtmUZN03cNFA5fWqwxZH4VajXCWgs5uRM5lxA2RxGrFYJGzO4H7sQPB4y3t4BXgwuLENRgy52I7gLkcXlswxb7Jxuk297MUudqW5yL1aarjLyDBnp0nGQwhkg1un1RUAmEX0FU6jhhEBM3Aa4c/tiYA2cxEianmpw7c55weQUv8tnetGRZjFYeKvSY8jQIgfA03tQo17B2DsJ2KWg2qdz1BnS7hfhbLqlKpdCeh/JyZJ4T3XcvvUe/gR4ZxRUF5AV6apLkuWO48+exfoB8BRG01k/xtKTifee3q3PlpPaVGCVxlOLz5cvlgldfQr+IN3k5qlMgmGgEzG/E/A315eb5v/pOzrlyPy4+mKmUt8kHEDahSK/JLf+O2KJMNZJ1ot092Hfob3b/IUOGDBnyt+L1JzBtQX5qiYm10zy94z6euGMPP/zNT7Pt1AGO3vo+xhb+moWpGczSLB9eOEKlGJCagtMHAm57KuFM5Wc4NfMkz9i/plcLOLCyzNtaJ/jMuR/ln3rvpdr8dW57IeOev36RVMPp9gRjOx7hrom/QImCXrXG50bexB/n9/M823mj/Cyf79/FnsoYW8UzxFv38CeTP8Mn3D7qZCy5kETt5r3qBWQRcPQtB3C5Q7OCK9pIq/GDgo0oIWsrZo2hJiJ2TET0OhI8jyTwSbXChhNEeg2TLiKMoRKO8cIgxBY+0fgewnGPytgU9m2jBH4EeYLsn8ffdTMsHCtNsKduKQVlc0fZ69bYBvPPlLYyW++EShsPmG5fXd2zrlxavcryR0m8u9/IeWfh9HHk5hKsEJBHE8hdb8DlBSKoYQcDhDaISrv0OQRqtZBcKYJaiJ930e0RlJVY54OUSGPwd04jr6xaXomQELauqm6ZifHvyctMKoU2HqaukPU6ql4nPHwTqtEguPEGcA47GBA/d6xMNWq0yD3/um/IlX6Kc7DnVSqmF7GbHp1XYlRZFT6+0GXPWHSNAP2bisR794zw4nyHxY3kuxKnV3K9iqdzL0sBUqbUoM6W0ZFp928uMJ0tbaemDiPWz4H4zibwQ4YMGTLke8frS2A6R7y+ykbm2Hn8WYqJj9Ks3cLsG+Y4x9vg/2vvzoMsu6vDjn/P3d6+9uvX+/Q2o9n30YZACI2ExGIUYsWIhEBSBIcq45hUOQ6kkjJUJVVeKgE7JsQOm2xcEAKJTAwGCTBgYiQEaBjNSDPMotHsM93T+/LW+8sf93ZPz6hn6VZvoz6fqlev3+/dd+95v75Tfea3AmcrB/iBeTMPyndoHjjD8M5uftJY5pfWXkYSe3CMITb8LMdaE2w804/XVODk94do2XySf5r/MY3Pvo67n32Glws2/+WBNt5x4BLv8f47z5U3Mt6fYH9/G493PkDWLfNQ5Tli1gTDVpHR6HaembyXOjYdziDvrp3Fqp7kmJdid7RM3PdIlCKAw2RkElMq4VbHqHl5ak1FEsUqR+oDEN+BUxqgKx/jkJ0gnYhRyWWx0ymGJUY2bnAcoVKuUm3qwVRjTMQz1O7dSyQ/wj2td2OMwbZsSDYFawpG0kFLnx0J1iPc+ujlOrWsoAVw9GzQwngNjiWsycevGB+Yirr0FJKczbUg505Or33Ylo3hWhb2cAu1vj6qQ4PUBwexszncSApKIwhCLBYhUcwTe/kg4kRJ3b2b8uGDmEQblQuX8JoaiHZdpyvV9qDr9a/qlrqWWDJFvq2dTO9t08vpuK2tVxxjRSLBov+eR727OxjTOuN9P9wtJ+LaWMzeAnk1Y8CdJYmLOhbpmEO56uNEZiRrcv1xkbPJxj0SkWBi15wTzFmO9425slzCtYz8OkRSUK/OI8E0wczzwm3Q9YYgUVVKKbVkVlWCWZsY4/lj/QxE47RbwvpDn+Jg1xYOJX6VmlPms9Fh3leL81ApTT37L/jx6y9i14vky/v5zcT/5huyFSn9Jb9s9shLHseZ5HRzL95AifaDR/nHHAXgXFeRI21dHJt8lIGOZ3iqr4XkUUO1XmHvoac53t7D+toFajIBsTI5J4+Fj2PVMcbCq4+y2Xfw7bNsZIRmdwPVVAuD5XEysQjHSuNIpUzNQD3eQW7P3bQM7sPUj9HTtouJ0RgNxSEytT66iinGxgp4Pe2UT0ex3RpZO8bImREqjU2Uoj1UfZ+WaIGmeIyEm7hcYY3r4dwvIN0G0UzQejlbQhFNw9j5a2/zB3QVEnQVEleU3bM26LZ+3dpGKv0FvO7u4HSuzZqGOBPZDLXDh7FcBztcKxMnBqYGxsKJuuy6vcCLF9OYVAuy8S1E/RJ4KSKdzYh7o9vbgBO5wTHzI5ZFy9r11z/GdYNu8iNHSPZkOTtZozF1eRzm+eESdd9M18eZwQnyiQi+b4JWXt9w4tI43YXLrZLBGMxXJmMNyQjOZJXzIyXiJZuWTIxa3WeiUp/zRB0IWj2Fubd+2pZgrhqDeW6kdOUYUMu53IIZywXjMefTgmk5wfjdzrvn9lmllFKv2qoa+V6r1jAXzyIxn+9s28BgbxqpHeW5xk/xUuH7PFb6Hm32CfzBz+OM7+PFwgGeXvN1BirbOF6+kw80foD3tj1JITHJRL6BQ1s3IpFRjmzdzpEd2wAYiiX5gw2PkcjU2F4/xxe923F86DpwAG+yzjOvv5MNtXM4E3UStWG8eJ2mTI54ZJJC8iJOZYzOgRGi1WHEKhEbnsCaLFOMpcjGXNJehLaYR9kCxzbUGzeydf0uEl4jW+Jr2daxGzJriWx4iF3dRRqSMe7Z2Mba7bcRj8VwbY/KhVEk6VIvNuM3t1Ku+rQkG9he3H5lhdleMB7OiUDrjtmTSwgmU8QbwJvfWoOuX8eKRrBiV3Zlu8UilusisTh2Mhl0K9cMtdFJQJDqONSrNLc303zbjiAJ9lIwOYhlSsF+3jOVR6A0clXsy/t/LHfNGsS26W3OUJ+xn2G17hP1LO7ozpONu6wtJhkr1zk9OMHhC6O8PDBB32iZXNzjxXPBDGnfD1o8Z5tdfc/aAg9sbGJra4apMZDnhktEbGvOrZAAjgTd7nP9rIjgiIUfftdyrY5jCR25Gb/7qRZM4wcTfNbcPfdJOpYddJErpZRaFquqBdPUanT84qe0J32+u24XmWw3p8//gk1HfOKN4/h+jb6eNVwaP0U5+jV+1DNCvOJxx5lt9DvN7K90Y5VjFNNtCDHG7TMYqSB+hvPFLk7vXcsPIw0c8tbwZH0XBTNCRdqoOB5DjS10njjG+d4OxLeoW5PExCF7cYB4ZgIao7hmkoI9QiUGBXOWv0/4NEcTNJSr5K1xJswYmAzFWIozlUkyiQLZlk6K6QRO705KowMYL4lnD4IXRywXLBs3lsLZ+jY2HvkbHKeIJRWIGwbdOK4tWJaQmG0CSTQLHbcHyeP1tO/m+nvFXJ84DjLL8jtusUjyjfcyeeAAYtuYapXa4DBSqkICqE9Az30k26MQCbtAN70DRs7CkaeCltUp5TEojQbjR53I5ZbLubaMLTDLiyCehxf1EClPlw+MV9jRkWVzW4aNLWkmqnVEYKJSpzUbZaJSp1LzaUh6jJcdjDG8cH4Ex7JmbcF0bQvXtugtJjnePz5dlk96RJy514FYwX0zn9ZP1xHOj5TIxl0Gx6t0NSbY0paZUSlhYujXg2EZmbY5X4NcdzCcQyml1LJYVQkmIpzcfTvNmeOcSrWxv1Ykti7K/qaXefT5IvXJERLJDF6xheebz/Hwyx2s6U9jez/HTTXy7NBu8iWo1RM0pEawjM24GER8DJPEqHFfuZ81yTFkYoyttdPsrJxlLJXi1Pa72D/eRySRRgaHqFvgRXMYpxxM8jAmmB0tFarxCKXUbQy0TeL5p9lwyBD3x8ESHFOjsamLU36EdbE2Er1NtGZjtGZ3YIzhxKUJ3KmEYf3D03+sJZ4jns9RPnaU+JYtdGaivDCewxaLxlSEXHKW8ZOWFXSL34iXuPEx1+G2teFcNT5x+tSdnUgshj85iV8qIZk0/uhRsAQRC/LduO6M1i/bhXRr8FwahsmB4DneAA1rYfgs9B0Ofhb72q2yS8ROp3AaCpBIgFxeq9EQ7LENwezqqBMs6h51bN54WyPfPdRHazbGtvYsf/P8Oap1Q0PCI5fwyM6yu9AUS2ZsWCmGDc2pm14k/RWxz7PuUlGXcs3nwkiZVNRha1vmim0fETtcAD8C6ZtYjmg2lvWq70ullFLzt6oSzCp1jorDi8Mbabdsup2Xebkeo2koRn1siHq9gisFssMZHhrN4MWiVOIWdavGqD9JYgwqdgLXTGBFbJyqzUithudYOLVRHLdC1Rfu8E5SLQ1TtpP4uFi1cXyrjPEEu1ajUq9johPEWnbQMuFSGunDqZeI1GvUJE1/z25adm4lM7mf9ZfSpHMHYbyGODHiLmQiOfasbSFtxcnubJr+fhLusDI9ycO6soswfvseKmfOQOftuG1rmHz2JK1xl1TUoZBcnLGIN0uuk6y4xWBmt9fRgVgWJTlFdWCY6aWLrma7waSk8YvB5I5EYzDRI5KCyveD5KM8HLSOLTM7nSb10JsZKdevWB5yaKJ6ReLn2BbpqMNYuUYhFSURscklPBpTESKuxfmREoWUx9u3zZ6oT59navAkUzP759+CO5+udYA3rCtwon+c/3e0n4akRz5x1e/QcoLliTru1CRRKaVuUasqwax/89Ok6hP02y3EccCM0X2pQPOpEvX6JNHsWsT28CuDlP06lrEwksBxbJJY+HaSkjWB7fcTiXfg1kY5P2JhImOUJs4T9T0scRjza2DVqBHFr9uI8Uh5UcZ8Hxkfp+QKUc+hvmEbh0ZvY/vx71E+14/VmKIeL1B1EjT09HD7eB+Fhh14w2fh4iTN6RgJM4HBIp9rARMsDD5TRz5+zd1lppbLkXqdmGuTjXlsbEm/YvLNSjU1pjJ6x31ETz59eRLHbNbuDXYEMvUg2XTCJOa2N8PwaTj4xPxbxxaYWBa2dXkZnZrvk4k5r1gwfXNbhpHJYA/ye3oLxLzgu3u2Rdnyr78TT2iqS/vg2WEaU5Hpc8zHfJcKjXsOqajLRKU+PRbzqiBhw6+Ae/3F35VSSq1cqyrBHP/2j7j9+CXe+eCv8eGJJ/mr7oNsutDM+voWqkMjxH2wjRN0/ZkYrnHxq3EccWn0q5SKGVLWMapn6jjRDP5EHxE3RtWJIVhMWganVqUmFjg+VAz1chnBJZPMMullGR58GcuOIEmLUms3ibrQnDjDsYko9YKh0ruNicRaLBHuX3M/ZvQCteMJRifS5HIp6HuRug9OPo/X2/uKlj/Xtq7ZGmlFItjpFH6pjG0JXQ1xmjO34B/xZDGYsNO44drHePHZJx3ZbrB2Z6YtSD5XCFtkelfE8XKdbNyj4arfYzAUIhgOkJvR6nf/xibOD0+yrpi64XVcWyhV67RkYrx9e8tNLd4+a7yW4LyKxejzCY/uxgS12RJM0ORSKaVucasqwaz89h/yd5/8E36t+hz7iwNUrAqWU0XcOl46QnQMBk2KiIxRMimq5DWGJQAADhtJREFU1Trp8hBeNkGi0Ea+KUsu5/NyzcN1HEbKNulUkZFaljJ50n6di+4wmUqVRN8kl7wRnKpFQ6KIZeK0WsJg+jY87yLluEvfWJWdrUUa8pvpO2cYjNeY6NyFP1qZHhoototEE/i1KrWxEk6yiC9RrHQaJ5ebcx24nZ04hWB5oN1d+RscvUJ5ieBRuG1+n7cdSLYEXegrhBVucHPi0jjGQDF18933U3uj34yYa5NPRGjNROedXAJ05uOv7Nqeg0TE4e6eAiOTlXmfQyml1Mq1qhLM73zhL5iwkmTMBZ5Y8wIPHu/kLpOlz6/QYgtVIySccSJxFzsS5WJvhTXPH8PZvIdIpBOpjJLb8iawT1A58hJ2roNMLMXJoSpjpMg0uyTPlRgbuESs0ET1YgVLLhDPrsEZGyK6ppv1Td0My0v8LDJOlxtld3cBcd+EN1bk9FCZvFhXbt/nRJFMO3axjilNUhoEK1vDzmSu+12vJbZp08JV6HJxYsHYysirWDy7aROU5zE7eZG4lgUYkhGHfMKjZ5GGLYgID2wskoy8un/6liU3ndReS2MqQuMcEmmllFK3jlWVYBb23MeLP36JjN/Pg8P3sk0qDORBzlVwPI9YU5yWbJJU1GfkgZ1UBw6SOn+cjc2dnB40GLGJrtlGS76LiUSW8v59XDh/jhYsRnMFNt3xOmoXjvOtwR/RkegmPtFPqT5GU+8QjSeGSL9pL+XWbZTNJvqPXMCx3OmJHF5nN5VS33Ss0wmmF0e2vA178O/AasCv1vB6enGbmmb7iquDZQUJ5qtZwzLREDxWCMsS1hVTtOVitOfmt57ozUpFX11iqJRSSt3Iqkowy91refzkMB8cG2PTZC+xxiNUygNEomka1uSItvXSs20niWicU9YQL1VOs+1N92E5ccyZQZrbXWzHgmyW+I4d5H95mEprG4ODA6S6u0lu3kRpYyfVnxzDHzY4Ld3sikfo6imAdQy3o4doLk6l5hOxh7Bm7M3tORaT1TrH+8eIe84VO6RY8TipBx/EHx3FHx4mvn3bMtXgCtJ1z43X57zF3Nnz2vo+SimlVq9VlWCms0eJ9f4xR87v4U4nR92UcE2MdZvfhBMdIpnLk25qQSwLf2iAhmgDMcvCHx8llYLi+vbpc4nr4kaidO+4i7ZMikvnzpBqaGSyIkRjOdxqBDubYd1bHyTeVER6D0MuXG7HsdjdmbtimRfXtkjHXGwrWGT76sk7YlnYmQxWJoN48x/79pqRKCx3BEoppZS6hhWXYIrIw8AfATbwGWPM7y3UuXc33sUbj6xnY+d6IjsLjB3sp7Grkx333MnAmcMUu3qnl8LpznTTnenGungIe+Tv6e71oPN1l+P0PJyWFhJdXaQzGfIdnVi2TZPTRHfnuzg1ZnNXbIRELo+40VcsWL6+OX3F65hrE/csWjIx+kbL19zjOXXffYirXZxKKaWUWrlWVIIpIjbwKeBB4DTwrIh83RjzwkKc33Ed1g22wGaf9e2bOBqxKSY7SOaiJHNXJoDW1BaC8YZgSZzkuitjdV1SDzwwnZBadrCeoG3Z5GNZSpVJerdsvenYIo5FzLXpaUxSqfnXHCenyaVSSimlVroVlWACdwBHjTHHAUTky8AjwIIkmPFMgvTmNF0btrOraRe92V682XaCmSmShIZ10P2GV7wl19gFZXNbho2t6VnfuxbLEh7YFOyd/Lq12v2rlFJKqVvXSksw24BTM16fBu5cqJMnYmn2PvLPaG3qwhKLXPQm1pH0ErDpV+Z0nag7/91RlFJKKaVudfPfimNxzDby8IqtPkTk10XkpyLy076+vlkOv87JRVjTtg7H0W5mpZRSSqnFstISzNNAx4zX7cDZmQcYY/7MGLPHGLOnsbFxSYNTSimllFI3ttISzGeBdSLSLSIe8Bjw9WWOSSmllFJKzcGKGoNpjKmJyIeAbxMsU/Q5Y8zBZQ5LKaWUUkrNwYpKMAGMMd8EvrnccSillFJKqflZaV3kSimllFLqFqcJplJKKaWUWlCaYCqllFJKqQWlCaZSSimllFpQmmAqpZRSSqkFpQmmUkoppZRaUGKMufFRK5SI9AEvz/FjBaB/EcJ5tTSuudG45kbjmptOY4xuFaaUUvN0SyeY8yEiPzXG7FnuOK6mcc2NxjU3GpdSSqmlpF3kSimllFJqQWmCqZRSSimlFtRqTDD/bLkDuAaNa240rrnRuJRSSi2ZVTcGUymllFJKLa7V2IKplFJKKaUW0apJMEXkYRE5LCJHReQjy3D9z4nIRRE5MKPsYyJyRkT2hY+3znjvo2Gsh0XkoUWKKSoiPxGRX4jIQRH5eFjeLSLPiMgREfmfIuKF5ZHw9dHw/a7FiGtGfLaIPCcifx2+/oKIvDSjvnaE5SIifxzGtV9Edi1yXFkR+aqIHBKRF0XkbhHJi8hTYZ09JSK5pYxNRNbPqJd9IjIiIh9e7nssvM5viciB8B77cFi2rPWllFJqca2KBFNEbOBTwFuATcC7RWTTEofxBeDhWco/YYzZET6+CRDG9hiwOfzMfwu/w0IrA/cbY7YDO4CHReQu4PfDuNYBg8D7w+PfDwwaY9YCnwiPW0y/Bbx4Vdm/mVFf+8KytwDrwsevA59e5Lj+CPiWMWYDsD2M8SPAd8M6+274esliM8YcnqoXYDcwAfyf8O1lu8dEZAvwAeAOgrp6u4isY5nrSyml1OJaFQkmwR+3o8aY48aYCvBl4JGlDMAY80Ng4CYPfwT4sjGmbIx5CThK8B0WOiZjjBkLX7rhwwD3A18Nyx8H/sGMuB4Pf/4qsFdEZKHjAhCRduBtwGdu4vBHgD8Pv8/TQFZEWhYprjRwL/BZAGNMxRgzxJV1c3WdLUlsM+wFjhljrrcJwZLcY8BG4GljzIQxpgb8AHgnK6u+lFJKLbDVkmC2AadmvD4dlq0EHwq7Aj831U3IEsYbdkPvAy4CTwHHgKEwGbj62tNxhe8PAw2LERfwSeB3AP+q8v8U1tcnRCRydVyzxLzQeoA+4PNh9/1nRCQBNBljzgGEz8VliG3KY8CXZrxeznvsAHCviDSISBx4K9DByqovpZRSC2y1JJiztbKthOnznwZ6CbqnzwH/OSxfsniNMfWwW7WdoAVr43WuvSRxicjbgYvGmJ9d9dZHgQ3A7UAe+LdLGVfIAXYBnzbG7ATGudy9O5slvffC8bLvAP5XWLSs95gx5kWCoRRPAd8CfgHUrvORlfpvVSml1ByslgTzNEGryZR24OwyxTLNGHMhTPB84H9wuYtyyeMNu3m/D9xF0C3pzHLt6bjC9zPcfLf/XNwDvENEThAMZ7hfRL5ojDkXdp2Wgc+zPPV1GjhtjHkmfP1VgoTzwlRXbvh8cRlig2AM48+NMRdgZdxjxpjPGmN2GWPuJbhfjrBy6ksppdQiWC0J5rPAunB2tEfQhfj1ZY6Jq8aWvZOgOxGC2B4LZ213E0x4+MkiXL9RRLLhzzHgAYIJK38LPBoe9j7gr2bE9b7w50eB75lFWEjVGPNRY0y7MaaL4Hf1PWPMe2YkJEIwZm9mfb03nIF8FzA81f26CLGdB06JyPqwaC/wAlfWzdV1tiSxhd7NjO7x5b7HwhiK4fMa4B+G8a2U+lJKKbUInBsfcuszxtRE5EPAtwEb+Jwx5uBSxiAiXwLuAwoichr4XeA+CZbaMcAJ4F+G8R4Uka8QJC414DeMMfVFCKsFeDycPWwBXzHG/LWIvAB8WUT+I/Ac4YSW8PkvROQoQUvUY4sQ0/X8pYg0EnSj7gM+GJZ/k2Bs31GC2dP/fJHj+M0wFg84Hl7PAr4iIu8HTgL/aKljC8c4Pkh4H4X+YJnvMYCviUgDUA2vMygiv8cy15dSSqnFozv5KKWUUkqpBbVausiVUkoppdQS0QRTKaWUUkotKE0wlVJKKaXUgtIEUymllFJKLShNMJVSSiml1ILSBFOtSCJSF5F9Mx7X2y0HEfmgiLx3Aa57QkQKr/Y8Siml1GqmyxSpFUlExowxyWW47glgjzGmf6mvrZRSSr1WaAumuqWELYy/LyI/CR9rw/KPichvhz//KxF5QUT2i8iXw7K8iDwRlj0tItvC8gYReVJEnhORP2XGXtgi8p7wGvtE5E9FxA4fXxCRAyLyvIj862WoBqWUUmpF0wRTrVSxq7rI3zXjvRFjzB3AnwCfnOWzHwF2GmO2cXm3n48Dz4Vl/w7487D8d4EfGWN2EmxTuAZARDYC7wLuMcbsAOrAPwF2AG3GmC3GmK0Ee6IrpZRSaoZVsVWkuiVNhondbL404/kTs7y/n2ArxyeAJ8Ky1wO/CmCM+V7YcpkB7iXYHxtjzDdEZDA8fi+wG3g22PqcGHAR+L9Aj4j8V+AbwJPz/4pKKaXUa5O2YKpbkbnGz1PeBnyKIEH8mYg4zOj6nuWzs51DgMeNMTvCx3pjzMeMMYPAduD7wG8An5nnd1BKKaVeszTBVLeid814/vHMN0TEAjqMMX8L/A6QBZLADwm6uBGR+4B+Y8zIVeVvAXLhqb4LPCoixfC9vIh0hjPMLWPM14D/AOxarC+plFJK3aq0i1ytVDER2Tfj9beMMVNLFUVE5BmC/yC9+6rP2cAXw+5vAT5hjBkSkY8BnxeR/cAE8L7w+I8DXxKRnwM/AE4CGGNeEJF/DzwZJq1VghbLyfA8U/85++jCfWWllFLqtUGXKVK3FF1GSCmllFr5tItcKaWUUkotKG3BVEoppZRSC0pbMJVSSiml1ILSBFMppZRSSi0oTTCVUkoppdSC0gRTKaWUUkotKE0wlVJKKaXUgtIEUymllFJKLaj/Dw7wtQT8dcGMAAAAAElFTkSuQmCC\n", + "image/png": 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\n", 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" ] @@ -595,7 +308,7 @@ } ], "source": [ - "model_dirs = ['data/lunarlander_dueling dqn','data/lunarlander_ddqn', 'data/lunarlander_dddqn']\n", + "model_dirs = ['data/lunarlander_fixed target dqn','data/lunarlander_dddqn','data/lunarlander_dueling dqn','data/lunarlander_ddqn', ]\n", "group_interp_2 = GroupAgentInterpretation()\n", "for model_dir in model_dirs:\n", " for file in os.listdir(model_dir):\n", @@ -604,6 +317,13 @@ "group_interp_2.plot_reward_bounds(per_episode=True,show_average=True, hide_edges=True, smooth_groups=20)\n", "group_interp.add_interpretation(group_interp_2)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs_src/rl.agents.dqn.ipynb b/docs_src/rl.agents.dqn.ipynb index 04dcc82..d83ca0b 100644 --- a/docs_src/rl.agents.dqn.ipynb +++ b/docs_src/rl.agents.dqn.ipynb @@ -48,10 +48,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 11, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [], @@ -61,10 +61,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 12, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [ @@ -99,10 +99,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 13, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [ @@ -165,67 +165,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, - "outputs": [ - { - "data": { - "text/html": [ - "\n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - "
epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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21.015652#na#28.00000000.88085900:00
" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "memory = ExperienceReplay(memory_size=1000000, reduce_ram=True)\n", "explore = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001)\n", @@ -237,10 +183,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, "outputs": [], @@ -250,26 +196,13 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": { "pycharm": { - "is_executing": false + "is_executing": true } }, - "outputs": [ - { - "data": { - "image/png": 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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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epochtrain_lossvalid_losstrain_rewardvalid_rewardepsilontime
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\n", + "image/png": 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iVGD/auDdBODEd0Bxhjjm3kEsVVqx5NI9/LqK5Z43xfK6J+v3PrU3OXikjBshxAlR4EbI1ayiUCzVWkDrA1SXWs9U7XkLOPIl8N18sX3uT6A4U6zLg+8OfgoIu9YYsGnrDMrrEQgwZt/XUFdtG7eahs8jhBAHRJ0TCLmaVV4WS7WbaHdWXSYCnpJs4Pi3Yl/CZOkcV/NrXTyNgZubv1h6dgQGz7X+PGuzJ9gTU4iOEtQ5gRDihChwI+RqViEHblrA1Utk2yqKgA9vNAZ18WPFMY2H+bUGHbDzFbEuV5VaMmg28McKsW7vMdusUago40YIcUpUVUrI1UwOzjQeIoMGAF89YtwPAKuGiGXdHqC/vwFUS2O/NRSQhV9nXG+JXqSWKFTUOYEQ4pQo40bI1Uxu46bxMM5wkJFkfk5hulham0LKO9T6wLuAeZu21grclBS4EUKcE2XcCLla6aqBLU+IdRfP+r0967ZHqy6tfw+NB3D9U8YOAQ1iov1Za1CoAANVlRJCnA9l3Ai5Wh381Liu9TEO4SEbMBX4dbFYNxiAooz69+h9P+Ad0viz7nwbqC5uflmbitq4EUKcFAVuhFytirPEMnK4lG2rM0yHPKQHAHw7C7jwl3Fb5SrmAvXtYtuzPIMABF1JaZtGoabAjRDilChwI+RqVZ4nqkjjx4ptjcmsCWHXimrQbrcAp3cCBzeK/cG9gT4Pi16kBWcAn86tX25bKKmqlBDinKiNGyFXq7I8EZyptcZ9So1YXjNVLGNHml/jFQr4hIox3YLijNNLtTcKFaDXtXUpCCHE7trppy4hpEXt/xg494do26Yw6RE65n2g5JKxo4Krr/l1PuGtV8YroVSLKa84b/mZGgghpBVRxo0QZ3D5PFBVCnw5GfjxedGZwJqaSuC7eaKq1NUHUJh8DGg8AP9uxmDHdLaE654EOl8Hh6BQizlXeQPvAyGEOCDKuBHiDN7qCfh1AwpOi22mAG57zfK5lUXGddNq0sb4hBurUts7hUrM7MANAFpp7DhCCGkFlHEjxNHppDk55aANAJJWW8+6mQZuMaNsf46LR+PntBdKlci4GfSNn0sIIQ6EAjdCHF15Qf19NRXA3jctn18iTQx/zXTA14Y2a1G3ikwbc6DMlZxxA2/rkhBCiF1R4EaIo6uwELgBQNp2y/vP7xNLDxvHVUuYAtz9oZho3lEo1CZVpYQQ4jwocCPE0ZXnG9eVamDMB4B/pOVMHABUXBZt23zDbH+GaScFR6BQiZkgKHAjhDgZCtwIcXSmAZpKC6hcAO8woDTb2P5NlvINcGwzoHQxHwbE2Sgp40YIcU7Uq5QQR2eacVO7ibZoLl5AdbkY+kPlYjz+5SNi6RHUehO+twWFkoYDIYQ4JSf+5CbkKmGacfMJF9kmF09RVWit/ZtS7VidDZqqto0bdU4ghDgXCtwIcXSmwZmLp8ikuXiK7T3/ZzxWXWZcV6idPOOmEtk2mvaKEOJknPiTm5CrhFxV6hUCdOwp1uXA7Z/1xoDNdPw2N3/zGROcjVJqv1e3jR8hhDg4auNGiKMrvQT4RAC3/ke07QKMgRsgAjeNu3ngFjW8VYvY6hTSR5ueAjdCiHNx4q/chFwl8tIAd38RrMjVn6aB27IoMam8HLhdMx3o2Kv1y9maKHAjhDgpCtwIcXRleYCrt3FieKD+4Lo/vwJUFot1F3fzc51RbVVpZduWgxBC7IwCN0IcmUEP6KuNgYqMMWDwPON2ZTFwNFGsaxxoztHmUmrEsrq8bctBCCF21iaBG2PsKcZYCmPsKGPsc8aYK2OsC2PsL8bYScbYF4wxTVuUjRCHImeUFBb+u2jcjesKFXD4f2Jd7V7/XGcjj11XU9bweYQQ4mBaPXBjjIUAmA0ggXMeD0AJ4H4ASwC8yTmPAlAI4NHWLhshDkfuNamw0M/INLNmqDGuu1xFGbcqCtwIIc6lrapKVQC0jDEVADcAWQBuBvCVdHwdgDFtVDZCHEdNhVjWrSoFzDsomDKdScFZUcaNEOKkWj1w45xnAFgG4DxEwFYEIBnAZc65PFrmRQAhrV02QhxKRaGYdxSwPO+o1hfoEG0+0G63m8UE846kuhT4YQGQedD2a5RS4FZV2jJlIoSQNtIWVaW+AO4C0AVAJwDuAEZYONXiXDWMsemMsSTGWFJubm7LFZSQ9u7Dm4Dtz4t1pYXpqxgDhr8KDH3OuK/bMMvVqu1Z1mHg8jkgea3t16jkzgkUuBFCnEtbVJXeAuAs5zyXc14D4GsAgwD4SFWnABAKINPSxZzzDznnCZzzhICAgNYpMSHtUeFZ43pD844Gm4zZ5ojt22qknqGllwCDjZPGK6mqlBDinNoicDsP4FrGmBtjjAEYBuAYgF8B3CudMwnAljYoGyGOKSCm4ePXPSmqTVUOVk0KmA/pkZdm2zVyG7dqCtwIIc6lLdq4/QXRCeEfAEekMnwIYAGAeYyxUwD8AXzc2mUjxCFcPg+c+M647RUC+HZu+JqI64FbFgKuXi1ZspaR/rtx/eeFQOaBxq+pzbjRALyEEOfSJo1dOOcvA3i5zu4zAAa0QXEIcSxv9ayzw2Jz0PqYA463XXRR/JjatQR44H8NXyf3spV73RJCiJNwwE9yQkgttTsQMaStS2E/1WXAhb/E+tnfgT/fs3xe1iGgqsT6fRgTY7lR4EYIcTIO1r2MEGLmjmWAq5Xx2hxN1iHgt/+K9WufAPa9bzzWczxwZJNx+7f/An7dgNsW1bnHYdEhIfw60c5NR4EbIcS5UMaNEEdSN8uk1jre8B6W5J82Bm0AkH3E/PiN/xLLgFjjvpIs83OqSoHfFgN73wb0epFxo0nmCSFOhgI3QhxJUYZx3cXb8owJjuinF8y39dXG9WEvAX5dgBl7gYcSjft5naFBdi8zrh9YLwYl1lWDEEKciRN8VSfkKiI31L9mOhAUBygaGL/Nkcnjr92xHEiYLNqsdYwX+3pPAA59JoY3kXEDkHvCuH1yO+AdZj5HKyGEOAHKuBHiSIouiKV3J8CzY9uWxR5KsoDP76+/Xx5/TeNWPzi9+wPzoA0Azv1Z/x4KFaCnwI0Q4lwocCPEkRScEcN6uDnJrCEXk+rvU7sb5xi1Nq+qxh3QVxm35fZuE78VSxcvUVVKgRshxMlQ4EZIe7X9BWC5SWP8zU8Af6wA/LoCLu5tVy57Mugt7NMBZTliXR5Ity61FtDrjNu6CtEZoWNP4JqpoupUKQVu3MZx7gghxAFQGzdC2qs/3xXLsnzgxFbg4Kdi2z0AULm2XbnsKf+U+bZbB6CiwLittvI6lS4iwONctH+rqRDDfyhU0rEaQKmSzjE0PJcrIYQ4EArcCGnvqkqBrXOM23IjfWdQlgv4dAbGbxDBFufAnv8DUr8Xx60FqCoXka3jHKgoBE7/IvYrVOKYXifWDTVS71MK3AghzoECN0Lau4o84/rt/wW8wtquLPZWVQwExgGdehv3jX4XWNpVrKutVAkrNQDXATAAGcnG/XLgxvWiU4OccSOEECdBgRsh7d2uN4zrLt6iCtDRVRYDf68S2TI3f/NjWh/juquX5etNM26mvU6VanEMAKAQgZuldnSEEOKgqHMCIe1d2o9iqVADWt+2LYu9HN9qzJT5dzM/ZhqIaTwsX6/UGNu4VRSKfWNWSnOUSoEbU4gqU8q4EUKcCAVuhDgKhUoEJs7AdA7RzoOtn2ctu6jUSJk0A5CbBnh0BGLvFMfkjBtjVFVKCHE6FLgR0lo4BwxXEESEJtivLG3OJADt1Mf6adbmYVW5iGmxSrKB7ENAQDTg4imOuXqLJedS5wSqKiWEOA8K3AhpLdueAl71tS14Kzhbf1/8vfYvU1sxrQ61NMju9U8BEUNE9bAl6XvFBPI/Pie2u9xgPOYqtZHjBvFjOt4bIYQ4OCdo5UyIg0heK5bFGYBPIz1Dtz1Vf5+LlfZejsggBVNu/pYH2R2+UAyeq7QSuPl3BS4dEeud+gL9pxiP1WbcpABZV2mXIhNCSHtAGTdCWpvcmL4hZXnm2z3uMekt6QR01aJqc8pPDbRjsxK0AcCIpcb1yT8C7iY9U+sGbjUm7ekIIcTBUcaNkNZWNyizeE6ucd07DOg5znk6JgCAoRpQaQHv0OZd795BLGPurD+7gjyciNy2jQI3QogTocCNkNaWewKIvNl8H+fAewOAhMnAtY+LhvcdewH9J4vjThW0GYDz+8Q6a2bSX6EEXswz750qc5HGfpPHb6OqUkKIE6GqUkIaUlMh2lo11ZldwL4PzPfJvR6zDgKXL5gfK0wH8tKAH/8lgriqEpFV8goWP86k7JJxXXEFU1Gp1JYH6FW7SgP0Su3oKHAjhDgRCtwIacjaEcCyqKaPvr9+tOjxWFli3CcHEoe/AN6KB45tNR4rOGNcL88Xw1ioLPS2dAZFGcb15mbcGuPqY+xNSoEbIcSJUOBGSEMyD4jOBOm7m3d9oTSsB+dATZ0A4vi3xvVP7zGuL5VmEnDW8cdKssVy+H9argrY1VsEvwCgq2qZZxBCSBugwI0QWxSea951m2eKZWkOAG5+7OR24PdlIqizxLNj857Z3pVmA2o3oP+klnuGq4+xipsyboQQJ0KdEwixxrR6tPSS9fPqMg3ELh0FSnOBM7/WP6+yCPjlP6I9W11KDdD1Rtuf6UhKskX7vZasCtb6iHaDgOjoQQghToIyboRYU11qXM86ZNs1lUXAKz7m+3KOGTsjeEhZtE59jcf3vlX/PlG3ASrX+vudQWUx4OINqDQt9wwXL2PARhk3QogToYwbIdaU5xvXc1NtuyYjuf6+9aON60MXiN6jFYWi/Zw1NeW2Pc8R6coBTaeWfYbGzdgZpG7bQkIIcWCUcSPEmlJpEFyVqwi0bJnzUs6s9Z0IBMbVP+4eAHQdahwk1pLoEeLHGZUXiAGINe4t+xy1O7VxI4Q4JQrcCLGmLEcsvcOAykJj1WlJNvDxbUDRxfrXVBWLZae+QJ8J5sfCBlqf3knrC3QfCXSIBnqNA3yaOaNAeydXCytbsJoUEBk3PfUqJYQ4HwrcCLEm57hYduorOipcShHb3z8DXNgHrL2j/ryjckcDtbb+3KI9xxnXXetk3MIHAf0eBoa9JHpcOqu8NLH0DGrZ56i1AGiSeUKI86HAjRBrLp8TmTDfCLFdJFWDyuOvXT4HLIkwv6aqVFStKlWAsk7gZlo92KkPMOxlIPw6sS1n4hRO3uzUzR/o2Bu4+aWWfY7a5L2mjBshxIlQ4EaINdXlokpPnvvym8eADffUP880MKgqFoEbU9afjkmhNt8OjAU0HmK9PUyEfilFzCNqT5wDJ74zZiZ11YCbH+Dub9/n1KUxyVpSxo0Q4kRsCtwYY90YYy7S+o2MsdmMsQZaVxPiBGrqBG4AcPrn+uflngB2vQEkfwIUZ4hqOqYUAZxHEKDxFO3XLA1/0bGnWNYN6lpbbqoYU+6LCY2f2xRHvwIObAD+eEds66taZyovNQVuhBDnZGu9TCKABMZYJICPAXwL4DMAd7RUwQhpc9VlInBzs/AdRe1mHLJj1Q3mxzpEG6s+R70tAgdrY7KFDQBuehHwCbdfuZviUgpQkiVeq6ymUkzUbg9HE6V7lovsm75aan/WwuTAjSntVlWanJwcqFKpVgOIB9VWEEJahgHAUZ1ON7V///45lk6wNXAzcM51jLG7AbzFOX+HMdbAIFSEOIHqMkCprt8DskO0GI8t9QeRUapL42E+eXpjA+l2jL/ysjbXL/+pv6/0EuDb2b7PKUwHdr0u1mvKGjzVLuSqUoXSbhk3lUq1umPHjrEBAQGFCoXCyjxlhBDSfAaDgeXm5sZlZ2evBjDa0jm2fmusYYw9AGASgG3Svjau2yGkBRn0YoL4uj1DARGIqd2AgO6Wr9X6tmzZWlrRRTHWWsHZK7uPrs5UU/LsE3F3X9l9bdECGTcA8QEBAcUUtBFCWopCoeABAQFFEJl9y+fYeK/JAK4DsIhzfpYx1gXAp3YoIyHt0+XzokG9t4UqTKUaYMzYsQAwr/5za+GG9/ZibUDh8nxg+7/EjzzrQHmB+dytjeEG4KcX6+/X+gFxo5pe1qaqDdwU9gzcFBS0EUJamvQ5YzU+sylw477ZCIUAACAASURBVJwf45zP5px/Lm2f5Zy/bqcyEtL+VBaJpXsHsfSPNB6Th+xw8TTuG/UOEBAj1lujDZc96K1UIZZkG8ejKzgrtrc8DqR8bfu9jyYCRefFet+JxqpjlYvIgrU0eegVhYImmSeEOJUG27gxxo4AsPoNk3PeqzkPlXqkyo18OYApAFIBfAEgAkA6gPGc80IrtyCkZclzk8qZm5teAPa9D1zcbzlwU6qNI/W39KwA9iJnoqJvA9K2SzsZUHDGeE51KVBRINYzDwBdhor3YfBTgKu39XtnHzGux44CwEXvUm5onbHqaoPnlgvcvkq64JNbWm23FxPgodHdmxB22V73I4Q4p8YybncCGAXgR+nnQennewAWWmXb7G0AP3LOYwD0BnAcwHMAfuacRwH4WdompG18M10slVJTTrUWCL1GrHsEiqXc/s2nszgv+nax7dXCE6jbixy4BfYw7nPxMmbKABG4yb1nC84AW2eL4U9OfN/wveUJ3n3CgW43A/FjxXZZrugw0NJqq0qZMaC2s9zSalUnH9cae/3YEgQqlcr+MTExcVFRUT1GjBjRtaSkxOJn+NChQyPz8vKa9EbL1+Tl5Slff/31gMbO37Ztm6enp2efmJiYOPln8+bNno1ddyXmzp3bqaWfIRs7dmxESEhIz5iYmLju3bvHbdmypdnPXbFihf/EiRPt1nV83rx5nQIDA3vJ7/vjjz8eAgADBgzoHhERES/vv/3227taOj8mJiYuLy9PKf8OY2Nj4yIiIuITEhK6f/7551a/kS1YsKCjfL38bzEmJibutddeC+zTp0+MQRoHUqfTISYmJm7Hjh3ups+OiorqsXHjRu+GymTpuSUlJYrRo0d3iY6OjouKiurRv3//7mlpaRr5ug4dOvQ2vVdlZSUDgPXr1/swxvofOHDAFQD+/vtvrXyOt7d3H/n3O2jQoOjU1FSNq6trP9PyvPvuu/XavcjvcXR0dFyXLl16TJw4Mdy03KdPn1YPGzasW+fOneNDQ0N7Tpw4MbyiooIB4v8MY6z/Z599Vvse33TTTZHbtm1r0r+tBj8oOOfnAIAxdj3n/HqTQ88xxvYCeLUpD5Pu5QXgBgCPSM+oBlDNGLsLwI3SaesA/AZgQVPvT4hdBMQCuccBtw7GfRFDAFdfwL+Lcd9dKwEYRFVglyFA+ECAOcjsB3Lg5tHRuE/rA1QVGbdryo1BmKmzu4CeY61nF6ukeV0jhoihUcIGAF4hYvowxuxT/obIVaWMAYaWCdzagouLi+HEiRPHAGD06NFdli9fHrBw4cJL8nGDwQDOOXbt2nXK1nvWvSY1NVXz8ccfBz733HO5jV2bkJBQ+uuvv9r8rCuh0+nw1ltvZbbGs2SvvfbaxcmTJxdu3brVc9asWZ3vuuuuo635/IbMmDHj0quvvnqp7v7169efueGGG8ptPd/0d/jHH39ox40bF+nm5pZ+1113ldQ9d8mSJdlLlizJBgA3N7e+8r9FANi3b5/HW2+91WHevHl5ixcvDuzTp0/Z8OHDy3744Qdv+dn//POP67Bhw7rff//9hxoqU12LFy8ODAwMrPn222/PAsChQ4dcwsLCauTnz5s3r5OHh4e+7r3+97//+fXr1690w4YNfn379s0cMGBAhXzN2LFjI+68886iyZMnFwLi331YWFiV6WuyRn6PKysr2ZNPPhkyYsSIyP3796caDAaMGTMmcurUqTlz5sw5rdPpMGHChM6PP/546Nq1ay8AQFBQUM2SJUuCJ0yYUNTYc6yxtXOCO2NssLzBGBsEwL2B8xvSFUAugLWMsQOMsdWMMXcAQZzzLACQloGWLmaMTWeMJTHGknJzG/1cIaR5vDqJqa78Ioz7GAOCe5p3SnDzETMByJQa0a7KEcjDZLh4AHd/CIz92Pha5IzV6Z8tz+pQeRk49m3D9w7uA9z2X7GtcQfmHgXu+ch+5W+IUi1VybZcxq2tDR48uPTUqVMuqampmq5du/Z46KGHwnv06BF3+vRpTUhISM+srCwVACxcuDAoKiqqR1RUVI9XX301EBB/pKxdM3/+/NALFy64xMTExD322GOhY8aM6fLpp5/WDmY4evToLnLWxJJdu3a5RUdHx5WXl7Pi4mJFZGRkj/3797tu27bNMyEhofvw4cO7devWrceECRPC9XrR4eXrr7/26tOnT0xcXFzsiBEjuhYVFSkAICQkpOfTTz8d3L9//+5r1qzxHTt2bMTatWt9AWD37t1u11xzTfcePXrEDh48OOrcuXNqQGREZs6cGdKzZ8/YiIiI+B9//NEDEIHf9OnTQ6Ojo+Oio6PjFi1aFNjQfUwNGzasNCcnp3Z/Q8+eMmVKWN++fWOioqJ6/Prrr/UmHv7ss8+8e/XqFRMbGxs3aNCg6AsXLqj0ej06d+4cn5mZqQIAvV6P8PDwePl32FoGDRpU8cwzz2S+++67Fv/+NuS999678Oabb3ZMSkpyXb16deDbb799se45/fr1q1QqlcjOzm7S68rKylKHhITU/kfu3bt3lVarbbCjUFFRkSIpKclj7dq16d98802LdPV3dXXlH3zwwcXMzEzNn3/+qd26dauni4uLYc6cOfkAoFKpsHLlyguJiYn+8r/p2NjYck9PT/0333zj1fDdrbP1L8wUAO8xxtIZY2cBvC/taw4VgH4APuCc9wVQhiZUi3LOP+ScJ3DOEwICGs3mE9J01WUiYFFqWqchfVuRM24aN6D3fUDPe0WvT0AMaRI5HCjOBC5ZSTLU1PtSL9rBlWSLdmWeQYDW5O+7QmE+FVVLk9u5GXT2n8qrjdXU1GD79u1ePXv2rACA9PR018mTJ+cfP378WHR0dG2jvt27d7t99tln/snJyceTkpKOr1+/PmDv3r3ahq5Zvnz5RTnzsGrVqovTpk3L/eSTT/wBID8/X5mcnOwxfvz4IgBISkryMK1aSklJcRk6dGj57bfffnnu3LkhTzzxROi4cePyr7nmmkoAOHLkiPvbb799ITU1NSU9Pd1l/fr1vllZWarFixcH//7772nHjh073q9fv/L//Oc/QXJ5XF1dDcnJyanTp0+vbfNcVVXFZs+eHb5ly5bTKSkpxydNmpT39NNPh8jHdTodO3LkyPElS5ZcePXVVztJryvg3LlzLikpKcfS0tKOTZ06Nb+x+8gSExO9b7nllsu2PLu8vFxx4MCBEytWrDg3ffr0LnXvNXz48NKDBw+eOH78+LF777234NVXX+2oVCpx77335q9evdoPALZs2eIVGxtbERwcbKXrN7By5cog+X1PTEysDQImTpzYVd7/2GOPhVo6f+DAgdHW7jtgwIDy06dPN3kE7s6dO9fMmDEj58Ybb4x9+umns4KCgup1Q//ll1/cFQoFl1+XrWWaPn163jvvvNOxT58+MbNnz+505MgRC+M0mdu4caPPjTfeWNSrV68qHx8f/Z49exr98JG/sMg/ctDfEJVKhdjY2PKjR4+6HjlyRNu7d2+zD0Y/Pz9DSEhIdUpKSm2ZX3zxxazFixcHN3Zvq89s7ATGmAJAJOe8t1TNyTjnzU7xAbgI4CLn/C9p+yuIwO0SYyyYc57FGAsGYHHEYEJa3N63xfLyudap1msreilwU5t8NmmlxIpSDQT3Bk7tAPJPibZvVcXm16tcxFRWYQNFVWhlEbBrCeAZLAK31pjaSsI5B6v7u1K7iWybQSc6RTjBZAdVVVWKmJiYOAAYOHBgyZw5c/LOnTunDg4Orh42bFi9kY1/++03jzvuuOOyl5eXAQBGjhxZ+Ouvv3qOGzfusrVr6ho5cmTp3LlzO2dkZKg2btzoO3LkyEK1WiSfrFWVvvHGG1m9e/eOdXFxMaxdu7a20WTPnj3L4uLiqgFg/PjxBbt37/ZwdXU1nD592nXAgAExAFBTU8P69+9fKl8zceLEep3UDh8+7HLy5EntzTffHA2I6t6AgIDajMy4ceMKAWDQoEFlzzzzjAYAfvnlF68ZM2bkymUPCgrS79+/37Wh+7z44ouh//73v0MLCgpUu3btOm7LsydMmFAAACNGjCgtLS1V1G23dfbsWc2YMWNCc3Nz1dXV1YqwsLAqAJg5c2be6NGjI1966aWcNWvWdHjkkUfyGvq92KuqtC7Omz/izXPPPZfz2muvhcyePTvfdP/KlSuDNm3a5O/u7q5fv379GYVUK2FrmQYNGlRx9uzZI5s3b/basWOH16BBg2J37dp1ol+/flZH1960aZPfnDlzcgBg7NixBRs2bPAbPHiwhW+bRrZWldYlv2fS51C9N7Due3r77beX/vvf/4YtgaEljQZunHMDY2wWgE2c8+LGzrfhftmMsQuMse6c81QAwwAck34mAXhdWm650mcR0ixyFWJw37YtR0szzbjJ5MGDlRrz9msuHqKTwbHNJtdXAuf2ip8H/gek7xH7S7IB8FYZFuVUTinuWLEb4X5u2DlvqPlBtdYYuFnvHO9QTNu4mXJzc7OYUmzoj7C1aywZP358/urVq/0SExP91qxZk97Y+Tk5Ocry8nKFTqdj5eXlCjlwrBtcM8bAOcfgwYOLt27danHEZ09Pz3rl5JyzyMjIioMHD56wdI2rqysHRDZEr9cz6Zp6f1Qbu89rr712ceLEiYWLFi0KfOSRR7qkpKQcb+waS6/R1KxZs8LnzJmT/eCDDxZt27bNU84IRkZG1nTo0EH37bffeh44cMB98+bNZ9AG9u/f7xYZGdms6UaUSmX9L1CwPUBriLe3t2HSpEmXJ02adHnixInYsmWLt7XALTs7W7lv3z6vtLQ07axZs6DX6xljjH/wwQcXFXZuyqLT6ZCamurWq1evzICAAN2WLVvMqmULCgoU+fn5ql69elX+9ttvtYHav/71r6xFixYFq1SqJn842foKdjDGnmaMhTHG/OSfpj7MxJMANjLGDgPoA2AxRMA2nDF2EsBwaZuQ1lddJv7o93mwrUvSskzbuMnkwE2hNg4DAkgD2dZp65Z50Hz7wAZpRfocaoWM2z3v70W1zoBTOaXIKqpTPrW7ND9qTdMGD7ZRgIdGl3m5Um2vnwAPjdVqsea6+eabS7///nufkpISRXFxseL777/3vemmm+o1Ojfl7e2tLysrM/vbMGPGjLxVq1YFAUBCQkKjf9QfeeSRiBdeeCHz3nvvzZ81a1Ztdd2RI0fcT5w4odHr9fjqq6/8hgwZUnLjjTeWJSUleRw9etQFED0IDx8+3GBVWK9evSoLCgpUO3fudAdE9WVSUlKD1Xu33HJL8cqVKwNqakRy7NKlS0pb7qNUKvHiiy/mGAwGlpiY6NXYNZ9//rkvAGzfvt3D09NT7+/vb/aPr6SkRBkeHl4DAHIVtGzKlCm5U6dO7TJ69OgClar1Ozn99ddf2qVLl3Z64okn2lWN108//eSem5urBIDKykqWlpbmGhERYXWcnw0bNvjec889+ZmZmUcyMjKOZGdnHw4NDa3+6aefmpXhsqaqqorNmjUrNDg4uHrgwIEVo0ePLqmsrFTIvVF1Oh0ef/zxsClTpuR4eHiYBWj33HNPcVFRkfL48eNNbj9i678MuT3bEyb7OERHgybjnB8EkGDh0LDm3I8Quyq9JHqPuja77ahjqM24WQjcuB64fg6QshkozRbBT+RwMd7bDQuAw58DpSadgwpO179/K7RnK640xjqXiisR7G0SLGrcARikoM3+GTdHGHNt8ODB5RMmTMjv169fLAA8/PDDuddff31Famqq1cEGO3bsqO/fv39pVFRUj5tvvrlo1apVF8PCwnTdunWrHDVqlNlrltu4ydsLFizIKisrU6hUKj5jxowCnU6Hfv36xXz77beeCoUCffr0KZ0/f37oiRMntAMHDix5+OGHLyuVSqxatSr9/vvv71pdXc0A4OWXX87o1auX1SkvXF1d+f/+97/Ts2fPDi8pKVHq9Xo2c+bMSw0FlU899VRuWlqaS0xMTA+VSsUnTZqU+/zzz+fach+FQoEFCxZkLlu2rOPYsWOLG7rG19dX37dv35jS0lLlhx9+WC+L+MILL2Q+8MAD3YKCgqoTEhLKzp8/XxukPvDAA0WzZs1STp8+Pb/udbaaOHFiV1dXVwMA+Pn56f744480wFhdKZ+3ZcuWU4D4HcbGxsZVVFQo/P39a5YuXXreUo/SlmCpTN27d68XkKWlpbnOmjWrMyDm8rzllluKJk2aZHWc1y+//NL/2WefzTLdd9dddxVu2LDB7/bbby+1dp3cxk3efuihh/JefPHFekHsxIkTu2o0GkN1dbViyJAhxT/88MMpQPw72bx586np06d3Xrp0aXBBQYFq1KhRhXJP3LoWLFiQ9dBDD0VaOtYQdiX12W0tISGBJyUltXUxiLNZPVxMdzX8FfPJ4p2JwQAcWC8CsfmpoiMBAJzZBawfLYbtmP6bCHq+myfai922GLiwDwiKB756FDi5vaEnADc8C9z8QrOLePjiZfx5Oh/Tb+hqsfoFAIb/3y6czBGfwx9PSsCw2CDjwXV3AZn/iMzis2fNM4uNYIwlc87NvlweOnQovXfv3g22O3JWJSUliri4uLiDBw8er5tBstW2bds8ly9fHtRaw4e0hQEDBnRftmzZBUttzGzx+++/uz311FNhycnJqfYuG2l9O3bscJ80aVLXL7744vSQIUOa9G/i0KFDHXr37h1h6ZjNuVjGWDyAOAC1KWHO+fqmFIQQh1CSLaa6ak9BW85x4OdXgDvfAjw7Nn5+Y5LXAKd2iqyU2qRmqMsNwIg3AHdpNACFEhj1tvF4+HViact8rN6hjZ/TgCc++wcXCiowoIsf+oaLTKDBwPHc14fxwIBw9A33RWWNHt5aNYoqalBQVueLusZddEqo7ZxAmmPz5s2eM2fOjJg5c+al5gZtpHHPP/98x08++SRg7dq1Ftv6EcczfPjwsszMzCONn9k0NgVujLGXIQbHjYOYNWEEgD0AKHAjzuXwJjFzgHs7myhezm6l7xHDdlyps7ulFQYoTZoTMQYMfKzx6wfPBQ591vA5gbFNKpLBwPHZ3+cxtl8otBolLhSINmvfHMioDdzySquwKekivjmQgZOL7kBljaE2cMsvrVOzpnETARs3GHvQkiYbM2ZMyZgxY674j8+dd95Zcuedd7ZKFVxb+fvvv5udKVu8eHH24sWLzarUFixY0HHLli1m7cnvuuuuAmtVb/bUFs9OTEz0euGFF8y+8YWFhVXt2LHDQluMq5etGbd7IaamOsA5n8wYC4KYa5QQ5/L1NLGsaGfNl87vE0uVneZBVbmKYMbFyzh1l40qa/RIPFSERrtu+HVr0n33pxfgxc1HsTstF6smGmsp1/95Dq/eFQ8AyCkRAViNnoNzjooaPTp6i/Ln1824qbXGTFt1ZfOHDCekjZjOVHA1PHvs2LHFY8eObfJwHFcbW+uCKjjnBgA6aSy3HDSzYwIhDiGoR+PntAV7DQjsI32pHfhYk8eq+y01B6/uzKi3P6LyM/SsXI2qG18CJm0zdnSwkdyObcfxSzh5yXJiZnuK8e/Ir6k5qKzRw0srxuVauzcdBoNJm121u7E3ad0esYQQ4qBsDdySGGM+AD4CkAzgHwB/t1ipCLG3rMPAX6tsP7/7HS1XlithbW7QplKoAO8w4LonGj+3jpJKHaqgwSp+N97t8JL5MbhhYcFwMW9rE8dLqqgRQZaBA88mHjY7ppcCsnd+MbZrP5ZZDJ2BQ6sRwazOwLFyl0mNisbNOM8qBW6EECdh0ycr5/xxzvllzvlKiDHWJnHOJ7ds0Qixo43jgB+eFbMANCbkmiZni5pjUxrHgj2Gpo1Ubq9e4FUlovG+ouljRRWWiyrJ99gD+Flxbb3jFwubFyRVVBvbvZu+TI1KgRp9/c4Fl8vFeFwapfFj7I3tqUjNlsYJV2tROwxITbPGEyWEkHbH1s4J6wHsBrCbc25xtGhC2jW5cfqPLwAPfmH5HDlacPNrlamunt0rnjerpx5h3g38VzTtEWmw0xitZbliZohmvE65LZmBAxkWgjRLQZYtKmqMr62sSqwrFQzVOgOKKmrMAjQAWL3nbO05pranZKN7Ry9RVQoAgXFiCi97O7jRB6U59hsl1SNQhz4PtrPGlYSQ9sbWuoxPAAQDeIcxdpoxlsgYm9NyxSLEzuRR/E/+aBx4ti691Lhd2bojlmeUNhLo6Ewa3TcjcFv+jwEJnxvw4znRoB+nfxEZN28xL3ZOSSW+OXDRpnvpDRyrdomZeEqrdMgtqcJ7AS9jfvWM2nMqapoXuJWbZNzksdnu6CmGPtm0/wKKKmrM9slKK83fk9r7yFNuRQ0H3AOaVaYGleao4B1aY7cfG4JApVLZ33QS7Oeff94OY8NYt3HjRu+WfoZsxYoV/r6+vr1jYmLiunTp0uOVV14JbO69UlNTNVFRUXZrqLpt2zZPT0/PPvL7PmjQoGgAmDdvXqfAwMBepr+TvLw8Zd3zY2Ji4jZv3uwJGH+HkZGRPbp37x63cOHCIL3e8igriYmJXvL1bm5ufSMiIuJjYmLihg4dGhkSEtLz/Pnztf9mHnroofDnn3++o/zs2NjYuK5du/aYP39+sKXXYFomSxYsWNAxMjKyR3R0dFxMTEzcL7/84j58+PBuMTExceHh4fGm99qxY4c7AGRmZqpUKlW/pUuXdpDv06tXr5iYmJi44ODgnvLvNyYmJi41NVUTEhLSU75/TExM3COPPBJWtxym73Hnzp3jb7311m7Jycm1YxhVVlayKVOmhIWFhcWHh4fH33TTTZEnT56sbVPCGOs/bdq02p6qL730UtC8efM62fSLb6ds+gvFOf+FMbYLwDUAbgIwA0APAG83eCEh7YVpMHZ4E9Dv4frnyAFdM6oPbXW+hONgLjC6qzFLlFXWSPWnafss3vRhtN45JJYzfuFYMUSP0fs/lO4lAqzZnx/AvjMFiO3ohZjghmeLuFxu3nOTA7gUOhxbMi4A4HDTKFFV07yhvkyrSmXXd/PH1kNZSD5fiJ9PiAHMPVzMfz81egNmDu2GD6T2bTq99H5qpIybtUDdAVmbq7Ql1NTU4MEHHywCUNQazwOAUaNGFa5fv/58dna2MjY2Nv7BBx8sjIyMrGn8ypaXkJBQamnwYGvzcFo73/R3mJGRoRo3blzXoqIi5ZtvvplZ91zTXpZ1B/d94403Ap588smwLVu2nN2zZ4/b33//7fHxxx8f37Fjh4f87OLiYkXPnj3jxowZU9RQmerauXOn+/bt232OHDlyTKvV8qysLFVVVRWTh+WwNpjy+vXrfXv37l325Zdf+j/zzDN5AHD48OETgAjMk5KS3NevX3/e9Jpdu3alBQcHN/iN1PQ9/uijj3xvu+227ocPH07p1KmTbvbs2SGlpaWKs2fPHlWpVHj77bf9R48eHXn06NFjSqUSGo2Gf//9975ZWVnZjT3HUdiUcWOM/QxgL4D7AKQCuIZzHtOSBSPkihgMQI1JwFNVIkb/B4DyAsvXtELg9vB2jtm7OPLLjZ8fjQZupq/jCufcTMsxGbw7SAyxkV8qgrEdxxqfA/pyRf2/oVq1Cjd2Fxktb60alXYM3Dxc1HBRKfBbai4OXhC1iO71AjeO/p19MfHazgAAnUHK+Mm/b127+LvfYvLz85URERHxhw4dcgGAUaNGdVm+fHkHAHBzc+s7bdq00Li4uNjrrrsuOjMzUwUAKSkpLkOGDInq0aNHbP/+/bsfOHDAFQDGjh0bMXXq1NCBAwdGP/7446ErVqzwnzhxYjggsim33XZbt/j4+Nj4+PjYn376yR0QGZFx48ZFDBgwoHtoaGjP1157rTZT9u677/pHR0fHde/ePW7MmDFdGrqPqY4dO+rDw8OrLly4oG7s2WPGjOly7bXXRnfu3Dleft2mUlNTNf379+8eFxcXGxcXFytnh8aMGdPl008/9ZHPGz16dJeNGzd62+e3YpuQkBDd6tWr09euXRtoMDQtUz1//vzcc+fOuWzdutXzySefDH/77bfPu7i4mH2YeHl5GXr27FmemprapDF/MjIy1H5+fjqtVssBIDg4WBcREdHof6Qvv/zSb9myZReys7PVZ8+ebYH2CcC0adMKhwwZUvTxxx/7lZSUKDZt2tRh5cqVF+S5XefMmZPv5uam37JlixcAKJVKPnHixNzFixcHNXhjB2JrVelhANUA4gH0AhDPGGv5GaQJkRVliPkybfXLf4BFHYGKIkCvE+OyBUpT0OmszDwit4NjLRe4FUqPSMkzBm7ZjWbcTBrWV13Z+KVHTopqTkOXm4AB01BUUQMfN/H5mnTO6tR/teQOAd0CjH9rtWolxvcPw6K74uHvrkG1zmA+LIcNiipqsHxHmtm+mI6eUDBWrw2bh8b899M3XPztHdhVjBVaW1UrV5UarM5F7XCqqqoUplVdH330ka+/v7/+zTffPD9p0qQuH374oe/ly5dV8+fPzwOAiooKRb9+/cqPHTt2/Prrry957rnnOgHA1KlTO7///vvnU1JSji9duvTizJkzw+VnnD592nXv3r1pH330kVn9+WOPPRY2b968S0ePHj3+zTffnJ4xY0aEfOzUqVOuu3btStu/f//xZcuWdZInXl+2bFnwrl270lJTU4+tWrXqfGP3kZ08eVJTVVWlGDhwYEVj1xw/fly7c+fOk/v27TuxdOnSTunp6WYBQ6dOnXS7d+9OO3bs2PEvvvjizFNPPRUOANOmTcuVJ3nPz89XJicne4wfP95qdlGelzUmJiZuwYIFtdXHK1euDJL3Dxw4MNrS+TExMXEpKSkWg6e4uLhqg8GAjIyMJn3wKJVKvP/+++ceeuihbl27dq0cMWJEvTk4s7OzlQcOHHDv06dPRVPKNGbMmOLMzExNRERE/EMPPRT+3XffNTpf3KlTp9R5eXnqm266qXz06NGF69at82vsGgAYOnRotFweW6vHVbKeRgAAIABJREFU+/btW37ixAnXY8eOuQQHB1f7+fmZRb19+vQpP3r0aG116jPPPJPz9ddf++Xn59tpPKW2ZWtV6VMAwBjzADAZwFoAHQE0beROQpqjLA94Mw64Zjowcqlt1/z5nlim7wFC+gHggIf0mVBhJUCRex62YBu3DlqguBrYccH4nSmnsU6Yphm3k9uB/pOaNB2XigE6KY7SQkSOF7o9gM5qLXr/+7va8/LqzjxggVxV2i3AA6dzywAALioFFAqGIG9X+LppcDy7BAXl1ejgYfvHg9kwHpLHbugKjUoBjUph1v7N102NF+6IxaLvjwMA+oSKwE0tdV64VCT9HuWq0qYE/O2ctarSu+++u3jTpk2+zz77bOfk5OQUeb9CocDUqVMLAGDKlCn599xzT2RRUZHiwIEDHuPGjasdIVme3B0A7rnnnkI5e2Fq7969XidPnqz9wl5aWqosLCxUAMCtt956WavVcq1Wq/Pz86u5ePGiavv27V6jRo0qlKungoKC9I3dZ+vWrb6RkZGe6enprsuXL093c3PjjV0zYsSIyx4eHtzDw0N33XXXFe/evdt9wIABtd/Oqqur2aOPPtr52LFjWoVCgXPnzrkAwMiRI0vnzp3bOSMjQ7Vx40bfkSNHFqrV1pNE9qoqtaS5c4YPGjSoIioqqmLWrFlmE6HLE8crFAo+Z86c7ISEhMpt27apbS2Tt7e34ejRo8d+/PFHz59//tlz0qRJ3V566aWLs2fPzrd2zbp16/xGjx5dCAAPP/xwwaOPPhqxcOHCRtP4tlSV1iW/XwaDAYyxem9e3ffTz8/PMG7cuPzXX389UKvVOvz8d7b2Kp0FYAiA/gDOAVgD0cuUkJaXkSyW6b/bdn5umjF7VlkIHNgg1msDNysd96qkL9sqV8vH7eCs9IgNacb/evkVjfTs1NUZyqIsH/CwvbF9kBuQIWIsuEIEXhdr3KEpMo8Yz+WXIyWzCD06GWuLiitFb05XtfiiKmfc/N2N48nJ46gBQHyIN3afysOhi5cxLKbhmomTl0qgUirQpYM7Mi/Xj17lTFuXDu44cN74O/PSqqEy6WGqkM5TSD1kf0vLRW5JFQLkqtJmtAt0NHq9Hmlpaa4uLi6GvLw8Vbdu3SxGq4wx6PV6eHp66qy1lfPw8LD4h41zjqSkpOMeHh71/lCaVtEplUrodDrGObf6R9XafeQ2bjt37nQfO3Zs1N13310UHh6ua+gaVqdndN3tRYsWBQUGBtYkJiaeNRgM0Gq1/eVj48ePz1+9erVfYmKi35o1a9Itve6WduzYMY1SqURISEiz2l8pFAooleaJpKYEjdaoVKraacp69epVsWHDBv+GArfExES/vLw89ddff+0HADk5OeojR4649OzZ0+6NTA8ePOjWv3//8h49elRlZma6FBYWKnx9fWv/3R4+fNjtvvvuM/uG/q9//etSv3794u6///48e5entdn6tV0L4P8AxHDOh3HOX+Gc/9KC5SLEKPOgWHoG23b+e9cY1ytLgH3vi3W1h+hdejEJSN9b/7pKKapS278VQG4Fx30/GGDpe3V+VSOBW902eZkHgG+fFJPE26BSb3yqCxN/z8+XMExdl1S7X6NSoLRKh5Er9phVc/Za+BNGvG38jiaP4RboZcymyUEdAAR6iv1nc8oaLNOOY5cw/M3fcdOy31BWpavtMQoAL46MwYQBYdCoxMeTr5v5oMNqpQKuanHMx01dG7CZOnThsrGN2xW2C7TKI1CHootqu/14BDa74fSrr74aFB0dXblu3bozjz76aERVlfhHZTAYsHbtWl8A+OSTT/wHDBhQ4ufnZwgNDa1es2aNr3zOn3/+2eg/+sGDBxcvWbKktirrjz/+aPCa22+/vfjbb7/1y87OVgLApUuXlLbe55Zbbim755578pcsWRLU2DU//PCDT3l5OcvOzlbu27fPc/DgwWb/+IqKipTBwcE1UtWiv2kPzhkzZuStWrUqCAASEhJafbC/zMxM1bRp0zpPnjw5R9HEAatb0qFDh1yOHDlS+5/8wIED2tDQUKttDg4dOuRSXl6uzMnJOZyRkXEkIyPjyKxZs7LXr19vU3VpU3zyySc+u3fv9p4yZUqBl5eX4d57782bOXNmmE4n/vu8++67/i4uLobhw4ebVR0HBQXpR40aVfjZZ5/VawfpaGytKl3KGBsM4GEAaxljAQA8OOdnW7R0hABizDGgeWOrVeQDXYYCqd8Dwb3EaPoFp4FP7gBezDWf+/Po12Kpsf+klrd+w2vbt5nyUetRUK2AzmCAyuSDe8sZjlvCAHc1E6+fKYHhrwA/vQgkrxEn7V8NhA0EXKz26EeljiO/kiHETYeMclVtxi29hCFNmlaqe5AnQn21tb02q3QGsyza2bwy/Hk6D9d164DC8mowBrNqUK3aWG55/7HsYpzILkZMR8u9VFMyjU2Jvth/oTaTBwChPm6I8Dc2qRnbLwReripsPig63WlUCqgUCsy6sVu9jgq3xAZi5/EcVOn04ncN2G/su7raYMw1uY2bvH3zzTcXzZgxI2/Dhg0dkpOTj/v6+hq++uqrkueeey74zTffzNRqtYaUlBRtjx49Onp6euq//vrrMwDw+eefn5k2bVrnJUuWBOt0Onb33XcXXHfddQ1W2n/44YcXpk6dGh4dHR2n1+vZwIEDSwYNGnTe2vkJCQmV8+fPzxoyZEiMQqHg8fHx5YmJiem23ufll1/OTkhIiHvttdeyGrqmb9++ZcOGDYvKzMzUPP3001kRERE1qamptf+x586dmzN27Nhumzdv9h08eHCJaVVZWFiYrlu3bpWjRo1q9u9y5cqVQZs2bfKXt7ds2XIKMLYnk/cvWLAga/LkyYXy71Cn0zGlUsnvu+++/JdffrnxnkF2YK1Mdc8rLi5Wzp49O7y4uFipVCp5RERE1bp1685Zu++6dev877jjDrP73H///YUTJkzounTp0qyGyjR06NBoOWiNjY0t/+abb9LrniO/xxUVFYro6OiK7du3p3bq1EkHAO+8807GzJkzQ7t27RpfWVmp8PPz0yUlJR23FAi/8MIL2evWrWuBsYFaF7Olbp0x9jKABADdOefRjLFOAL7knF/f0gVsSEJCAk9KSmr8ROLYNj8B/D975x0eWVnv8c85Z3p63WST7X3ZBktZelnpCIp6xauoV8FrwauiKIp6UREUEQtiQdALCgIKKtKld5Zt7C67y/ae7KZOkulzznv/eGfmnGkpS7IlvJ/nyTNnTpszySTnm1/5/lb+GSacBP/1yMD7X5vTGNa4QEbTzroOHr8agjvl+i+tgp7dMG6RHM+UPu4934e66QwnE/9YuKyi0Z+kJeLi3rMtFo2VImRjt+DMv8vfy23/pct6vb1r4Owb4B+fzT7B2ddDdeGxwb9bLfjL24JtvTChJMH2kJv/Nv7FN91/4XON9/PYViloPn78BPqiSR5cIeePrv3+2QQ8LiJxk1nffTxzvo0/PJfP/XkZq3cH+da5s/jSfSuZVl/KN87JbjC/7C77d/L5q05jQk2+EL712U385Im3C1737y9dmJfuAvjCPcup8Lv54fvmFNwOsKWtj+sfW8917zuCj82vhB9PgOnnwXk3QmWeRVRRNE1bJoQ42rnuzTff3DZ//vzDKs0SCASODIfDKw72dYwUV1555djS0lKzUI3ZYOjt7dVnz549e+XKletqampGf059lLNjxw7XWWedNf2yyy7b97Wvfe2w+l3N5c0336ydP3/+xELbBhubfT9wIRACEELsAYr/m69QDCdpHzNzP7sDW1bK9KdugL/SXv/W3+GP58Krv4Lunfb6qvH55xgmZpZlh91OrpfZmSW77fUxR4AoYVpSdHpKobRAzVjUjlxFk9n/hN2wVIo2gJip8bW5YZp9smZ7XSr7WuIxOGFKDWU+O3KVngua26wQjCR4ZXMH46sD+D0GN148j8+cPCnvki6Ya6e0H3ozz5oKALdRWHhduKCxqCj75SVH8q1zZxbdDlBX5kXXYPl2Z6p09DQnKIaPf/zjH2XTp08/4vLLL9+nRNvoYPz48cn169evPdxF20AMtn0uLoQQ6UJTTdOGP5ekUOTyxDVQPcXuqhzMnNFiVKcERuUEaF0tl5/6X/m48h7493fksr9q2JsTwgkphOq8Sb45L8SWcJJ7NrpYXB9ibr3B/dvBcBTbf+VFW4CZlsAdDYK3HMbMzjs3MTmX86Et0h/u0hmCH5yQ//+YhuCkMUkaQxHie1xsC0p1ePYRDbh0PSvl2B2OU+Zz05Yj3NbsDhKOmzRW+NA1jerSwgPvL5w/lodXy+zIT5/cwLT6Us6ZY4u5vliS6x/Nn5z38eMncMq04lkMQ9co9fVvDVXmc1MV8LCzKyzT4LrrXS3cRnO0DeDmm28u/J/BIHjf+97X+773vW+1c90DDzxQfs011zQ7140bNy6WNp4dSQ7Ga7e2thqnnXbajNz1zz333NsNDQ1KzB6iDFa43a9p2u+ASk3TLgc+Bdw+cpelUCAjYQCTT5ePkU45/slVWDAA0njXWyatPZw3bF+qRnb2RbD+4exj2qStBLobTvzK8Fy7g7Tdx4XjwlT4XRzpN1lQnUTTXPSkXBhCCRkx8xiw0VFtYwkho2oVzVBWYPJQQoqrdZ1S7P3pbfj2sVZeVOqM+hCg4zL7CGl2/djcZpke9jsaDK57ZB2/u/Ro2nuzhdtn/yS7ewOe/v9s6LrGuUc08NhbrQDc9MTbWcLtvjd2FjxuftPweJ/6PYZj7FVgOO1ALMuyNF3X98+7QXHI45xU8G547YaGBvNATeJQDB7LsjSgqG3JoFKlQoibgL8BDwAzgO8KIX45LFeoUBTCebPd8qy93DtAKUvPbmlSO/siKHeMo3OnomjeMpiyuPCxZ/1w2GvbTEvw3n/J+3yZy77fp4WVz5DrQgl4778E5/8z+3dVCEtG1QKp2ud0uvT0a1IvIMVV3HHYrStNenO0ynkT5A6ueC9hXQq3cVV+Gsrl92VmQ1nGVDctetIRt/SIqWhSnsPnGtjD8uKjmjLLsZyh82Wp8znTsyBtPoaDgNvInlc6fBG3NW1tbRWpP6oKhUIx7FiWpbW1tVUAa4rtM2inUSHEv4F/A2iaZmia9lEhxN3v/DIVigKEipQoPH4VfOTefo5L+VD6KuD8m+H+j8vaOGf6c8oZsPnp7ON0FwSqBn15KY+qfvcJJwS/XS3oTZXm1Xni5HpWpxsy79yYXp99TisWljNFAzVZ62lcIB+3PAfTzyEYs8XU2o4kHRH7V/v8xl4CqYiaJ9ZO1CUjWy5Dz5jWaprG1efM5It/WUG6X6k9deFXnD6VHz2+npoSDx2heFbHaTE0TeP7Fx7Bdx96izJvtiCLJqWo+vDR47j9pa1ZxwwHAY+L1p6o/Bl5SmSUdhhIJpOXtba23t7a2jqHwdcHKxQKxVCwgDXJZPKyYjv0K9w0TSsHvgA0AQ8hhdsXgKuAlYASboqRIZ7jA+arhGg3vP0Y3NAM39ghO0FzSXueeVLpwHRDQ8BhJ+QUcRXj7C7TQU4jCCUEC/8iuOYYwaWzih9z4b8EmxwDdKbX5EeUimkVQxPMYxNlj6Tq8LypNOKl/2DzU7dzxxsergcZYdzxKsHYSZljy1yCNx26d3qFiabr6Mko/nALbVXHQDD/tTVNoyLgpi/VHdHeF6PEY9BY4cPj0mXaFjkpYTCMrfTTVOljXUsPHX0xalJWIb1Ref6p9QNO0dkv/B6DaMIkaQnc3rL9b2rJYeHChfuQTVoKhUJx0BjoL/CfkKnR1cBlwJPAh4CLhBAXjfC1Kd6t7H0Lfr0oe93UxTD2KLkc64XuIpZC4ZSxd9rbLDVIHb9DuLkdwm3iKfLRShYUbnvDghVt2SVNK9ogasJ3XoP7NxYvd3KKthllsUx0K5f/PTLfrLbEJfiC6x/2irS33JjZLF69mHtXO2aW9u2lJw4NfimIqv1w1Uv2dXk0mao0kvJ1ApX11JV6OHFKThQPOcA9Ldx6owl8HgOXruExdEIxGSkbrHADuHTRBASw8LqnOPq6f2NaImMD4jzPMAXbAFmvF02asjvWWw7JGBS0PlYoFIrDj4H+Ak8WQnxSCPE74CNIL7cLhBArR/7SFO9anrkuvy4pUAunfh0WfUE+7y3STJa2x/CmjF9PuQrO/hGUOLoVXQ6j9rRJKxQUbhf+S/D+h4W05UjR4fBX//pLYsCB6s3+BN+amzf/OcP0ivzmranGPso0hx+qNzs6ZaGzY+G35JPeVoJxqPPKa4wmbRW0sCrClAq5fsyuJwDwl1byw/fP5eQCHZylHhehWBIhBOG4iceQc0jdhkY89T3wDEG4Ta0vywyxb++Lc83f7SY+p5D92LHDZ8Hi9xjEEhbxpJkSbtGRm56gUCgUB5iBatwyd08hhKlp2lYhRG9/BygU7xhfge5CI9VJ6k/Voa24GyYU8H+OSnuMjNBxeaF6YvY+xew+CoR99qZGVe/rS9JUIa+hK2cwTtISePTsY9siUswdVRXlG/MiePsZXl3igk9Pj3DHBltQPsiV2f9WeUo45+cvZEQQwKapn6Rh73NoHdvpiQsmBSw0BHdvlinJsxrDfP6IJODB37ed2lY569UVDxYcEwUy4rajK0zSEkQSJm5DQ9c0uhyTDYYScQMZAetO/Sm519FR6jF0PnPyZLa093Hy9OEzMw94DAQQjCQp95bKiJsSbgqFYpQw0F/g+Zqm9aS+eoF56WVN03oOxAUq3oX4KvPX+VNirj7lZRbJm9IiifWA4c4TZ9Gk4K51QqbPdB1mvx8W/pc9eH7MEbJBoQjtETuq1hXLjrCt78zv2u5JlVUdXZPA6x64mP+94xPcf2o3Lk2gFegCX7JPZ31rL69tseeWdkcSPLHdYkePSTAm06uO6VO4NPs8M1beYF9/3bFFr6PEaxCJmyRMi0jcxKXr6Bo0V9qi0juIrlInhbzZTpxSg65rHDupmkuOGV9USO4PgVTzREcolrIDiY/c2CuFQqE4wPQr3IQQhhCiPPVVJoRwOZYLDyFUKN4puR2UADXT5KOuy8aDZIHBnyCFmys1JcHBr1cLvvua4O51qcjR/A/D9LOhYS6c9k04/oqCqdJ0IK0raou1SI4G+NfG/GtJz0z3ugZfW+Vx6/gMQQ35Qe0fvJA/SvGNbZ30CT+lWoRQUiPgsnA7LMZiZr4YSrhK6a4/rug1lHhcxJIWoVhSpkpdOpqm8Z/H2anMYrV6xThz9hi+dW72WKx5zcPj2VaIspRJ796emBTwVkJ25ioUCsUoQLW0Kw49ko5cZEk9zP2wTHmmcfnsaQq5xHrldi1buLWlUp7fXeJiT5+gN+4QVI3z7RRsDq6U9gk5Mm3hHOFWX5IvkEKpfbz60ASD14Aj9Y2Z57tFDb9Ivp+1YkLevn9ZspMwPgJI4VjiElR67PfVl5C/3uWddl2ZbsUR/XTPpico3PfGTta29GREWqljssL+BMfKHBMPjhhbzpHjB2+9MlTK/fJa23qj8nNjJkCoVKlCoRgdDNrHTaE4YKSF29Sz4Mj/BD1nUoLLC+0bQIhsFdHTAmsekFMGcqxCnGM8T/hreoB7/wokYYmMsW1ryN43nNM3YYl8IZQWd76hZRXxGoLmZFvmeZUrwc9iH8rap6HcR3tfjKQlCOGlTIvgIknAsJhUarI7LF80fe2V7csyx+pWAtFPSrgklWa86ckN8npc+cLNpQ9duZWnzHYn1gT40MLmYU2N5pL2jdvXm464JVWNm0KhGDWoiJvi0CMZlenQBZfIG2+uX1vPbgi3w9uPZ69/7Cr52NuSl/YsNNPctPqPhl3ziq32frDMjWUJLCEI5tiCxcz8dGg6neob4nSkBdUmlZptDxIws0tJqwJuvnPBLOrLZAQyLGQt36/ct+A3BJVe+/X+Y6LsZLUcwldD9OtX55xZCnKiAkCpY8qBUWRAfH943Qa3fWwhV509g+aqwMAHvAN8qUK/vmjSjtQmo/0coVAoFIcPSrgpDj0SEdlgUOzjWZ4ap9TqmA+9/hFY9y+5XCC6UsixIzmAjcf9G7Of7+xNcsljgqdzRm3GCgRz0pYhZUOc4vSp6VE+UfJa5vmOhrMBqEiNg7KEbA5IpK59k1c2a5ykr6bOm8xE+N47to9ZtVK0WIYt3AT9i66A1w4RTqoNcOLUWoBMhKwq4MZVyPh4EOi6NuTGhv0hPXe1N5q0m1SK1UQqFArFYYYSbopDj3AnuEsKT0YA2UwAkIzYM01f/oW9Xc9XS6EEjA1kK6xwvLhwS08JcHLqgwZLUqNS3brgTyd3Z86dy5agkI0GvqFF3GatvpHKmO1RF244hhs/MJcvLZ4KQDIVJewOy7Bf75hjsYTGk9bRTC7X8KZnnyY1/H07mLn0u2ip71FP1RFsnvPlfl+/xONMiepZjQi3fuRIvpnTZHAoIkd5adJIOB1xS6iIm0KhGB2oGjfFoUe4XRrjFhBggG2a+8bt8NLNcmyV4dh30efyT5nMT1t2xwTFsnbdjgDNyXURXmzzZ21PWnZK7v82ernyGItyry1ytgSh0S8NbIdCSe8WAGLeGryxDqIlTVSXeKnwe5haX8rcJtnMnQ4WzmuuYMPuZo4q6aDb5+I9YxM8t8fg2JooY3Y+hi+6D6MjjKl7WX7q/5F0l/X/+o5U6cZ92abBXrcxKGuTQwGfy6AnknBE3JRwUygUowMl3BSHHqE22eVZrIDd5QM0af0B9qzRNBNOyD9lAjw5HZ43LNO47T1FLiEVRfv01F5cLhcvtuXv43Jc3pI9cd4zyfaO2xyEcX4T137UgwFsnvsV9jadheWSytLQ5RB4kYoENlf52d4RZmyFn4baalyJXrqBKq/gVyeEEcKFGZbHuhN9xD2VCM0YcB5rwCHMJtSMbC3aSNJc7WdLewhROgatbib4C3gDKhQKxWGISpUqDj3CHfaQ+EJoOrj9+etdPjguP9oG0JcAnyH45aJezm2Uxf9P7tSzRlk5iaayqm5d4C3wW3JMdSRLV2539BBEk4LdfYJ6XxJ9PzowAQQ6prcSYWR31GqpF/3SGdO4dNEE6sq8mK4SdCuetY+uayTd9vfQNPxZTQrFcF7vp0+ctF/XPlJYluDW5zaxrmVg7++Gch/d4QTRCafDF16HyacegCtUKBSKkUcJN8WhRcdm6cXm7Ue4gXTEz6V2WsEbdFtEsLYTPDqMLxWc2mRv64oUEW6prlCPLvA4Uqy/XNjGH04K8sXZMvX2jdQM0o2OgfJbe2QTQKNv/y0oeqqO6Hd7ud/NqdPr8LkNTHcAvaDJrC3CTFcAUSz1XATneK1Dgb5YkhU7uvnpvzcQjBQoLHRQ6nURTZiEE2pigkKhGF0cNOGmaZqhadoKTdMeTj2fpGna65qmbdQ07T5N0wYODygOb2IFxt7ecpR8dBWIqDnxlMjHygn2GKz6wmLnR0ul8NrYKysDJpXZgqoz2n/EzaMLppSbNAeSfHVGJ+OrvFT7NMpS9hiL6uXx9272ZNKYW1IirjEwNOGmmzEEGq3N5xKqmjXo40xXAN2MgxBoZpyS4MbM+dIkPOWDds79wUVH8InjJxyQDtChEEvaP6tbntnYz57S8FcA7b3xfvdTKBSKw42DGXH7ErDO8fzHwM+EENOALuDTB+WqFAeGPSvhhmZY/bfC28ub+z8+Ldxqp8Hi78KH74aZ5xfctTm8Dj9RFlTKKJnXgI9NkZMXuou4RGQibho0BgS3LApxUlO+kNE0mFMpoz/dUYvndwse2CQFXFPJ0DpKvZF9aAh6K2YM6bh0qlQ3YzRt/RvTVv+UQHBTlnCLBcYO+nyNFX5OnlaHsZ9p3pEi7hBu2zrCmc7aQqQNg9t6VVOCQqEYXRwU4aZpWjNwPnB76rkGnAGk7+J3Au87GNemGGaEkH5rd5wNN06G534s17enIiav/zZ7/9rpUDcLxhefpwnYqVJvamSubmR3lqaJ9fKVzh9wq+cWPj7FvolPq0jZasQKi6tMxC1lr6HpGloRIbOoXqq8I+/V+MSTgmd2yfVl7v6FT1nXWlxxO8eaXo6Ujuv3uFySrgC6FWf6qhupbX0BgPKuNeiW/X6jvvxB74cb0WR2BPNrf1tVdN90RLQjpCJuCoVidHGwIm4/B74OpP+FrgG6hRDpgpRdQFOhAxWHGS/dDL89CXa+JpsOnrseXrwZ3KkOzHCHve/DX5GjrCrH5Q2JzyNtCeLt394ibbx6hr6CSo9dF1WaGv7eVSAgc/8GweVPy+3eQUSdytwFPN/qw3hcxX+9jESIKW/9kslv3UJJzyZc8SDulHAbSnQMUqlSK4Ev0ppZpwkTwxFxMwewATkccEbc0hTy2wN70sM/V+wpuF2hUCgOVw64cNM07QJgnxBimXN1gV0L/kXWNO0zmqYt1TRtaVtbAY8GxaHFjtfz1z39PXji23I50mWvX/oH+ThQmhSkQS/YEbdimHbEZdraWzPLpSmxVSji9oMl9rqAaxDpzgKf3omlZqYDtBC+8G55/tAupq26iRkrrssIt6h/zMCv6cB05TdqaJaZlSo1De+QznkoEk3k1wwWWgfQWC7/MWjtiYzoNSkUCsWB5mBE3E4ELtQ0bRtwLzJF+nOgUtO0tK9cM1DwX2UhxG1CiKOFEEfX1R3+6Z9RT7GIWPc2+WiZ8ssZOSmU8swlHXHzV/W7m3AYr5b2bs4sl7iKC7deR8NiuWdg4VbIqq1ygOOMHENYd6IXVyKIafgxPUOLjiVd+R241W1LKO3ZlHmu0f9c1sOBdHPC9y+0m1CeXLu34L4uQ+eIxnKCEdVVqlAoRhcHXLgJIb4phGgWQkwELgGeEUJ8FHgW+GBqt08A/zzQ16Z4B+xdC1tfyF+fyIl41M2EEofgjvXAU9+D71Vm7zMQE06Eqe+B8v7Tim+3F65xCriWTMJRAAAgAElEQVTkwPVg3FZdCUvwvdezBY7fNXCq9Li6fHFQ4e5fKOlmfo7WE+si6SoZlN+ak2QBoedKZk89iA4x/XookhZu88dX8p5Z9QBE4sU7d6tKPPREEySLePUpFArF4cih5OP2DeBKTdM2IWve7jjI16MYCr85Hu58L9984M1sU9u4Q0Ac9zk45etw/BXZx77imDM6/Vwobxz49crHwjGXDeiIv3afTBcmdS+m4UNLRbp0TaZBexxdpUta4Y9rs4/XB2Gh4S7wW1Q5QGbSsPLbWb2RvViGB6EPbaBJf2OsIoFGXjz/Wdqazx7SOQ9FeqMyFFrmcfGLS44EYPmOLkyrcHSzMuCmL5okFFNRN4VCMXo4qMJNCPGcEOKC1PIWIcSxQoipQogPCSGKGDUoDmX+8sYunns7VXu46WnY+ry9cdIpMsXZX3pziKJlIHakug92T7gIw4wy/7Uv4+3bjWbGqXVFCMYF4YTglRbBR5/IFwDF5tznklsLV+0ZIOJWYHamO9aF0F1yNNUQ6H/+qE6spAnrMK9xW76ji3+slNUTAZ+RmanaFU7wxFutBY+p9Esvtz1BZQmiUChGD2pWqWKYETy2uoUzZ4+BP18sV1VPhvmXgKYhhODZtjLOKHb4QN2kQyQUkanaSKXtjVaz7xUq25fzDEHeH/8DH3lc8GZ74eMH62R224m9dEVMvrhEilJfESuQut1P4451UL3vNSzdkzWqyrDiMk06wDzRXOK+2szy9mmfZM+kD1DWvZY5S76BGOK5DlXW7rHHXPlyjIF7ikxR8Hvkfl39+L0pFArF4cbo+KuuOGQIEOPBFbuJ9TpsPupnQ8M8AP62CT71nJd9vsmFTzDMQsNIhgGIlIzPrBNoeOJdGFiEEtmibV5FlNkV9o1+MKlSgFI3jCs3aPCb6AiM3OOERePWB2na+lfq9zyDKxmmt2IGXXXHZO021Po2gJi/IbO8Zc6XCFXOIFI6MbXm0DLR3V/ShrpA3vzXLR2hgsd4DPlZ6q8OTqFQKA43lHBTvHMsOy1YrcnIiFh+V2ZdRLgzflu7UyVvx3Zfh1XnGOuUHipfYkeP3ilCCDymFG7hUlu4VXTaxq0lZnfWMZ+d0csPj3ak1oaoe36xKMRtx3fjymk1LQ1uYMzuJ7PW9VVMY9Xxt/D2gm9lLED2J6UpdBc7pn6M9jEnY2WG0sufyWiJuDnFWlqQpdnSFmJLe1/uIRkfvbASbgqFYhQxOv6qKw4uUVv8NGvt/NT9G3zPXptZ963VDfxkaX7N1/Y26Vt2f+VlcO6P4ZjLofnYYbuscBJKiBDHTdJbyatnPgSAL7ovs89YM9t1ZkypO2ukZ39ebIXwGlBbYuQd54r35O2bdJeR8FWzc/onMV3Sl25/a9E2HPVdVp58W2aQfLhsEgBtY0/fr/MdDKIJk/Wt+d8ngIjDr82dEm5PXXlqZt0vns6fXZqJuBXxelMoFIrDESXcFLKJoHPL/h/vMNE9obydDxgvZm220Hh4qxRuTqf7n8UvJiZcfKf1JAjUwNTF4M33JNtfWsNQRpi47sPSXISqZiJyPvJNVktm+fr5bRiD7UYYIkYB+w8nVqopI+Gu2P8XcdQHJrzVPPXBdWyZe+X+n+8Ac+er27jpyQ28tSeYty2d7pzbVJ6ZoTq1vpTmSj+QbQOYJh1xU12lCoViNKGE27udFX+WTQS3nwn/dwFcWwFd24Z2DoflxwyxNW/zGjGJUpcUbmHHPfQh6wRmxO4ixtDrugbDliCUaxFM3Zux2Egb0ca81VhoTNPkYNHT6sPMrrOjXV+cFeKKqUU6FvYDp2/bktP/wubZX2TX1I9m1nkjshM3VD5l2F4T3TisuklbU92fP3sqP3oWSZjUlXq581PZM2xfulq2uYTjJu192Y3o6chcOKYibgqFYvSghNu7nX9+QT6GO2BbKlJ2/yeGdg6Hye44kZ16nBa9i82iiXVBN79bbRFOQqnLYkpp4U7A4eSlPYIKLYzmyvdGW7fwOnaWzuMS13PoWFwyMbvAfXGTyXsmDp+gdM4NTfhq2Drni0TKJmbWueMy3dxTOSv30HcF4XiSnV3Fx1NF4iZet065r3gj/LqW7DSr15VOlaqIm0KhGD0o4fZuxnSIp9J6ezk8xEiTQ7jNjq/OLN+fPJWEw3HmhqUQSUrPs7ObsoVbYhjd7X+81OLDj1oEY1Cl96G5fAgt+4ZvugLUxXYAcLHxInUlgxiz9Q5IR9zWL/h2VhdomtXH/4yeyln0Vc0e0etwkjStrO/7k2tb+cEja4knD2yEan1rD3e+uj1rXe7w+Eg8ic9t4DKK/8lqy4m4eTLCTU1OUCgUowcl3N7NRB0Rij7HzMfgLvjFfAh1Du48KeGWzPk4XZ28PG/XUAK8umBhbbZw+8rzw3dz/c1qeH0vuCLtzGELcW8V5DQLJN0lvDXvGgCmejox+hEEw4FhRkm4y2id+D4sly9v+75x57HkzL8TLWke0etw8s2/r+ZL963MPL9/6S62d4TZ0lbYXmOkuOnJDSzbbtdJGppGLCUeO0NxLrtrKVs7wlmWIE7uuVymT7vD2Z8pd8YOREXcFArF6EEJt3cjG/8Nv19sD3ovRNc2WH1fv6cxLcHvnt9MfNmfAUhiR61aRRVWgY9XOAkeQ1CVU3r18Pb9/yg+vVNw/4b86vRpURn92znlY3nbLMNHcNL5WOicXVXYeb8/jGQYIzl4gaObUSzd0/9UBE3PE5gjSVc4QTxp5Y2Mag8duKElnaF8c1xTCDr65Po/v2ZH4qbUlRQ8xwlTammq9BPOEWjprtKo6ipVKBSjCCXc3o0s+z/YvRSW3C6fpywkstKlAHGHMOlpyU6tAv9cuZsbHluHZ+MjAKwuPRGALTP/m1fnfI9JpfmRjpf2AELqk8/MiDCjTIqEGu/+31w//ZTg6y8LkpbFxm5bhFQnWkjgIlh/VN4xQneDbpDw1VKl5XuAAZT0bMIbLizqjnj968x97auDvkbDjGIZHix9ZFOy+0PuEPYD1YXZFY7z9t7egtuu/ddaovEkwaj9mXvPrDFFz1VV4iaU04Sg6xqGrqlUqUKhGFUo4fZuJJZKke58XT7Wz5SP3nIoqbP3e+Y62LdOirabZ8IjX8s6TXc4QR22dUNfzXxWH/cTeqrnManKw4+OCfOZafmiaHOfG03TOG9cgh8dG2VOZYKaAWZ75iKEIGZmR4riScHXXrTXeWKdtGtVWI5ZnquO/zm95dMwXQEAov4xBT3WAKatuolZy68tuE0XUtxo1uBEjm7GsHTvkOeQjhTOKFSuz1nCLDy0fbi56m+ruOOl/C7kNA+tamF7hzRQ/tDCZhb3I9xqSrwFjXY9hq4ibgqFYlShhNu7hb1vwS0LYfmf7EkHnZshUAuVE+RzdwDO+I7jIAG/XiRFG8CGR7NOGU2a1GuyNukB82T0irGY7rKMn5jXgPMm5Auyz0+xx2FpmkapG0JJDcsavGD46XLBjLsEvTH7/F1Ri15HULCObnq18qwxUvvGncfrZz1ELCAbBOK+WpnyFDnXKeybfdPme7M2jdnxcGY5PVJrIGTEzTvss1j3l/uX7swsRxImwtEMEEsevAjVd863u2qfXCvrLutKvXz7glmZZoNC1JR4CMWTeU0NHpd+UN+PQqFQDDdKuL1b+M0J0LEJHroCnFEibymUpFKkpXVSyBWjemrW01jCwoM817/M43F5/YO6lNPGZYuXUregJ6Gzsq24cFu2V/CLlXL749sFv0pNrXphp10jtTckaHVkd+u0ICG9LM8KxCmeTJcfXZhoOcJt2qqb7PO0PIeekAJNs5I0OoVbYnB1bnoyiuka3PfnnfL1B1ZlCbNCdDhqy2IJk7hD3Axnh+9QmNNUzgcXjstbn7AsKvz9W7NUl3gIx02SOdHCEo+R17SgUCgUhzNKuL0bSTpc/IUFk0+HE74Esz8Aug7Hfbbwcb5sV38zFuZIfZM8Ja78wepFcOUMCS91C3qTOhc/Cjt7CouGDzwq+NkKQXc0yWefsW/OLQ7d9OAWLWPwe2R1gjqtm4irrN/B9ZbhR7MSeRG3kt7sFJ6Rmnmq50xAGGyDgmFGMY2RF27tfTE6Q/FMtCqNyB0t4HgaSZjs6rYtXeIHSbidN6eRioCbjx43Pmv95SdPGvDYqhIP8aTFmj3BrJq98TUBdneHD5oYVSgUiuFGCbd3Iy22BQTxMLjcMOF4KKmW6yafVvi4nHqu92y+nu+6/wSA0I2iDZHH1smIx0XNIb4xq4P61ufwhu1RUyUuW0Wc/AB0RorfZBf8Jfsju9NRQvfnDXYkTRdJKrUQMVf/I6RMw4tuJTITFYrRsONhPNF25r6eXefnGmSqVDdjmEZgUPvuL/t6o1z9oO2jJ4SgtSfKZXct5fI/LcOy7PfoTCmu3dPLDY+tzzxPHIDU4tZ2W/BOqAnwmVMm8YGFTQD88P1zM+Lt6AlVfOH0aQOeryogI3K/fm4z9y/blVlf5nUTiVsqXapQKEYNxW3IFaMLwwtmAZuHRBHhUd4EPbvB5bMjdDnHN/SusZ9o+YPV01w1N0JPqJNZXc/S3nAGza/eh6W5WHXirwAoc2dHg17aGePC6YOLTu3qy3/NyyZ1EotFIQJJbwX9xQFNVzriVjhNGwk04Q/vpmbfa9Tsey1vuyuRP1czD2GiiwSme2SFW3tvtrXG5X9axolTajLPN+4LMaOhLCPo0jz2Vnbn7IFoTghGpJj/z2PH8fVzZlIZyE6Fpm1CZjeW5R1biMqAw4omaEcP/R6DuGkRTSSL+sApFArF4YSKuL0bECKr2B6AdN1XosiYoVO/Acf+N9Q7nPy3vgB9cqbmDx9ZS3vcYW2hG0UFkluHGT2vMHbHQ8x57Sq5u7Cjd56cT2F7JFs45BacA1wxtQOXJmgJ579qQwA+PFZe55i6/CkFWec2fBhWHM3K/v4ITWdv89m8fMGzJF3FBVfN3leYsvrmorYhABPX3QZA0j04EbK/RAtMPChzjIjqTPmzbWkP0RVOcPGRTXn7uw3tgKQV052e588dmyfaAEKpDtEx5flmxYVwvs+ow/7D75ZR2GBEmfAqFIrRgRJu7wZiPXlpTo65LLVQJLpSWg9TToeyHAuGm6ZCMs6ul+/FcKQXhWag9xPaSjcI6MIuFNeTUjSO8WcLhe6cwGBfgdryhXUCryFoj8qP8Il1UVyafC8uXRAwpcWHqMwvdneSrjvTLMeLWrJZIb1t66zP5x0X91SSdJVQ0ruVsuAGZi2/lklv/Sr/BYRJZeebgBxsP5L0RfPFSVufHYVLi6HXtsiu3kuPn5C3/7iqQJ4h70iQFm6lRWaPTqyRYnmwwm36mLLMbFJnd6nfkxJuqkFBoVCMEpRwezcQSY8TciirQC0EamDK4v6PnXcJzLwwe93DX+Y3nl8wS9+RWVXrs9D7UW5GTlE/gDsmB6sfUWXynfm9/PJYeZ0xM/s8uXrk45OCVPrdhJI6+1LC7f3jItx5ai+fmdrDjCoNd0IKt1hgbL9vL+kpB6AsuMG+1pSISwu37TMvxzSkgOiung/AprlfZeP8b2Sdq6JrjUy7OvBE7bFhpqf/ert3Sm/KONeZHnWOkkob625pC1Ed8DClvjTr+M+eMhmf2yA5BOG2rSPE/Ut35jc/9EMsabI71QxRbGj8t86bxc3/MZ8zZ/cfMU0zptzHmu+dzYePHkcoZmbE58SaAItn1uNxqz91CoVidKD+mr0bCKfEg7fcXuf2wUW3wsJP9nvo/23wcLO4JHvlyrvz9htfYhascXNHO5nw9h14I3vzthmmnaZdWCdoLJXRkXASHtwkuOYVi39sFty0PFsU1PlBK9CZWuKC8yaC3+PKmOrG/DnTIHKIp6JgEzbeKTtLhWDamz8GwEzPFNU0eiull92+pvfw3IWv0jrhIkLlU/LOl2sr4onZwq3Q/sNJXzSJx9D50QfnZa2vL5PzxdK1a+G4ycTaAOU+N7Ma7c/EhQua8Lr1IaVKr3tkHU+u3UtrMF+YF+PWZzfz7NsylV1SpO7M5za4+KhmKgKDnzThNnTqy72E4kniqXRpc1WA02fWZ5oXFAqF4nBHCbd3A5GUeDAcN8m0KDH6vzFe+7rgl29C+zm/6ddWo8pT2J1+zK7HqWp7g5q9r+SNe0qnStO4dXBpgnASrnxRcPfb8OUXBPdvzD5nnSc/JVgTyL42dzxI0vBjugvPt0xjGXYqTk9GqN73Kr6UyDRddkRq/VHXEiqbRLDmKJK+GiyXj+7ahbx19PWESic6Tph9bWN2ynFgy0/+A131i/q9lndKMJKgxGtQU+Lhz58+LrM+PbMzmeoqDceTGcF016eO5epzZ7LkW4uZ2VCGzzW0iFuaB1bsGninFGtbpKjWNPC6hteQuKbEgxDQE1WpUYVCMTpRwm2Us2Z3kBdXpZRP2J5YkBFu/eC8gX/qhVL48N3gyp4O/7C5iBsT/4HlLZwG1B2dqFkCh8LpU58hMl5suRiaYF5FlClV2Tf77xzRhjslTjQzTnnHKjnU3fANOBu0Y8yJmLp8T/Ne/yrjN96V2ZZ0iL6+qtm8es7jBOuOtg/WdFomf5CWSRfb15gjRtMp2N7KmflGwMPM+tYeGip8uA2dk6bVsmCc/JkYhoauyZ+nEIJIwsx0WNaVefnsqVOoL/eh6xpet45piYINIbk491m5M8ifXtue6RYtRswxfkqDfqch7A81pfJn+drWzgH2VCgUisMTJdxGMcFIggtueYmTV12dv3EQwu01R6Pkqk5DhkiSUohdHLuWX5VfyRcTV/Br8314PAXOJwTVba9nnvZWyQ7VqE+mL10FzGtLXILOaOFaua/MCvLdo6IZkZZmQb0bT6SNsVv/RvOWe5m87tdUty3BHQ8itAHEkm6w5YgrCm4SuaJP0yhkVrdt5mfYOPerqffkMJZLpU27aheS8I1sYwLIbsqmSn/m+3PP5YsYW+Hjgwub8bh0kqYgHDexBFT6Cwtar0sKt8GUrOXOAH1+QxtPvFW8uxagrc8W8o0V/mEXbunu0kdWtwywp0KhUByeKGOjUUpHX4yF1z1FVtfokZfCij+BZgxKuHXkOIUkTQtX00LYvYx1YjzzyxKIffLG6y/wSXIlsoe375z6UTbNuwp3rJvjn7wAb2Rf3jETyyxebytcj+RG4DLsaNuNx4TY2RVF111MWvdb/OHdmegZIE11+0nvZt5XkaaBxGCbCTSdSKns0HTOLnUlegHorZg1qOt4pyQtK0sIBTwuXr76DCwBt7+4laRpZSJiYyoK//wDHhexpIUlBMUNXiShWH563LQEvdEEsaRFbak3b3tXqrvz4iObeO/8Roz+WpH3g/HVI+uVp1AoFAcbJdxGKUtT3YQNOFJGE0+CiadCoi+73q0I0dR9eUJJku0hF3tDFg3H/w+L724ngo8Ktx09KSzcpHBpbT6XrbM+R6hiGugGcV8dkZJmKjpWsGfixXLMVgrnbfzKWUFmVVqsCnr56xYPzSUmYAu36RUm0yvcGIk+/OHdgN0RmkZoA9dQFZohuuKk2+iqP3bAY9OkPdqcUUR3XJrzRgONgz7P/mAJQW80iSXya8Y0TcPQZCQtaYmMcGssItwqA27C8SSmJXAP8K0Lx/Nz2qZlceuzm9nU1setHzkSb85JYimvuffOH8vpM/tvHNkfJteVMrOhLC8aqFAoFKMFlSodpaQ9vabpUtC8OvHzctaorxTKBmexkLbhOK1BiqGtQYs+y8M2IYVIpdu+OZa68nNrJT1bAGhvPJVQ1Ux7uLumsWvyh/HGOnDHu7KOuXiiLbyaAxZ1JQaLxya59fg+xpYXTu/5Q7uLv4lBzk8FiPrH8MIFL/D6ex6ko/EUrH6Md3NJeqRwc9a4eaKypjBakm90O5w8s34fX/2r9IrzGIV/peOmxZ5gJDP6qViXZXXAQzRhDUr4hOP5+8RNwaY2mS7e0Zk/lSM9zD7gGd6mBCfjqgNEExbWAfCjUygUigONEm6jlEjqxjtGk8JoLzX97V6QdMRtXmUCQxM8sk3Q45iqVOFxOtTnC6Sq1IiodBrRSTpClVvMP6XcPueYgH3jNQy96Egt3cw+h0jF7Ux9cBYQMb80Ge6qPZZ4oIHe6jlDTm0mPJXyOh0Rt7LutZi6J2MlMhIIIXjozT2Z58VqxrrDCfZ0R4kmpBr3FQmnVZXI71nPAE0GII1ugaxRUs7mg4SVbyuStiQp9vrDQYXfTTRhYg7BW06hUCgOF5RwO9DsWwfP3zjiL5OOmEzXpE3DXjG04vhndgpuWCpvfA0BiyllJivaYI2jMbXaq9HoNykhQnVwbd453PEgwao59FTPzdtmpdKTek5nqeHQZr5BFq67EtlNDitOuo2Xz36MZaf9aVDHd9UvYuWJv2Hj/K8NvHMR0uLP7ajr80baiPnqiZY07/d5B+LhVS1Zka9i37KKVDPCri4pcr1FDGmr08JtEHYa4VSN268/elRm3R6Hn1trMH82bjpVWuIdWeEWSZgkD8DMVYVCoTjQKOE2EgR3w84lhbfd/h549ofQtaPw9mEinRL7L/eTACzvKe9v9zw+9ZQj2qVpNJVYrA+6+dyzcv1Vs7qpCLj5+aIQT4/9LdPX30rV3lezzmGYURKeCoSRH/lKz//M6sLMob9JDE584exUaahiKpGKKfTUHjmo4wHamxYTfwe1aJYhC/Hr9jybsUBxx7tIFnn/w8Xbe3upcpjU7ssZNJ/m55csAKA9NQLLXyziFkgLt4Fne6YjbuOr/cxskBHUFodwu2dJ/mc8HXHzu0euvLbC7yaWtDIiUaFQKEYTSriNBL8/He44ExI5PmVCQDwlVPryOyoHTcub8MQ19OfZEImb1GlB3CLBauMInt3ryxq+3R9d0ezzahpMKbOPrXCbLKiVz70GVERlqm7Cxjsp7Xwrs59uRjFdhQ1wzZRwm7zut3nbrp7bx9Wz2oumRnPxh3YRdkS1hlKbNhJMXPsbyjpXYyTDJDwjO1g+YVqZ9CYUj5Sl05m90f5TpXWpKQub9hUX1GmCkQRuQ6PM5+bR/zmJhROq8vbJHYW1ald36vVH7k9POrrYF1OD5RUKxehDCbeRoC813qllZfb6tf+0l0WBm0qofXDnv+00ePVX0LE5b9PzG9r4yG2v0RKM8KznSgD2lc0mbmk8ud0c1ADxJTnTqQxdY2alfb3fntuTNaoo7qvNLE9dewsIgWYl0IWZEWi5CGf9mWUyfcX11O98DIBFYywWNXmYtPbXNG8cIN0pLLyRvcR9deyYeinhkuYBTXdHmvLgeqasvRV3ojdr+sJIEE9aeAydK06fCsC5cwo3nqSFWzpKVkw4Ta0vpanSz57ugUdYdYUSVPo9+D0Guq4XjOJFc6JeaR83l34AhNsgooYKhUJxuKGE20iQtpf4w9l2VEwI+Osn7H2SOSmt3lb4yRR48jsDnz89D7OA0Pvl0xt5dUsH/1y5h1JN1jO53fJG9j8vGvx+dfH00b93CB7dJvjvZ2xxN600jsvQ8TvuyXX+bPFnJENZjQDjN/yR8s5VAMRTRfu5dNXKCQSm4cNIhgmEdjB2+z+z9qnoXEXt3pcx4tl+cJ7IPir3LWHBS59l4vrf44kHCdYsYMNR3+G1cx7DdI+sWCrGksX3I3J+pZIDjNx6p8RN6d32tbNnsOX687jkmPEF90sLt3SNm6+fUVNHjq+kKxzHtAQ/f2oDj60pbGbbE5UjttIWJF88YyrTx5Ty1bOmZfZp68muc/MaBgvGVVBeyD9mmEifO1TArkShUCgOd5RwGwmcdhuRlN1FLFt8kFNQT6e0zmDZHwf/OgVGRhmp9GLSEryiLwSgp94e0/T09sI3s/WdgsufFnw+VcNW6rL4/PRevjhTXnfAYfdR5tEJ9G5l6qqfUL/zcdyxLnorZ2W2V7ctYdL63yPQ2Dvu3MLXrhvsmPZJDDPK3CVXZVanh9FPePuOzLopa35pHycEs5d9l4kb/gBAZccKEu5ytk//NGDXmh0MemoW0Drhgqx1uV2zw00iKTKdpLquFa0LLM0Z5p47fcJJVcBDNGHSG0mwZk8PDyzfTSxp0h3O/mcjnrTwuoyMie5xk2t4/EuncNp025/Nma40LUFbX4yAxzXoNPj+kI649aqIm0KhGIUo4TYSlI+1l9M3qO5UobYv5cb/l0sgaNs4sCNV2J870SCZ05nnrBlqXZP30mkLhAY6OMFaRqh0In6fbTD7RoeHHy+16EtkR83e7s4+zzVzujlrvGB8pYykpYVbucvE0GH6mz+mtGczY7f/A2+sg0hJM2+ecEvWOUJlkwn1Y4VRKBpVu+cZjEQvVW1vZNYFwvYA87o9T+cdE/dWE/cN3e5ksOzpjnDHS1sH5W2W9m5L0zLugiJ7Dg8J08I7iO7bykB2+tgwiguncr+LSMKkK2ILtZ888TZf+9uqjDfaY2ta2N4Zzptpqusac5sr+ehxMvIXTdq1kf9eK0X5+tbeAa/3nVBXKn+H1NgrhUIxGlHCbSRwiq2eVpnS/Pf/yueTT7e3veIQOs9eLx89jjTf24/BdfX2NpBdqWmevCbrZaMJk2WpiQk/dv8ekGOnSj3ZN+nfrIb/fTm7iD2cU9M+NkdTeQ341NQwX5vVRUlPfm1d55gT8urZIqXjMrYfhdCELYTWHXUtAHUtz1PRnl0bGAnYQrg65Q3nJOkutc19R4DfvbCFV7d0sK6lZ8B9dcsWO101R9I+/pys7c+s3zfgPM/BkjAtemPJQdWLaZrGQ184MfO8mFEvQLnPjSWk91uabR3STLcvluDxNa08sFx28jq7SJ1cME/+zJy+bp2heOocIxsJG18T4KjxlaqzVKFQjEqUcBsJEo702G8Wydq1zU9D8zEww3Ej3/qsfBQCrNTNTJh2VO3Fn8rH538MsT5ZF7d7qX38mCOyXnanw4ez3x0AACAASURBVKn+eF12d8b8DXgNuHVRDzceZYfV3nA0tb6wW/DNV+zIybhAAn+BKM6FE5PMG+PJjLJyEiqfkmdamyhS35a53mkfzyyHS8fTVy5roxp2Piy3T/5P9jadKcWQZeLv24k/ZEffumplKjjpHprVyVBJC403tnUNsCesW/g9OuuOY/vUj7Nx/jfytt+zZAd/XbYrY4T7Tkh3fg426zhvnP3z6E+41aRmjN76XL5AbwnG+Nty+2eQLGCyC/ZkhJgj4pZO6Z40tbbgMcPJiVNriSRMEubgOqkVCoXicEEJt5EgkT/qB5CzQn2VcNYPoXEB9OyRYizmEEKmFClAdvNBqA3C2Wk4cuZw9joiGR1U0EIduyZ/GICmUphQYf+4e+JaJu31vdez0103HxfC049dgyshBcOKk36fWddXOZuu2mPY22wL00jJuKLnANmN2jL+vQCYhp83T/w1AFZqUHz72NOI++vxxDpxJfrwxOT739e4mBfPfxbLkCmxaMr8djgRQvDFv6zgR4+vz8z3XLKtkweW76KjL99YNk24fCrLT/8TG4/6Nj21RxXdr9CA9qGStv74z2MLNyQU4qmvnMIf/+vofj3yjp9SPO28ozO7NjNRxOQ2bbDr3J4Wed8+f1bBY4aTyoAHIVRnqUKhGH0ccOGmado4TdOe1TRtnaZpb2ma9qXU+mpN0/6tadrG1GO+KdQhTNK0+L+Xt9IVikOyiJVCuqarZor8igbh4S/BjxwCJxmzo28RR4QnEoRwSsgd9Umonw2tq+3o3ENfZMbfZBr1nCMaCBBlqT6HeMAWNV4D3j9eXlvU1EikhJvTIeSKqR39Fq6DbZrbVz6F9oaT2T79k1guH8LwsPoEu5GgZeJF/Z4HYO0xN7D01Dvpq55DLCCbOnzRfZi6h1DZJLrqjkUTFoHezRlj2x3TP06spIlg9XwAOsecNODrDJVXNncQSZh5fmaPrWnln44RU/uLs/Zrf0kX3zdXFU9H5zJ1TBmnz+hf6NaV5jd4pAv+71u6K2v90QW82wD8HtkM4UxVdobi1JV6GVNeeMD9cJI2JVYNCgqFYrRxMCJuSeCrQohZwCLgC5qmzQauBp4WQkwDnk49PzxIxvjBg29w7b/WcsszG7NTpU7cjhtsQ2oM1Mp77HUl9TIlmo66RYNQmrrJRtrtZgRfOfgrAYFo3yTXLb+Lkh65PG1MKQEtzvTSfBf9T0yP819TI0QtnZ09UjzscmiTxRMGtmkwEn2YuhfLXcLKU+5g07yvZ21ffuof2TXxg8R9dQOeSxgeusccj2V4sXRPZs5owltNPNBAJGWs64734Y5JIZu2+9g6+/O8vviv7Bt39oCvM1SWbO0suq2tt3jEbbAMptFhILZ3hPG7DWrLhreT1jnvtKbEw+prz+LrZ8/I28/n0vnlRwpPpwi48yNuLcEolQF30akNw0l6AkSvMuFVKBSjjAMu3IQQLUKI5anlXmAd0ARcBNyZ2u1O4H0H+tqGTF8b/HweXFfP9946iwv1l2UxdrGIm7NjtG5mdqMCSBsRKyFToi0rAQGlKWuRcCcs/QO4A1Azlc4qOcLoJ4+8meVOX08XVV4NN8nM3MlcZldJ0bC0NS0e5PGTS+ID2zQIQVX7MiyXL2N0K/Rssdc55kTWH3t9v40JBdE0zNQxpuHF0lwkvDKiY5hhxm7/BwDJ1DQGYXjorZk/bCOlHli+ixU7pDh0phJnN2bX0LX3xYrWduUSd0TWdnXZKfQ3d3YX2n1ItAYjNFX5qA6M3Egtv8fA7zYo9dk/42svnA1IgVcsehbwpmvc5GcsFEvSEowyq7Fs0KPM3gmVKuKmUChGKQe1xk3TtInAkcDrwBghRAtIcQfUFz/yEKF1FXRvzzz9pedWvrn2vVK4jT+elqpj+H7iUnt/d46QGbsg+3nVJPm4ZwW0bZDL6chc62rYtQSajoaSWq5fJTs4X3p7D1c/uDpziiW+LzAzsgwAs8gEgTqfFGq7+wRxU5CwNE4bE+Fb8wYec1TSswl3PIg7HsTSh18wpOvWLMMPukHcW4ulubB67W4K8x14tQkh2NoeYmdXOM+X7LE1rdz63GZ+/Ph6Vu8OMrOhjMYKH19cPJXV/3sWP3z/HJoq/XSHE0TiA0fMtneE+Pw9y3lhQxuxpMm1/1qb2fbomnfeWdoTTVLuc+MaILW9P1x55nQAXLqGoWtZI7JmjJFjvIrVt4FsfjA0LbNPukmhoWLk06TO19nSPvBnWqFQKA4nDppw0zStFHgA+LIQYmCfBfu4z2iatlTTtKVtbW0jd4GDoGXTyrx1pUkZSRH+ao5v+QpdwmHv4YgMhROCH73tGGruq4TmlFFuy0q7YSHtCfdKqnbMVw6azraIjDo1ap3c98bOrGs44bXPArYZbU3LC5lJBgDlHoGhCW55y8OCe+SNtTlgUlsycJo0XWfWMu58xAiMlkq4pShIe7xZLh+9VUfgDm51XMT+v+6SrZ388NF1fO9fa/na31bx2pYOTEtkRS03puraPrSwiRe/fjpnz26gzO/mo8dN4DOnTEYwuCHsO1NTCh5/q5WuXL8VIPEOrCqEEPRGk1T6R2a8V9obztA1NE2j3Ge/TlOqpm5ibfGZsJqm4fcYma7OeOox4Bm5iQlOGiv8jK8O0BUqPLtVoVAoDlcOinDTNM2NFG13CyEeTK3eq2laY2p7I1BwCrsQ4jYhxNFCiKPr6gauoRpJGl/7Ppaw0z4fjX8zs/xSm/yPP4IjOuSwy3hgE/x2ZzM3Vv4vXPRrOP+nUJHqDox0wap75XJpTiF5Ki0ZL59AUARYrC8nnerMJemuYM5rX2Xc5nuYvPbXmUYGXQOvLpfDKf3hMwaeYQqgW/JG2DrhosH7UAyBhFd2NMa9dmdjr6eWMaZtphr39x+MNS3Btg67+1EIkalL29Ke3RV5+0tb+cPLW0kWmOEa8LhwGXpWai+dguuvszRznako077eWMH9O3PE3PrWHl7b0pG3XyFufXYzcdMasUL/dJ1behKHc0RVmdfNA587np/9x4KCx6bxewxiSYukaXH9o+uA4sPtR4LGCp8ae6VQKEYdB6OrVAPuANYJIW52bHoISA/z/ATwz9xjDxlW/DljnvuaNYuJ0XuYGL2Hl625vO4/FYC2mLzRTXSWRzmEWyR1P9nhngCBavCUgMsj9+neCbtluhNfOUw70z5HSri1JXy8ZU3kP1zPc7P7NwUvM+kO4EraQsUdte1FvDn3zxLXYIWbTC+aQ61fGyQJj5ws4bT4eM7RyHhd4qP9Hi+E4O7Xt3PdI+tY19JDazDK9x9eyzf/vpp1LT1ZvmJpXt/amTGHdVJXli+KxlbK9/3qAALLsgT3L7Ujoc9vsKPDsxrLUteafd03PbmB21/aSmgQBfUrd8nI7pT6kZnLmp4/6kv5sVU4InuGobFwQjUzG/v3zwu4ZcStJRglnEotBw6gcKsp9RCOmVnRVIVCoTjcORgRtxOBS4EzNE1bmfo6D/gRcKamaRuBM1PPD03++QV48ttYaCwV07M2JVLf0jaqGBswaSxzpLIcwi2aypK9HXRx6RMWcVPICJY7AMGd2ccc/enM099vljf9voRgoS7r4C42Xspsj3lsewahZaelAn07MsuenAhbo39wkQktLdyMwsLtzV3dXHbX0kFFpAqxee6XaWs8jZaJdm9KEHuMw73m6ezpLj7/841tXbywUQrUn/57A9/+55pMyvLu13dgFoisATz3dnba/QcXHcHJ0/ONYtP2F29s68Lqp0FhfWtvVhRv+Q67GWFWSvD8/OkNtAblta1wNCvs6y3S3OLA59Yp8RpcfFTTgPvuD+mIW7pZpcrRANGfea+TgNdg1a4g33vYru0ryf2PYQSZ2VBOe19sUN9PhUKhOFw4GF2lLwkhNCHEPCHEgtTXo0KIDiHEYiHEtNRjcT+GQwQdgZ4zaukf/g/A9HN5zXUsPl3IKFqarIibvKlv7HHx4h64662kFG++cuiQth5vjL+Ma97IjvqsDgbojVv0JjSien6NkemyRU7jDjmBoLtGGsE6xzHtjWRf97hBBm6q9y1JvU7h+qaXN0nRdNuLW1i9OzjkkUN9lbN48+Tb6KuWTRlJy6JP2K/Vh581e4JFj2/tKX6Tbu2JZkXK7v/vRfZ1b5bX/f4jm5hWX8rRE6oyUScnzq7b9gJRujR7goXF5aP/cxLHTJTir70vzp2vyuaWNbvt9xSOm+zt532E40miCYtFk2uoLhleK5A0C1JTFqbVyQ9GiWNIvWuQXaEBd34924GqcQM4Z04DAtiwVzUoKBSK0YOanPAO8Rpapl4M4IXOCn7t/jghfHh1C81pVeG46Udz9Mx1ywx+uSIJY223/c9tWMjdGzR299rRsDhu5t4tl++o/J/M+mdMWW8U98kokaW5CIRkhG3rLNmsoFnFo2rOG3N/lPZsBIp3dqbHJW1uC/GLpzdyz+s72Ny2/zfOnkiSPqR4FYYX0Pr1URtK2d3CCdXUpTzQNKRn2bUXzuaJL5/Sbxrw5Gnye5zox0T33pyGkTQzGsop8dpR2HDCJJ60sgTnH17exjX/WENbkUjRuhbZuFLIKHe4mFpfyvNXncY1F9hTDhorfMxuLBt0F2uh6FrDATDfTTOuSgr+QulxhUKhOFxRwu0dYmkG40ttFbYvanDjMsGSval0ZJGIW6GmxBd3WVCbSr16y2lH1nvdvsYWhjHsm36b2x6+flPyP/iW/hX2TLqYrtqjiflqMA0fq467OTORYNzmuwu+h3kV+5FK0goLvVc3Z9d+vby5gxseW88vnt5YNE3ZH8FIgpCQN3utpIZKv5tQP1Yc0YSJoWn4+hnZBXD1OTMxdC1TYB+Km5T73ZT73OipTspivDc9QH0QguDxL5+cWf7gUU0YupZVc7W7K8INj61jw96+jNBJj9j6+8rCExraU2noT5wwccDXfydMqCnJSpG++s3F3P/ZEwZ9fKF/BibVlRTYc2Twewx8Ln1YzI4VCoXiUEEJt/2hZlpm0UecKk9hQTKlNI5eJOLWUyDL9maXm/tDR8KcD2DOOJ8AUS4zHuH+9fbOceTN8PT6Ps4fb9E67nwAdolafGOmEvfXY7r8+CN76a45kn3jz8vYgmiAEZcpuQa/hY7gz6d08435xWvGcjENL+1jTsyIwVz6ihTWr94d5MWNQ7dv6Q7H6UnXuFVPoTuSYMnWTv69tpXrH12XmbeaJpqw8Hl0/vjJY/o976dPlp55cdO+qbcGowMbECMFgXyt4oLA59Y5fUYdMxvKuf+/j+fiI5v4znuPAGSK1Em6Bm9iTbaoKTS9IWlZ/HWZ7NY4kNGrNKWDjMxCflr0w0c3ZzU5HAiqSz30RFRnqUKhGD0cuIKT0YRjMkIJEfxFOjIvHBfHnRoEH9TKU/EzSTB1755eFuP6oyM8tcfDb98O8PVXDVa6a7jeuI2l3gcJaDHqNbtwPSK8nN0Y5rOzTTTNRev4C+gYcwK3GzG0VL1dbeuLQKoOTdMxdTullk6X/ur4PiJxk1KPnc7atWsbZ+35LZbho6PhZMJlEwiVT0WzkghNp7J9GYYZk5Yd/Qic8dUBfG49U1t03KRqXt/aydqWHk6bMTRf5V1dEV605tG26FvULTif2cEu1rb0ZGZmbu8MManWLtDrjSYIuF1ZvmMAi2fW8/R622EmbXNxzMRqJteWsKU9RGSQkZlAWrj1E3FLmCJTI3fspGqOnVSd2XbU+MqCx1x+8mS+fJ/tDeh3GwghMmLSsgRX3LMis93tOrT/7zJzmjdOnVE/KGE8nBw7sZqn1+/rN62tUCgUhxOH9l/+QxEzARE7EuInhqdAo1yzP4HfrVPi93Gf94N8KPZdkpbFj5ZafOwJi5f2wJSyBN+eH8Jl6JwzLsnVc6V1R50l040BTabEjtPXZc67W9Qyp8IRGdI0Er4aPG63HA4v7BtUR4NM01mOejTDlKLTpUNTaA3VrS8DsKVHZ/nG3Xji3fgirTRt/SvTVt1E06a/MP+VK5iy5udMfPsOABKewsIjHf2a31zBk185lbs+dSwXzG3ktx9byNETqgpabgzE9s4w5aWleE69Ehrm8NAVJ2aJoJ89tTGzHI4nWb6jm+oSDzWpcV+nzajj1avP4MYPzss6b9qbrczn5qkrpYWL2xhk0X16gHoRoZe0LExLZKw0cjlyfBVvfe9sDEeRf3WJJ+t9AUQSJn9bbnuhhOLJrE7VwTYJHCzS0ddTptVy8VFNLBhfMcARw09jpZ9QLEkkoaJuCoVidKAibsUId8K2l2DiSdJnLc19l0Lc9kbzE2NxY4KN3RrvH9dHOKFx1njZfZjuOH2z5jw2BH0EIxa/XW1r5TqvSbljBuSiMSb31XTT/vo+IpYHvyaFznx9S2afM8bGOaq2+Kgpb0RGlbZP/Ti7J38YIGs0lWHahf2T10n/t/9v787joyyvho//zqyZ7CsJJOxrAsgqWBdQEAW1KlTrrrVudWl96ttafat1q1rb+mr18bG1rrVWS6lVrLbVhwKtdUUFEQTZISwhQFayzHa9f9x3ZkkmLGqSiXO+n08+mbnumbmvuTM6h2s5p7ZwEje814fLnR1HJYp2LQUgq+6zSFtrWsc0GQAt9g7SLPs9TRtRxLQRVpLkgkwPy7bUsHjNbk4Ydeijblv3NVGW5yPDDoJcTgej+2VHphGb/CEaWwNket0sXGGtCXMIlOT6eO17x1KY5aVPu3xs7Qd9HA7hV+eOxxziGry2JLwrt9dR3jeb3Ha1QgP2jmHfAUbEMryuuDV/WWkuirPTuPToQTz11mYq+mazemc9/1hVxTcmlOFwSIe1fe4uKHX1ZWrr3zHDCrlq+tAe6UN+uoewQadLlVJfGcn9f/7u1rZovGEX/HwwzL8IXrzSavvjhfCnS+GzvwHQkjOM96ngNfcsRuWGeOCoJqaXOZkz2IGzXbb9tthsT3N8YNAQ6Dhi4nU5yAvuZbUZyFoGxh1r8RZxTnkaGWmdx9tpzVYNzLrCCWAHjrHF3h2hjjsys2usWqfpRI/tLe58EXpLRr/E7QEr8Eu0KD3T3kn53HtbaT7EbPaNLUH27fczpDAjbifjkYPiR6Y279lPQ0uADHsk7KxJZQBU9MuJC9rOtttvnj2qw7nOGF/KmRPLDqlfbQv239tcw00vroxLmLt1bxPV9uYB70E2SFw1bUjkttOuCXrraRW8fO0xPHrhRCYOyMXlkMgmiKaY63bKmJK4EbtkdPvpozl9XF9mVRQf/MFdpC3IPlDqFqWU6k1SOnDbtGd/dAH44nvhF8Pgw2dhQTThLevfgFAQPn0FVr0YaX5tXwnXyI+pTrOCqwOt3fHZyW4/2hPffnJJQ8cHmzDj3NvYbIr5juun+GOmJVsz+sbtTE3EY1dH2J8d3UBhHC5WTrWKVOTueT/S3pJmjXyVbP0rpzneZkh6E0Hj4MYBL7B+zA2dnqOm6KiE7W1Jd4uzOqapGJAfzcXWdAgF2iFanWDCgLy49vZTig8uWs/3568gbAfeXx+XOLD8xdnjWHf3HK78gqM/eRnR9XPBsOGJ/1h1VPc2tnLnq6u50044e7DyTjefUs698+x8dXYtT4dDGNc/l4EFGcwsLyYYNqzZZZXybStsf/bkMu46c8wXeg/doTg7jYfOm8iQoq6p7nAoJg7M43szhlNRktVjfVBKqS9TSk+VXv37D1izq4GPvjOAvKV2oYaF11m/XT4I2rstX7467nmrwgO5M3ARtQHBlXPw6bW2OqA3vW19kV8wqIHyvDCjcttdfmPwNu8mI9xAc/YQZlUMp3VdCR6/tTkhNoFuZzwtewk5PLT64kc5GvKsfFyFVW+RWb+RDaO/S1qLNa2a1lzFf3sehgAgsGG/j5A7JjgxDlwSnUYNehJ/EbflIhtT2nEt07UnDGVDdQMLV+w84KL+WO9u2kum18UJo+Jr0hZ2kr/slY+teqaeA0xRfhnTi16Xk1kVxbyxugqAjyvrCITC1LXE1x49f8qAg75WWwmtRMFs2zT6I0s2cOup5exvtR5zxrh+kXx56sCGFmVyw0kjDv5ApZTqJVJ2xM0Yw5pdDYAh7+ljOz7AmwWz7rJufzw/+jxxcqr/Xmqx/gVfcgilotrnIQ2FDWMKpEMi04Jd/6b8w9sB+NrAHKYMzmfnwLmAta7METxwvjUJ+SnauRhn2N+hlmhT9lD8djmstOZdFK95ptPXqW0J0RSOBgbzQ8fHHTeOxGvsXllhBU5l+R2rKricDo4dZgVgnS3qByvFxrLN1ihoTVOA0f2yGZDfMffXi1cfzV1njGZUgpGU7phC/O3Fk/nm5OjU6jsb97Jqe33cYxLVOm2v3O7/qJKOCX/7x1zH7bXNkV2vbdN/SimlUk9KBm7BUJj/WbIBgDLZ0/kDC4d3aGrKs9ZHnVbaxF3jajhj4MGn/fr44keYmoOJA4u86vcit0NO60t/68hLWXzm+zTmjMIRDsRXJm/H0xp9L8bR8ct9++CzCNuJcwsbrc0GVe74dV2LfSdR3xpicaWhyuSyKH0O4Zm3UekexMPBMzmLX9Ac6tj/qvoW9jVZI4JZ3sSBxaHkP1vwQSW//tdGVmyrockfjGx0aG/iwDwu+tqgSN3PWI5uSjlxz9yxPHHJZACeeXsLL6+IJsw9eXRJ5P0eSJ/sNJb84PjIlGms6SOK+PWFViWNZn8ossYt19f55hSllFJfbSkZuD37zhZ+8Y+1AOSwP/GDvPZIzuz4Wvfzd1uBTnFaiLFFzgNOy7XpnxGmIifA5LwmALLdiUfpJCaVR9gZHa0JeXIIudKRcCAu3UeCVwCgLm9MwjxrG8b9kMVzP4zcbzRpXBC+i3mttwNQmV7O0lG3Ud0Y4LkPdzO19REaZ9zLhSeMJ+P697g/+E2WtZTy6NINHV67tsmaJsxNd3d6TXz2mq/2CWjjXseuGvDw4g0EQuagCVuL2yWhPX1cX1yHmNbji3I5HYxNMC0MkHYYOdYGFWbEja61ERHG97dGSRv9Qfa3WlUhurNQu1JKqeSSkoHbQ4us3F/nHtkfH9Hpx+eCM/l5n/tg/AXWD0DeoMjxteEyfh86EQC389DLNzkF7jmymZvHB7htXD1zBnR8roQDZDRE034E2011hpxppLXsprjyb3HtWxsdnL8ki/tWpPHcOusLfVPJ7E77YlxpLMk4BYB3wuVUhzP50IzgktCt1B53GyW50fM6HQ5GD7BSf+RlernbXhC/akd9XFF0gIZWK+C6b97YTkeaBhRYwclnVQk2Zdg87aaPixJsdIhVnG0dT3M7WPrD43novIkJi8N3lcyYEcEZMWlOvqzkuH2yvOT43OyobaE5ECLN7cDdje9PKaVUckm5wM0fDFPTFGBEcSb983yRJLdntf6EHwcvo8ZZCOVfh+KKDs+d67+TDaYUABeHFrgV7lhM3u53AXA6hQlFkJ4gXUbJ1r/G3Teu+JGkrNpVAPTZ/r9x06WLd7ppCgpvV3tYscf6cz60AmqaOh/V2mOszQU7TCF1zQEyPE5u/M4VjJpyMn1zoue958wxDOsTXUN2wVED+d5Ma/r4wUXrCITCvPLxDpr8wUierL658QFnrBHFWeSmu1m1s57Lf7eMtbvqOzymfZLe08b27fT1IFr2qSDDy8CC7quD2cYXs3P01xdO4nK7lFYg9OVk6nc4hKFFmezb76fJH8TncSZ94l2llFJdJ+UCt9pmKzAYWZyF1+XEZ+cu248VcARMgi9Fe9q0CS/zBrRNdx54bZvLX4+vYQtlG//IwM+eirRvaXRw5v9ms2pv/Hnc/vgRrJAjPnBLb9wKQNjhhpigcWVNNAh0YwVPQZw8uqTjdCZYtT8fq5nE/PAJ/C40C4CcdDdD+2Ticjo4qSJagzTRzsUbZkV36L25fg8vL9/BbQtXsW+/H6dDKMk58IL82qYADS1WP//0QWWHAGfv/mguuSPKchh+kDQOxfb5DlZUvquICE4Rpo0oxONyMKvc2s07vM+XlwKjb04ajS1Btu5rwuVwaOCmlFIpLKXSgVQ3tPKjBR8DkO9q5ojqf1MlVkqM64dV8931AwglCNxaZ97N919aDwhnlDUzb5Afb8yUXnWL8M8dbuYN8hMMw4iNv6Ng91sJ+/CnTVYw9NetTkYXRNe6NafH5x5zBeKnE1dNuY+x79xAyOkDY2gLdzY1OBicGWRTows3VjAZwMXGPfvZXtNMaV78CNjK7XV8Zvpzo/+KSNuUQfl47am92GnOsvzEo2ffPmYwT/5nEyu2WWlKapoCbKtpItfn7lBYvL1Txpbw2korSfDmvU1c/Zy15m6Ivc6rpilAXrqb8r7ZPHjO+INOex5RmsPcCaUMKez+0bY26++ZE0nCO3VIAStvO6nDjuEvoizPx6srrYA21+dO+sS7Simluk5KjbjNX7aNxWuryfA6uWjnz5iy8if82P0HALLSPbgcsHSXm7veixkFCvlpdOfzWvgoTi7ZT1aai0yPIy4f2C0fZPD6xlYu+qeXq5dI4qDN3lRQ02p96TaH4y+9tJt63Z8Tn3uqasBp7Op/KmJCvLrNw7xF2Szb7SBkhJPKgqy7GNxiBQ8BYwU7n+yIH8WDaKLg754wLNJ23PDChAmE+2YnDtxOrLDWcn26KxpcrtpRT1GWl/SDJJ29Z27H3ZMAG/fsZ+ln1QDMGVPCs5dNpU/2wdNpuJwOHjhnPN+d2XEHcHcRETJjitpn+dyHtKP0UB01pCBy+8wJ/bq9ULtSSqnkkVKBW5M/iAj85ORhlLZEi5Pv6HMcGbnFuB2Gfa0OnlgVU15owbfJWHoHAP0zw3GlrNrsaxU+SLuaNWmXMsWxBoBQh1xnVmDmt2PC5TVpfFYr7GsV/rLZg9+u87llxKVsGnUlDfmjO5wn5PIhJshv11mjS3+vtEa3+mYIbqcDlz1VetQARBbNOwAAEsxJREFU63hzgrQbDXaS2HmTSpk3sZR0j7NDZYK7zxzD9TOHdZqKY3x/q5pDqF1tz/On9k94fWLlpnu47NjBcW2xpZ8AThnbV0eVYkweFP37nD25fw/2RCmlVE9LqalSfzCM2+ng6NW34WveSUP2CLaOuIRAmjWiEbtMqr7V8OaqdZwUDpJWawV53gQ7SUNhrPxqtp+4nwXgjcA4Zjuj5aXEhDHiZGJwBde43+W54AxuXBatmZnvcnG9CzaPujLSn/bCDg+OcHR69aMaL0VSzynO5cDxeOzALTfdg9flSLhBYcveJrJ9LvLSPdx/9jhuPa2C7LT4lBsXHDWww/NipXtc+NzODoHh2ZMOXikA4MenlDN7TAm3vPQJa3c1cGJFMaNKsvj+/BUACZPqprKsmL/PwXbZKqWU+mpLqcAtEDK4HEJWg1Vbsqr/7LggaXqxnxe3pjHH8S4vvbSRGpPJSW6oNdYIltdhaMuV1ub9PS6Od6yI3C8Qa/qw0hTGn9wYJBzkvvD94IQjZAMz/fdztnMJd7ue4D/hMYRxYqTzKbaw04vEBG4G4SHfY/T5+EMoLmVO/yBUwbzxJTxX7aNmf6DDa2yvbaY010dWmhsRiRRMP1zLbjmRH/9lJVMH5/P66qpDTjgL1k7JIwfls/C6Y/hkex1jSnMiu0MBTXeRwNeGFFBZ00TGQdYQKqWU+mpLqW+B1mAYp0NwB+qoyxtLY158yo9vDa3nvt1XRnZnbjdWUBfECiSy3B0Dt+c2eJkr26w7fcfj27kcgPV22pA2jlALrlBz5L5gKKSOX7gfA+AE5woC4mFnQ4DHFn1KbZOfq6YNZVjM7sSw04sz3MqJjg9YHB5PCCdfC9sJdde+xtyCYqiC/OwsBuR7WfpZNeFwGIfDGkoMG0N1Qyuj+2V/4anIDK+LB8+dAMB5Uw88QtcZr8vJpIFWwfh+MWlE3N2UQLc3ee7yqTS0BslIkEpGKaVU6kipNW7+YJhBUkVGU2WHWp4A/Ta9GAnaAEplLwCFUs+3PIsZmt0xN9cxxQH6yR78rkzIjgZrn4bjpw3LP7yT8g9ui9wf4tjFM574qgx+XKzZ3cKmPfupaQrwyJL1ccebM6yqDY977udnvufiO7L1bVj9knXbkxGpOLB+t1UZIhgOU7mvmWDYMCBBlv6e5nQIPzx5JNecMLRbE+j2Fg6HHLSKhFJKqa++lArcTKCZm3kCgIbccrxNO+MKt2fXfNLhOZ/KUABud/yW4hZrirWmVVi6yxr5MEY41vkJjtz+MHQmAFWeAQRzBjOy5WneC48EwBVsjLzmT4t+CcBoxxZqnfm0jrsEAF+4mYbW6LqxhpZgZDMBQF3BxMjtE10fsfaCBLnkHG4oHM6F9jq13Q3W+/vRn1dy56urARhYkHyBG8C1JwzjxpNH6cYEpZRSqhMpFbhdtOMujjbL2V08Dbe/jvIP72DoJw+CMWTUfYandR/VJdN56+RXCbqsdW3ppWP406A7AajcvY+wgUv/ncUDn6SzrzlMMBSiTPYQLhgOUy6DH22h+P+8xf2XTKcVD1f6b6DBREf3loVHsDP7CP6SczEAGcOPxTvlWwA4xPDiSqtQfFvajOV2rjSA5szojsK8QBXeN27q+CaPOBu8WfSxF7F/uquBbfuaqGuOBoAnVhR/0UuplFJKqR6QUgtmCv072EUBQU8uZVusacWMxs3027SAPjsWAVBTdCRNOcN5Z9bLlGxdSHW/E6jaYa1Nq9+zHVf+DiAbgL+vb+LKhvsBMGlWigx81u80tzVFWUsWU1of4WHPI5zo+IBFoYnkZaUz96KHCe66Bnd2CaTHp+MAmD7C2twwf1klxw0vAqw1br8qvIMhVX/j6853oH57xzfpi18ztnZXA+9u2hc5fFJFMf1yOi9LpZRSSqnklVIjbhmhWioppmzbQvyePN6c8wYA3r1WHdDqkuPZPux8AFqyBrB59HXszxvN/JVWTc254deZvuZO/ui5EwdhvlHzOCPDVmmpcNmUuHOlxSSibSaNBaU38aHvaP4QmsE0OxBzlZRHgraN5yzmrNafAPDst4+MBF7NgRCN9nTpKx/v4IHK4dzpuBYTu0Zv+Mlw9dvWVO248wDwuBxMH1FEbcxI26SBeVw9fYgmcFVKKaV6qZQZcauubyEnVEeeMwfCsG74Zbyx08dAU4ynpYUcgc395vDgv3eyr8nPD2aNJN3jRESo9nsgJon/VMcaymULU+1kuzNaf8mr486PO1/75LWZeX2YeNXfWBYKJ6w1WTZ8PMvMTgCOHlYUF1xV1beQmebm5eU7ABjUtwg56014YhY074OQH4or4KIX416zICOa6uOxiyZx0ugSlFJKKdV7pUzgVpThYvP468le/yrB1gx+WTeDxeu3cr7HTT+7XukrW9ys2G6VifrBghUEQoYTRhbRjJdHgqdzrWth5PX+mPsoNMOC0DQ2mn60H8TK8Lo4fVw/XE7hpIpiyu2ksu5Oalh6XA5uObWcptZgZHH+7V+v4PZXVrN0XTWFWdFi6recOgoK8+CKRfDQBBh0XMLX7JsbjTYnDsj9HFdNKaWUUskkZQI3nC5yj7sK76fPgDEsXm8t+k9PT8fZYlVEWNcYHaEKhKy2xWurAWF+9rf5rLaMm93P08fdQmZzJQAPBecyID8dT4KA7KHzJhAMhQ+54Pjlx8WXfvrWMYO5929reGvDPt7aYK1Tu3r6UMb1t9fE5Q+BW/dG6qC2N9EuZTV1cH5cLU2llFJK9U4ptcZNWurw+fdSZ6x0GJMH5VFaGN0YsKbew/CYhLexLj9uCC+Hj+WinKcJl58ZaX/smlP57cWTO63ReahBW2fGluVEbhdkeCJpPiKcLnAlrn4wY1QfXr7uGB67eFLcmjullFJK9U4pM+JmjGH+64u5Ariz5ZsAXHP8UBzvRRf51xsfx/XNYt1uK+faH66YypNvbiY/w81Zk0opzU2jX24arrTBsPJ5GH8Bo0qLwNF18e9vLpzE957/iP9s2EtZno+CzEOvVSkijCvTKVKllFLqqyJlArc9jX527bSmN1eYodx48kiOHloI71rTjE3GSwgnE/rnsXCFtUmgODuNxy+ZHHmNGeVt+c9y4LZaMKZLgzaAgkwv939zPDfMX843jyzr0nMppZRSKrmlTOBWlOXlR0e64S344ezRzDluqDW9aedfS5dWAI4cnB95TnbaAS6PCB12JHSRkpw0/nDFUd1yLqWUUkolr9RZ4+bfj+et/wfphZw6pTy6Jm32vQDsyx/PPV8fwfDi6Bo3j1PXhSmllFIqeaTMiBueDBg9z9qJ6c2OtueUwe115AdbOd9lrR/L8bkJG4PXnTpxrVJKKaWSX+oEbgBnP9X5MVd00f+/bjye+uag7sRUSimlVFJJrcDtEOX4POT4EqfYUEoppZTqKToXqJRSSinVSyRV4CYis0VkrYisF5Gbero/SimllFLJJGkCNxFxAo8Ac4AK4DwRqejZXimllFJKJY+kCdyAKcB6Y8xGY4wfeAE4o4f7pJRSSimVNJIpcCsFtsXcr7Tb4ojIlSKyTESWVVdXd1vnlFJKKaV6WjIFbonKEJgODcY8ZoyZbIyZXFRU1A3dUkoppZRKDskUuFUC/WPulwE7eqgvSimllFJJJ5kCt/eB4SIyWEQ8wLnAwh7uk1JKKaVU0kiaBLzGmKCIXAf8A3ACTxpjVvVwt5RSSimlkkbSBG4AxpjXgNd6uh9KKaWUUslIjOmw/r/XEJFqYMthPq0Q2NMF3fmitF+HR/t1eLRfh2egMUZ3Pymlkk6vDtw+DxFZZoyZ3NP9aE/7dXi0X4dH+6WUUl8NybQ5QSmllFJKHYAGbkoppZRSvUQqBm6P9XQHOqH9Ojzar8Oj/VJKqa+AlFvjppRSSinVW6XiiJtSSimlVK+UMoGbiMwWkbUisl5Eburmcz8pIrtF5JOYtttFZLuILLd/Tok5drPdz7UicnIX9itNRN4TkRUiskpE7rDbB4vIuyKyTkT+aFeyQES89v319vFBXdU3+3xOEflIRP5q339aRDbFXLPxdruIyEN2vz4WkYld2KdcEVkgImtE5FMR+ZqI5IvIG/b1ekNE8rqzXyIyMuaaLBeRehH5ryT5jF0vIp/Yn6//stt69HoppVRvlhKBm4g4gUeAOUAFcJ6IVHRjF54GZidof8AYM97+eQ3A7te5wGj7Of9j978rtAIzjDHjgPHAbBE5CrjP7ttwoAa4zH78ZUCNMWYY8ID9uK50PfBpu7Yfxlyz5XbbHGC4/XMl8GgX9ulXwN+NMaOAcXb/bgIW2ddrkX2/2/pljFnbdk2ASUAT8Bf7cI99xkRkDHAFMAXrWp0mIsPp4eullFK9WUoEblhfHOuNMRuNMX7gBeCM7jq5MeZfwL5DfPgZwAvGmFZjzCZgPVb/u6JfxhjTaN912z8GmAEssNufAc6M6dsz9u0FwEwRka7om4iUAacCjx/Cw88Afme/n3eAXBHp2wV9ygamAU8AGGP8xpha4q9L++vV5f1qZyawwRhzoMTU3fUZKwfeMcY0GWOCwFJgLsl1vZRSqldJlcCtFNgWc7/Sbutp19lTQk+2TRfRzX21pyOXA7uBN4ANQK39Rdv+/JG+2cfrgIIu6tqDwI1AuF373fY1e0BEvO37laDPX6YhQDXwlD2F+7iIZADFxpidAPbvPt3cr1jnAs/H3O/Jz9gnwDQRKRCRdOAUoD/Jdb2UUqpXSZXALdGoUE9vp30UGIo1RbkTuN9u79a+GmNC9hRbGdaoS/kBzt8tfROR04DdxpgP2h26GRgFHAnkAz/qzn5h1fadCDxqjJkA7Cc6zZdIt/4t7bWIpwN/spt69DNmjPkUazr9DeDvwAogeICnJON/p0oplVRSJXCrxPqXfpsyYEcP9QUAY0yVHTSFgd8Snarqkb7aU35LgKOwpqhcCc4f6Zt9PIdDnwI+HMcAp4vIZqxp7Rki8ntjzE57Gq0VeIruv2aVQKUx5l37/gKsQK6qbUrP/r27m/vVZg7woTGmCpLjM2aMecIYM9EYMw3rs7KO5LleSinV66RK4PY+MNzeLenBmk5a2JMdard2Zy7WtBJY/TrX3sE5GGuh9ntd1IciEcm1b/uAE7EW2y8GzrIfdgnwckzfLrFvnwX803RBIkBjzM3GmDJjzCCsv9U/jTEXxnzZC9a6qNhrdrG9K/EooK5tKu5L7tcuYJuIjLSbZgKrib8u7a9Xl/crxnnETJMmyWesj/17ADDP7l+yXC+llOp1XAd/SO9njAmKyHXAPwAn8KQxZlV3nV9EngeOBwpFpBK4DTherHQWBtgMXGX3dZWIzMcKCILAtcaYUBd1rS/wjL2j0AHMN8b8VURWAy+IyE+Bj7AX49u/nxWR9VijJ+d2Ub8685yIFGFNqS0HvmO3v4a1fmo91o7KS7uwD9+1++EBNtrncgDzReQyYCtwdnf3y15DNgv7c2T7eRJ8xv4sIgVAwD5PjYj8jB6+Xkop1Vtp5QSllFJKqV4iVaZKlVJKKaV6PQ3clFJKKaV6CQ3clFJKKaV6CQ3clFJKKaV6CQ3clFJKKaV6CQ3cVNIRkZCILI/5OVB1AkTkOyJy8Zdw3s0iUvhFX0cppZTqKpoORCUdEWk0xmT2wHk3A5ONMXu6+9xKKaXUodARN9Vr2CNi94nIe/bPMLv9dhH5gX37eyKy2i6s/oLdli8iL9lt74jIEXZ7gYi8bheM/w0xtTJF5EL7HMtF5Dci4rR/nhaRT0RkpYh8vwcug1JKqRSmgZtKRr52U6XnxByrN8ZMAf4beDDBc28CJhhjjiBaWeEO4CO77f8Cv7PbbwPetAvGLwQGAIhIOXAOcIwxZjwQAi7AKtZeaowZY4wZi1UvVSmllOo2KVHySvU6zXbAlMjzMb8fSHD8Y6ySVC8BL9ltxwLfADDG/NMeacsBpmHVz8QY86qI1NiPnwlMAt63yqLiwyqE/gowREQeBl4FXv/8b1EppZQ6fDripnob08ntNqcCj2AFXh+IiIuYKdAEz030GgI8Y4wZb/+MNMbcboypAcYBS4Brgcc/53tQSimlPhcN3FRvc07M77djD4iIA+hvjFkM3AjkApnAv7CmOhGR44E9xpj6du1zgDz7pRYBZ4lIH/tYvogMtHecOowxfwZuBSZ21ZtUSimlEtGpUpWMfCKyPOb+340xbSlBvCLyLtY/Os5r9zwn8Ht7GlSAB4wxtSJyO/CUiHwMNAGX2I+/A3heRD4ElgJbAYwxq0XkFuB1OxgMYI2wNduv0/YPnpu/vLeslFJKHZymA1G9hqbrUEoplep0qlQppZRSqpfQETellFJKqV5CR9yUUkoppXoJDdyUUkoppXoJDdyUUkoppXoJDdyUUkoppXoJDdyUUkoppXoJDdyUUkoppXqJ/w8/E7BrW1m/twAAAABJRU5ErkJggg==\n", 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" ] @@ -945,68 +399,18 @@ "per_group_interp.add_interpretation(\n", " GroupAgentInterpretation.from_pickle('data/lunarlander_dqn', 'dqn_PriorityExperienceReplay_FEED_TYPE_STATE')\n", ")\n", - "per_group_interp.plot_reward_bounds(per_episode=True, 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changed, 204 insertions(+), 19 deletions(-) diff --git a/README.md b/README.md index b681e09..1507ba7 100644 --- a/README.md +++ b/README.md @@ -170,18 +170,59 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe ### Reward Graphs -| | Model | Gif(Early) | Gif(Mid) | Gif(Late) | -|:----------------------------------------:|:-------:|:--------------------:|:--------------------:|:--------------------:| -| ![](./res/reward_plots/cartpole_dqn.png) | DQN | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | -| | acn | | | | - - - - -| Gif(Early) | Gif(Mid) | Gif(Late) | -|:--------------------:|:--------------------:|:--------------------:| -| ![1](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![2](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![3](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | -| | | | - - ![2](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) - ![3](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) \ No newline at end of file +| | Model | +|:------------------------------------------:|:---------------:| +| ![01](./res/reward_plots/cartpole_dqn.png) | DQN+ER | + + +### Agent Stages + +| Model | Gif(Early) | Gif(Mid) | Gif(Late) | +|:------------:|:------------:|:------------:|:------------:| +| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| +| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| +| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| +| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| +| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| +| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| +| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| +| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| +| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| +| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| +| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| +| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| +| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| +| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| +| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| +| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| +| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| +| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| +| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| +| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| +| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| +| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| +| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| +| DDPG+ER | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)| +| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| +| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| +| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| +| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| +| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| +| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| +| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| +| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| +| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| +| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| +| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| +| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| +| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| +| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| +| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| +| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| +| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| +| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| +| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| +| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| +| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| +| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| +| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| \ No newline at end of file diff --git a/docs_src/util.gif_handling.ipynb b/docs_src/util.gif_handling.ipynb index 0c50b38..fedcad1 100644 --- a/docs_src/util.gif_handling.ipynb +++ b/docs_src/util.gif_handling.ipynb @@ -118,6 +118,149 @@ " optimize(str(Path(root_location+g_i)))" ] }, + { + "cell_type": "code", + "execution_count": 185, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [], + "source": [ + "df=pd.DataFrame(data={\"Model\":[],\"Gif(Early)\":[],\"Gif(Mid)\":[],\"Gif(Late)\":[]})" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": {}, + "outputs": [], + "source": [ + "gifs=os.listdir('../res/run_gifs')" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": {}, + "outputs": [], + "source": [ + "def filter_str_list(some_list,contains):\n", + " return [o for o in some_list if o.__contains__(contains) and not o.__contains__('.py')]\n", + "def parse_model_mem(item):\n", + " output=\"+PER\" if item.__contains__('PriorityExperienceReplay') else \"+ER\"\n", + " return [o[:-6] for o in item.split('_') if o.__contains__('Module')][0]+output\n", + "def convert_gif_to_link(item):\n", + " return f'![](../res/run_gifs/{item})'\n", + "def take_second(elem):\n", + " return elem[1]" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": {}, + "outputs": [], + "source": [ + "for env in set([n.split('_')[0] for n in gifs if n!='']):\n", + " local_list=sorted(filter_str_list(gifs,env))\n", + " unique_runs=list(set(['_'.join(o.split('_')[:-2]) for o in local_list]))\n", + " for item in unique_runs:\n", + " row_list=filter_str_list(local_list,item)\n", + " if len(row_list)==0: continue\n", + " row_list=list(sorted([(o,o.split('_')[-1][:-4]) for o in row_list[:3]],key=take_second,reverse=True))\n", + " row_list=[o[0] for o in row_list]\n", + " df=df.append(pd.DataFrame(data={\"Model\":[parse_model_mem(item)],\n", + " \"Gif(Early)\":[row_list[0]],\n", + " \"Gif(Mid)\":[row_list[1]],\n", + " \"Gif(Late)\":[row_list[2]]}))" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": {}, + "outputs": [], + "source": [ + "df.reset_index(inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "| Model | Gif(Early) | Gif(Mid) | Gif(Late) |\n", + "|:------------:|:------------:|:------------:|:------------:|\n", + "| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)|\n", + "| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)|\n", + "| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)|\n", + "| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)|\n", + "| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)|\n", + "| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)|\n", + "| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)|\n", + "| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)|\n", + "| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)|\n", + "| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)|\n", + "| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)|\n", + "| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)|\n", + "| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)|\n", + "| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)|\n", + "| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)|\n", + "| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)|\n", + "| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)|\n", + "| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)|\n", + "| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)|\n", + "| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)|\n", + "| DDPG+ER | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)|\n", + "| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)|\n", + "| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)|\n", + "| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)|\n", + "| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)|\n", + "| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)|\n", + "| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)|\n", + "| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)|\n", + "| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)|\n", + "| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)|\n", + "| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)|\n", + "| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)|\n", + "| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)|\n", + "| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)|\n", + "| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)|\n", + "| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)|\n", + "| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)|\n", + "| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)|\n", + "| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)|\n", + "| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)|\n", + "| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)|\n", + "| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)|\n" + ] + } + ], + "source": [ + "for i,row in df.iterrows():\n", + " if i==0:\n", + " print('| ' + ' | '.join(df.columns[1:]) + ' |')\n", + " print('|:------------:'*len(df.columns[1:]) + '|')\n", + " else:\n", + " print(f'| {list(row)[1]} | ' + ' | '.join([convert_gif_to_link(o) for o in list(row)[2:]]) + '|')" + ] + }, { "cell_type": "code", "execution_count": null, @@ -128,9 +271,9 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "PyCharm (fast-reinforcement-learning)", "language": "python", - "name": "python3" + "name": "pycharm-acf1a9e4" }, "language_info": { "codemirror_mode": { @@ -142,7 +285,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.9" + "version": "3.6.7" } }, "nbformat": 4, diff --git a/environment.yaml b/environment.yaml index fb5d411..2fcfe66 100644 --- a/environment.yaml +++ b/environment.yaml @@ -27,4 +27,5 @@ dependencies: - easydict - matplotlib - jupyter_console - - moviepy \ No newline at end of file + - moviepy + - pygifsicle \ No newline at end of file From 9ca68f70f2928f64910ed2706e180270a81a9047 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 20:53:04 -0500 Subject: [PATCH 08/29] Added: - reward graphs --- README.md | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 1507ba7..7279119 100644 --- a/README.md +++ b/README.md @@ -172,7 +172,20 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe | | Model | |:------------------------------------------:|:---------------:| -| ![01](./res/reward_plots/cartpole_dqn.png) | DQN+ER | +| ![01](./res/reward_plots/cartpole_dqn.png) | DQN | +| ![01](./res/reward_plots/cartpole_dueling.png) | Dueling DQN | +| ![01](./res/reward_plots/cartpole_double.png) | Double DQN | +| ![01](./res/reward_plots/cartpole_dddqn.png) | DDDQN | +| ![01](./res/reward_plots/cartpole_fixedtarget.png) | Fixed Target DQN | +| ![01](./res/reward_plots/lunarlander_dqn.png) | DQN | +| ![01](./res/reward_plots/lunarlander_dueling.png) | Dueling DQN | +| ![01](./res/reward_plots/lunarlander_double.png) | Double DQN | +| ![01](./res/reward_plots/lunarlander_dddqn.png) | DDDQN | +| ![01](./res/reward_plots/lunarlander_fixedtarget.png) | Fixed Target DQN | +| ![01](./res/reward_plots/ant_ddpg.png) | DDPG | +| ![01](./res/reward_plots/pendulum_ddpg.png) | DDPG | +| ![01](./res/reward_plots/halfcheetah_ddpg.png) | DDPG | + ### Agent Stages From ec375058e6ea1eab61c80160ed789668b848c5ee Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 20:55:36 -0500 Subject: [PATCH 09/29] Added: - reward graphs --- README.md | 96 +++++++++++++++++++++++++++---------------------------- 1 file changed, 48 insertions(+), 48 deletions(-) diff --git a/README.md b/README.md index 7279119..3f9e916 100644 --- a/README.md +++ b/README.md @@ -186,56 +186,56 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe | ![01](./res/reward_plots/pendulum_ddpg.png) | DDPG | | ![01](./res/reward_plots/halfcheetah_ddpg.png) | DDPG | - +![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) ### Agent Stages | Model | Gif(Early) | Gif(Mid) | Gif(Late) | |:------------:|:------------:|:------------:|:------------:| -| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| -| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| -| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| -| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| -| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| -| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| -| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| -| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| -| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| -| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| -| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| -| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| -| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| -| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| -| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| -| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| -| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| -| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| -| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| -| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| -| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| -| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| -| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| -| DDPG+ER | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)| -| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| -| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| -| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| -| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| -| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| -| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| -| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| -| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| -| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| -| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| -| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| -| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| -| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| -| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| -| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| -| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| -| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| -| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| -| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| -| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| -| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| -| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| -| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| \ No newline at end of file +| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| +| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| +| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| +| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| +| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| +| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| +| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| +| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| +| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| +| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| +| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| +| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)| +| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| +| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| +| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| +| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| +| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| +| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| +| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| +| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| +| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| +| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| +| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| \ No newline at end of file From 2d3d466298c7e1ec5c015c2afca84c93446cd95e Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 20:55:59 -0500 Subject: [PATCH 10/29] Added: - reward graphs --- README.md | 1 - 1 file changed, 1 deletion(-) diff --git a/README.md b/README.md index 3f9e916..d4528a3 100644 --- a/README.md +++ b/README.md @@ -186,7 +186,6 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe | ![01](./res/reward_plots/pendulum_ddpg.png) | DDPG | | ![01](./res/reward_plots/halfcheetah_ddpg.png) | DDPG | -![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) ### Agent Stages From 006b41f0ad314eec1981fa95a3772f62c6a4dd14 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 20:56:26 -0500 Subject: [PATCH 11/29] Added: - reward graphs --- docs_src/util.gif_handling.ipynb | 13 +++++++++++-- 1 file changed, 11 insertions(+), 2 deletions(-) diff --git a/docs_src/util.gif_handling.ipynb b/docs_src/util.gif_handling.ipynb index fedcad1..a907a5a 100644 --- a/docs_src/util.gif_handling.ipynb +++ b/docs_src/util.gif_handling.ipynb @@ -157,7 +157,7 @@ " output=\"+PER\" if item.__contains__('PriorityExperienceReplay') else \"+ER\"\n", " return [o[:-6] for o in item.split('_') if o.__contains__('Module')][0]+output\n", "def convert_gif_to_link(item):\n", - " return f'![](../res/run_gifs/{item})'\n", + " return f'![](./res/run_gifs/{item})'\n", "def take_second(elem):\n", " return elem[1]" ] @@ -286,8 +286,17 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.7" + }, + "pycharm": { + "stem_cell": { + "cell_type": "raw", + "source": [], + "metadata": { + "collapsed": false + } + } } }, "nbformat": 4, "nbformat_minor": 1 -} +} \ No newline at end of file From 336796da49d62efb94c769c11bdee738b8d06d86 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 21:03:06 -0500 Subject: [PATCH 12/29] Added: - reward graphs --- README.md | 94 +++++------ docs_src/util.gif_handling.ipynb | 274 +++++++++++++++---------------- 2 files changed, 177 insertions(+), 191 deletions(-) diff --git a/README.md b/README.md index d4528a3..79da6f2 100644 --- a/README.md +++ b/README.md @@ -191,50 +191,50 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe | Model | Gif(Early) | Gif(Mid) | Gif(Late) | |:------------:|:------------:|:------------:|:------------:| -| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| -| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| -| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| -| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| -| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| -| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| -| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| -| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| -| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| -| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| -| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| -| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)| -| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)| -| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)| -| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)| -| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)| -| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)| -| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)| -| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)| -| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)| -| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)| -| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)| -| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)| \ No newline at end of file +| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)| +| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)| +| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)| +| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)| +| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)| +| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)| +| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)| +| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)| +| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)| +| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)| +| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)| +| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif)| +| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)| +| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)| +| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)| +| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)| +| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)| +| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)| +| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)| +| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)| +| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)| +| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)| +| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)| +| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)| +| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)| +| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)| +| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)| +| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)| +| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)| \ No newline at end of file diff --git a/docs_src/util.gif_handling.ipynb b/docs_src/util.gif_handling.ipynb index a907a5a..b585758 100644 --- a/docs_src/util.gif_handling.ipynb +++ b/docs_src/util.gif_handling.ipynb @@ -2,10 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 199, "metadata": { "pycharm": { - "is_executing": true + "is_executing": false } }, "outputs": [], @@ -17,8 +17,12 @@ }, { "cell_type": "code", - "execution_count": 14, - "metadata": {}, + "execution_count": 200, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "root_location='../res/run_gifs/'\n", @@ -27,85 +31,35 @@ }, { "cell_type": "code", - "execution_count": 22, - "metadata": {}, + "execution_count": 201, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif\n", - "5763851\n", - "pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif\n", - "6137289\n", "ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif\n", - "36778535\n", - "acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif\n", - "11609189\n", - 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"10103383\n", - "cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif\n", - "15459933\n", - "cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif\n", - "15569151\n", - "ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif\n", - "37563630\n", - "lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif\n", - "15766535\n", - "lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif\n", - "30719225\n", - "lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif\n", - "5376415\n", - "pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif\n", - "6241684\n", - "cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif\n", - "15578381\n" + "8026824\n" + ] + }, + { + "ename": "FileNotFoundError", + "evalue": "[Errno 2] No such file or directory: 'gifsicle': 'gifsicle'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mg_i\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroot_location\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mg_i\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mst_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0moptimize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mroot_location\u001b[0m\u001b[0;34m+\u001b[0m\u001b[0mg_i\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/fastrl/lib/python3.6/site-packages/pygifsicle/pygifsicle.py\u001b[0m in \u001b[0;36moptimize\u001b[0;34m(source, *args, **kwargs)\u001b[0m\n\u001b[1;32m 62\u001b[0m \u001b[0mPath\u001b[0m \u001b[0mto\u001b[0m \u001b[0mgif\u001b[0m \u001b[0mimage\u001b[0m \u001b[0mto\u001b[0m \u001b[0moptimize\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 63\u001b[0m \"\"\"\n\u001b[0;32m---> 64\u001b[0;31m \u001b[0mgifsicle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msource\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moptimize\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/envs/fastrl/lib/python3.6/site-packages/pygifsicle/pygifsicle.py\u001b[0m in \u001b[0;36mgifsicle\u001b[0;34m(sources, destination, optimize, colors, options)\u001b[0m\n\u001b[1;32m 51\u001b[0m \u001b[0moptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"--optimize\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 52\u001b[0m subprocess.call([\"gifsicle\", *options, *sources, \"--colors\",\n\u001b[0;32m---> 53\u001b[0;31m str(colors), \"--output\", destination])\n\u001b[0m\u001b[1;32m 54\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 55\u001b[0m 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\u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/fastrl/lib/python3.6/subprocess.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, encoding, errors)\u001b[0m\n\u001b[1;32m 707\u001b[0m \u001b[0mc2pread\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mc2pwrite\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 708\u001b[0m \u001b[0merrread\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrwrite\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m restore_signals, start_new_session)\n\u001b[0m\u001b[1;32m 710\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 711\u001b[0m \u001b[0;31m# Cleanup if the child failed starting.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/envs/fastrl/lib/python3.6/subprocess.py\u001b[0m in \u001b[0;36m_execute_child\u001b[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, start_new_session)\u001b[0m\n\u001b[1;32m 1342\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0merrno_num\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0merrno\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mENOENT\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1343\u001b[0m \u001b[0merr_msg\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;34m': '\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mrepr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr_filename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1344\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mchild_exception_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merrno_num\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merr_msg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merr_filename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1345\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mchild_exception_type\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr_msg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1346\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'gifsicle': 'gifsicle'" ] } ], @@ -120,8 +74,12 @@ }, { "cell_type": "code", - "execution_count": 185, - "metadata": {}, + "execution_count": 209, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "import pandas as pd" @@ -129,8 +87,12 @@ }, { "cell_type": "code", - "execution_count": 193, - "metadata": {}, + "execution_count": 210, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "df=pd.DataFrame(data={\"Model\":[],\"Gif(Early)\":[],\"Gif(Mid)\":[],\"Gif(Late)\":[]})" @@ -138,8 +100,12 @@ }, { "cell_type": "code", - "execution_count": 194, - "metadata": {}, + "execution_count": 211, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "gifs=os.listdir('../res/run_gifs')" @@ -147,8 +113,12 @@ }, { "cell_type": "code", - "execution_count": 195, - "metadata": {}, + "execution_count": 212, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "def filter_str_list(some_list,contains):\n", @@ -159,13 +129,17 @@ "def convert_gif_to_link(item):\n", " return f'![](./res/run_gifs/{item})'\n", "def take_second(elem):\n", - " return elem[1]" + " return int(elem[1])" ] }, { "cell_type": "code", - "execution_count": 196, - "metadata": {}, + "execution_count": 213, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "for env in set([n.split('_')[0] for n in gifs if n!='']):\n", @@ -174,7 +148,7 @@ " for item in unique_runs:\n", " row_list=filter_str_list(local_list,item)\n", " if len(row_list)==0: continue\n", - " row_list=list(sorted([(o,o.split('_')[-1][:-4]) for o in row_list[:3]],key=take_second,reverse=True))\n", + " row_list=list(sorted([(o,o.split('_')[-1][:-4]) for o in row_list[:3]],key=take_second))\n", " row_list=[o[0] for o in row_list]\n", " df=df.append(pd.DataFrame(data={\"Model\":[parse_model_mem(item)],\n", " \"Gif(Early)\":[row_list[0]],\n", @@ -184,8 +158,12 @@ }, { "cell_type": "code", - "execution_count": 197, - "metadata": {}, + "execution_count": 214, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [ "df.reset_index(inplace=True)" @@ -193,8 +171,12 @@ }, { "cell_type": "code", - "execution_count": 198, - "metadata": {}, + "execution_count": 215, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [ { "name": "stdout", @@ -202,53 +184,53 @@ "text": [ "| Model | Gif(Early) | Gif(Mid) | Gif(Late) |\n", "|:------------:|:------------:|:------------:|:------------:|\n", - "| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)|\n", - "| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)|\n", - "| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)|\n", - "| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)|\n", - "| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)|\n", - "| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)|\n", - "| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)|\n", - "| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)|\n", - "| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)|\n", - "| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)|\n", - "| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)|\n", - "| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)|\n", - "| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)|\n", - "| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)|\n", - "| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)|\n", - "| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)|\n", - "| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)|\n", - "| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)|\n", - "| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)|\n", - "| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)|\n", - "| DDPG+ER | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif) | ![](../res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](../res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif)|\n", - "| DoubleDueling+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif)|\n", - "| DoubleDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif)|\n", - "| DuelingDQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif)|\n", - "| DoubleDueling+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif)|\n", - "| DQN+ER | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](../res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif)|\n", - "| DuelingDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif)|\n", - "| DQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif)|\n", - "| DoubleDQN+PER | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](../res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](../res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif)|\n", - "| DDPG+ER | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](../res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif)|\n", - "| DQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif)|\n", - "| FixedTargetDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif)|\n", - "| DQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif)|\n", - "| FixedTargetDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif)|\n", - "| DoubleDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif)|\n", - "| DoubleDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif)|\n", - "| DuelingDQN+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif)|\n", - "| DoubleDueling+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif)|\n", - "| DuelingDQN+PER | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif) | ![](../res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif)|\n", - "| DoubleDueling+ER | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](../res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif)|\n", - "| DDPG+ER | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif) | ![](../res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif)|\n", - "| DDPG+PER | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif) | ![](../res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif)|\n" + "| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)|\n", + "| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)|\n", + "| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)|\n", + "| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)|\n", + "| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)|\n", + "| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)|\n", + "| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)|\n", + "| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", + "| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)|\n", + "| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)|\n", + "| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)|\n", + "| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)|\n", + "| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)|\n", + "| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)|\n", + "| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)|\n", + "| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)|\n", + "| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)|\n", + "| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)|\n", + "| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)|\n", + "| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", + "| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)|\n", + "| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)|\n", + "| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", + "| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)|\n", + "| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)|\n", + "| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)|\n", + "| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)|\n", + "| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)|\n", + "| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)|\n", + "| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)|\n", + "| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)|\n", + "| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)|\n", + "| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)|\n", + "| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)|\n", + "| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)|\n", + "| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)|\n", + "| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)|\n", + "| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)|\n", + "| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)|\n", + "| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)|\n", + "| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)|\n", + "| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)|\n" ] } ], @@ -264,7 +246,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": false + } + }, "outputs": [], "source": [] } @@ -290,13 +276,13 @@ "pycharm": { "stem_cell": { "cell_type": "raw", - "source": [], "metadata": { "collapsed": false - } + }, + "source": [] } } }, "nbformat": 4, "nbformat_minor": 1 -} \ No newline at end of file +} From b1d7aa6fd39e818e5fbf1dafee22c4274e4692b8 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 2 Feb 2020 21:11:23 -0500 Subject: [PATCH 13/29] Added: - reward graphs --- README.md | 24 ---------- docs_src/util.gif_handling.ipynb | 80 +++++++++++++++++++------------- 2 files changed, 47 insertions(+), 57 deletions(-) diff --git a/README.md b/README.md index 79da6f2..22196b2 100644 --- a/README.md +++ b/README.md @@ -191,30 +191,6 @@ and [Abbreviations](https://docs.fast.ai/dev/abbr.html). Also we will use RL spe | Model | Gif(Early) | Gif(Mid) | Gif(Late) | |:------------:|:------------:|:------------:|:------------:| -| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)| -| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)| -| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)| -| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)| -| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)| -| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)| -| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)| -| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)| -| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)| -| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)| -| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)| -| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)| -| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)| -| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)| -| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)| -| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)| -| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)| -| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif)| | DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)| | DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)| | DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)| diff --git a/docs_src/util.gif_handling.ipynb b/docs_src/util.gif_handling.ipynb index b585758..9267b74 100644 --- a/docs_src/util.gif_handling.ipynb +++ b/docs_src/util.gif_handling.ipynb @@ -74,7 +74,7 @@ }, { "cell_type": "code", - "execution_count": 209, + "execution_count": 242, "metadata": { "pycharm": { "is_executing": false @@ -87,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": 210, + "execution_count": 243, "metadata": { "pycharm": { "is_executing": false @@ -100,7 +100,7 @@ }, { "cell_type": "code", - "execution_count": 211, + "execution_count": 244, "metadata": { "pycharm": { "is_executing": false @@ -113,7 +113,7 @@ }, { "cell_type": "code", - "execution_count": 212, + "execution_count": 245, "metadata": { "pycharm": { "is_executing": false @@ -134,18 +134,56 @@ }, { "cell_type": "code", - "execution_count": 213, + "execution_count": 246, "metadata": { "pycharm": { "is_executing": false } }, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "pendulum\n", + "pendulum_ExperienceReplay_DDPGModule_1\n", + "pendulum_PriorityExperienceReplay_DDPGModule_1\n", + "lunarlander\n", + "lunarlander_ExperienceReplay_DoubleDuelingModule_1\n", + "lunarlander_ExperienceReplay_DoubleDQNModule_1\n", + "lunarlander_ExperienceReplay_DuelingDQNModule_1\n", + "lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1\n", + "lunarlander_ExperienceReplay_DQNModule_1\n", + "lunarlander_PriorityExperienceReplay_DuelingDQNModule_1\n", + "lunarlander_PriorityExperienceReplay_DQNModule_1\n", + "lunarlander_PriorityExperienceReplay_DoubleDQNModule_1\n", + "ant\n", + "ant_PriorityExperienceReplay_DDPGModule_1\n", + "ant_ExperienceReplay_DDPGModule_1\n", + "cartpole\n", + "cartpole_PriorityExperienceReplay_DQNModule_1\n", + "cartpole_ExperienceReplay_FixedTargetDQNModule_1\n", + "cartpole_ExperienceReplay_DQNModule_1\n", + "cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1\n", + "cartpole_ExperienceReplay_DoubleDQNModule_1\n", + "cartpole_PriorityExperienceReplay_DoubleDQNModule_1\n", + "cartpole_ExperienceReplay_DuelingDQNModule_1\n", + "cartpole_PriorityExperienceReplay_DoubleDuelingModule_1\n", + "cartpole_PriorityExperienceReplay_DuelingDQNModule_1\n", + "cartpole_ExperienceReplay_DoubleDuelingModule_1\n", + "acrobot\n", + "acrobot_ExperienceReplay_DDPGModule_1\n", + "acrobot_PriorityExperienceReplay_DDPGModule_1\n" + ] + } + ], "source": [ - "for env in set([n.split('_')[0] for n in gifs if n!='']):\n", + "for env in set([n.split('_')[0] for n in gifs if n.split('_')[0]!='']):\n", + " print(env)\n", " local_list=sorted(filter_str_list(gifs,env))\n", " unique_runs=list(set(['_'.join(o.split('_')[:-2]) for o in local_list]))\n", " for item in unique_runs:\n", + " print(item)\n", " row_list=filter_str_list(local_list,item)\n", " if len(row_list)==0: continue\n", " row_list=list(sorted([(o,o.split('_')[-1][:-4]) for o in row_list[:3]],key=take_second))\n", @@ -158,7 +196,7 @@ }, { "cell_type": "code", - "execution_count": 214, + "execution_count": 247, "metadata": { "pycharm": { "is_executing": false @@ -171,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 215, + "execution_count": 248, "metadata": { "pycharm": { "is_executing": false @@ -184,30 +222,6 @@ "text": [ "| Model | Gif(Early) | Gif(Mid) | Gif(Late) |\n", "|:------------:|:------------:|:------------:|:------------:|\n", - "| FixedTargetDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_57.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_309.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_FixedTargetDQNModule_1_episode_438.gif)|\n", - "| FixedTargetDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_13.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_265.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_FixedTargetDQNModule_1_episode_449.gif)|\n", - "| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)|\n", - "| DoubleDueling+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_43.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_287.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDuelingModule_1_episode_447.gif)|\n", - "| DoubleDueling+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_151.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_341.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDuelingModule_1_episode_999.gif)|\n", - "| DuelingDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_69.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_272.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DuelingDQNModule_1_episode_438.gif)|\n", - "| DDPG+ER | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_69.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_197.gif) | ![](./res/run_gifs/acrobot_ExperienceReplay_DDPGModule_1_episode_438.gif)|\n", - "| DQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_44.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_216.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DQNModule_1_episode_413.gif)|\n", - "| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", - "| DuelingDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_112.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_431.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DuelingDQNModule_1_episode_980.gif)|\n", - "| DoubleDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_60.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_268.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DoubleDQNModule_1_episode_438.gif)|\n", - "| DoubleDQN+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_35.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_269.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDQNModule_1_episode_444.gif)|\n", - "| DuelingDQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_62.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_209.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DuelingDQNModule_1_episode_432.gif)|\n", - "| DQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_99.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_382.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DQNModule_1_episode_949.gif)|\n", - "| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)|\n", - "| DDPG+PER | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_55.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_267.gif) | ![](./res/run_gifs/acrobot_PriorityExperienceReplay_DDPGModule_1_episode_422.gif)|\n", - "| DQN+ER | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_31.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_207.gif) | ![](./res/run_gifs/cartpole_ExperienceReplay_DQNModule_1_episode_447.gif)|\n", - "| DoubleDueling+PER | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_2.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_260.gif) | ![](./res/run_gifs/cartpole_PriorityExperienceReplay_DoubleDuelingModule_1_episode_438.gif)|\n", - "| DQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_93.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_541.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DQNModule_1_episode_999.gif)|\n", - "| DuelingDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_21.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_442.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DuelingDQNModule_1_episode_998.gif)|\n", - "| DDPG+PER | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_52.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_596.gif) | ![](./res/run_gifs/ant_PriorityExperienceReplay_DDPGModule_1_episode_984.gif)|\n", - "| DDPG+ER | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_54.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_614.gif) | ![](./res/run_gifs/ant_ExperienceReplay_DDPGModule_1_episode_999.gif)|\n", - "| DoubleDQN+PER | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_7.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_514.gif) | ![](./res/run_gifs/lunarlander_PriorityExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", - "| DDPG+ER | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_9.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_238.gif) | ![](./res/run_gifs/pendulum_ExperienceReplay_DDPGModule_1_episode_447.gif)|\n", "| DDPG+PER | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_35.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_222.gif) | ![](./res/run_gifs/pendulum_PriorityExperienceReplay_DDPGModule_1_episode_431.gif)|\n", "| DoubleDueling+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_114.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_346.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDuelingModule_1_episode_925.gif)|\n", "| DoubleDQN+ER | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_88.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_613.gif) | ![](./res/run_gifs/lunarlander_ExperienceReplay_DoubleDQNModule_1_episode_999.gif)|\n", From 3a09d5f2a96d6b7048b6bc17d4f63f0c9eb1f537 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 9 Feb 2020 16:59:18 -0500 Subject: [PATCH 14/29] Added: - initial TRPO step code. Highly likely this is way off. This is a first attempt as translating math of the research paper into a code implementation. Excited to see how close I was to the real implimentation --- docs_src/rl.agents.trpo.ipynb | 96 +++++++++++++++++++++++++++++++++++ fast_rl/agents/ddpg_models.py | 7 --- fast_rl/agents/trpo.py | 27 ++++++++++ fast_rl/agents/trpo_models.py | 95 ++++++++++++++++++++++++++++++++++ fast_rl/core/basic_train.py | 2 +- tests/test_trpo.py | 43 ++++++++++++++++ 6 files changed, 262 insertions(+), 8 deletions(-) create mode 100644 docs_src/rl.agents.trpo.ipynb create mode 100644 fast_rl/agents/trpo.py create mode 100644 fast_rl/agents/trpo_models.py create mode 100644 tests/test_trpo.py diff --git a/docs_src/rl.agents.trpo.ipynb b/docs_src/rl.agents.trpo.ipynb new file mode 100644 index 0000000..c768de4 --- /dev/null +++ b/docs_src/rl.agents.trpo.ipynb @@ -0,0 +1,96 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true, + "pycharm": { + "is_executing": false + } + }, + "source": [ + "\n", + "## TRPO\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from fastai.gen_doc.nbdoc import show_doc\n", + "from fast_rl.agents.trpo_models import *" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/markdown": [ + "

class TRPOModule[test]

\n", + "\n", + "> TRPOModule(**`ni`**:`int`, **`na`**:`int`, **`discount`**:`float`, **`fc_layers`**:`List`\\[`int`\\]=***`None`***, **`conv_filters`**:`List`\\[`int`\\]=***`None`***, **`nc`**=***`3`***, **`bn`**=***`False`***, **`q_lr`**=***`0.001`***, **`v_lr`**=***`0.0001`***, **`ks`**:`List`\\[`int`\\]=***`None`***, **`stride`**:`List`\\[`int`\\]=***`None`***) :: [`PrePostInitMeta`](/core.html#PrePostInitMeta) :: [`Module`](/torch_core.html#Module)\n", + "\n", + "

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×

No tests found for TRPOModule. To contribute a test please refer to this guide and this discussion.

\n", + "\n", + "Implementation of the TRPO (Trust Region Policy Optimization) algorithm. Policy Gradient based algorithm for reinforcement learning in discrete\n", + " and continuous state and action spaces. Details of the algorithm's mathematical background can be found in [1].\n", + "\n", + "References:\n", + " [1] (Schulman et al., 2017) Trust Region Policy Optimization.\n", + "\n", + "Args:\n", + " ni: na: discount: fc_layers: conv_filters:\n", + " nc:\n", + " bn:\n", + " q_lr:\n", + " v_lr:\n", + " ks:\n", + " stride: " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_doc(TRPOModule)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/fast_rl/agents/ddpg_models.py b/fast_rl/agents/ddpg_models.py index a568825..aca05f8 100644 --- a/fast_rl/agents/ddpg_models.py +++ b/fast_rl/agents/ddpg_models.py @@ -98,13 +98,6 @@ def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = References: [1] Lillicrap, Timothy P., et al. "Continuous control with deep reinforcement learning." arXiv preprint arXiv:1509.02971 (2015). - - Args: - data: Primary data object to use. - memory: How big the tree buffer will be for offline training. - tau: Defines how "soft/hard" we will copy the target networks over to the primary networks. - discount: Determines the amount of discounting the existing Q reward. - lr: Rate that the opt will learn parameter gradients. """ super().__init__() self.name = 'DDPG' diff --git a/fast_rl/agents/trpo.py b/fast_rl/agents/trpo.py new file mode 100644 index 0000000..b20205d --- /dev/null +++ b/fast_rl/agents/trpo.py @@ -0,0 +1,27 @@ +from fastai.basic_train import LearnerCallback + +from fast_rl.core.agent_core import Experience, ExplorationStrategy +from fast_rl.core.basic_train import AgentLearner, listify, torch, Any, List +from fast_rl.core.data_block import MDPDataBunch, MDPStep + + +class TRPOLearner(AgentLearner): + def __init__(self,data:MDPDataBunch,model,memory,trainers,opt=torch.optim.RMSprop, + **learn_kwargs): + self.memory:Experience=memory + super().__init__(data=data,model=model,opt=opt,**learn_kwargs) + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + + +class TRPOTrainer(LearnerCallback): + @property + def learn(self)->TRPOLearner: + return self._learn() + + def on_loss_begin(self, **kwargs: Any): + """Performs tree updates, exploration updates, and model optimization.""" + if self.learn.model.training: self.learn.memory.update(item=self.learn.data.x.items[-1]) + if not self.learn.warming_up: + samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) + self.learn.model.optimize(samples,visitation_freq=1/len(self.learn.memory)) diff --git a/fast_rl/agents/trpo_models.py b/fast_rl/agents/trpo_models.py new file mode 100644 index 0000000..bcc45b7 --- /dev/null +++ b/fast_rl/agents/trpo_models.py @@ -0,0 +1,95 @@ +from fastai.torch_core import * +from scipy.stats import entropy + + +class QModule(Module): + def __init__(self, ni, na): + super().__init__() + self.ni,self.na=ni,na + +class VModule(Module): + def __init__(self, ni): + super().__init__() + self.ni=ni + + +def kl_divergence(p: np.array, q: np.array): return entropy(p, q) +def advantage(s,a,q_net:QModule,v_net:VModule): return q_net(s,a)-v_net(s) + +def update_q(): pass +def update_v(): pass + + +class TRPOModule(Module): + """ + Implementation of the TRPO (Trust Region Policy Optimization) algorithm. + + Policy Gradient based algorithm for reinforcement learning in discrete + and continuous state and action spaces. Details of the algorithm's mathematical background can be found in [1]. + + References: + [1] (Schulman et al., 2017) Trust Region Policy Optimization. + """ + def __init__(self,ni:int,na:int,discount:float,fc_layers:List[int]=None,conv_filters:List[int]=None,nc=3,bn=False, + q_lr=1e-3,v_lr=1e-4,ks:List[int]=None,stride:List[int]=None,discrete:bool=True,paths='single', + n_timesteps=5,training=True,kl_e=0.1): + r""" + Implementation of the TRPO (Trust Region Policy Optimization) algorithm. + + Args: + ni: Number of inputs. Typically will be the number of dimensions of the state space. + na: Number of actions. Typically the number of action dimensions. + discount: Discount factor of q value estimation. + fc_layers: If the state input is not image based, then this is required. + conv_filters: Alternative image based state input/ + nc: Number of channels of input images + bn: Whether to use batch norm. If True typically produces unfavorable results, so default is False. + q_lr: Learning rate for the q value neural net. + v_lr: Learning rate for the v value neural net. + ks: Kernel size for conv layers for image based state inputs. + stride: Stride for conv layers for image based state inputs. + discrete: Whether the action space is discrete or not. + paths: TRPO has 2 options: vine or single paths. + n_timesteps: + """ + super().__init__() + self.kl_e=kl_e + self.discount=discount + self.discrete=discrete + self.q_net=QModule(ni,na) + self.v_net=VModule(ni) + self.training=True + + def forward(self, xi): + training = self.training + if xi.shape[0] == 1: self.eval() + pred = self.v_net(xi) + if training: self.train() + return pred + + def step(self,samples:List,visitation_freq:float): + # s_0 ~ p_0(s_0) + with torch.no_grad(): + r = torch.cat([item.reward.float() for item in samples]) + s_prime = torch.cat([item.s_prime for item in samples]) + s = torch.cat([item.s for item in samples]) + # [1] actions are chosen according to pi + a=self.forward(s) + + # p_pi(s) = P(s_0=s)+discount*P(s_1=s)+discount^2*P(s_2=s) ... + p=sum([visitation_freq*(self.discount**i) for i in range(len(samples))]) + # policy_prime(s) = argmax_a (A_pi (s,a)) + policy_prime=torch.argmax(advantage(s,a,self.q_net,self.v_net),1) + + adv=advantage(s,a,self.q_net,self.v_net) + + # C = (4*e*discount) / (1 - discount) ^ 2 + c=(4*self.kl_e*self.discount)/((1-self.discount)**2) + + v_net_target=deepcopy(self.v_net) + for target_param, local_param in zip(v_net_target.parameters(), self.v_net.parameters()): + # n(pi)= sum_s(p_pi(s) * sum_a (policy_prime(s,a)) * A(s,a)) + l_pi=target_param.data+p*sum(policy_prime*adv) + # pi_prime=L_pi(policy) - C * D(pi_i+1,pi) + target_param.data.copy_(l_pi-c*kl_divergence(target_param.data,local_param.data)) + diff --git a/fast_rl/core/basic_train.py b/fast_rl/core/basic_train.py index 8a7f8c9..9cc0ed9 100644 --- a/fast_rl/core/basic_train.py +++ b/fast_rl/core/basic_train.py @@ -53,7 +53,7 @@ def init_loss_func(self): By default, the learner will have a `None` loss function, and so the fit function will not try to log that loss. """ - self.loss_func = WrapperLossFunc(self) + self.loss_func=self._loss_func def export(self, file:PathLikeOrBinaryStream='export.pkl', destroy=False, pickle_data=False): "Export the state of the `Learner` in `self.path/file`. `file` can be file-like (file or buffer)" diff --git a/tests/test_trpo.py b/tests/test_trpo.py new file mode 100644 index 0000000..fdc3425 --- /dev/null +++ b/tests/test_trpo.py @@ -0,0 +1,43 @@ +from fast_rl.agents.trpo import TRPOLearner, TRPOTrainer +from fast_rl.agents.trpo_models import TRPOModule +from fast_rl.core.agent_core import ExperienceReplay +from fast_rl.core.data_block import MDPDataBunch + + +def test_trpo_learner_init_discrete(): + trpo_learner=TRPOLearner( + data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), + model=TRPOModule(4,2,0.001), + memory=ExperienceReplay(100), + trainers=TRPOTrainer + ) + +def test_trpo_learner_init_continuous(): + trpo_learner=TRPOLearner( + data=MDPDataBunch.from_env('AntPyBulletEnv-v0',bs=8,add_valid=False), + model=TRPOModule(4,8,0.001,discrete=False), + memory=ExperienceReplay(100), + trainers=TRPOTrainer + ) + + +def test_trpo_learner_discrete_fit(): + trpo_learner=TRPOLearner( + data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), + model=TRPOModule(4,2,0.001), + memory=ExperienceReplay(100), + trainers=TRPOTrainer + ) + trpo_learner.fit(4) + + +def test_trpo_model_calc_q(): + trpo_learner=TRPOLearner( + data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), + model=TRPOModule(4,2,0.001), + memory=ExperienceReplay(100), + trainers=TRPOTrainer + ) + +def test_trpo_model_calc_v(): pass +def test_trpo_model_calc_adv(): pass From cb107881099808d044bb842702af89e02b9cfb9a Mon Sep 17 00:00:00 2001 From: josiah Date: Sat, 22 Feb 2020 19:45:02 -0500 Subject: [PATCH 15/29] Added: - first good start with REINFORCE --- fast_rl/agents/old_trpo.py | 27 ++++++ .../{trpo_models.py => old_trpo_models.py} | 0 fast_rl/agents/reinforce.py | 88 +++++++++++++++++++ fast_rl/agents/reinforce_models.py | 58 ++++++++++++ fast_rl/agents/trpo.py | 26 +----- fast_rl/core/basic_train.py | 2 + tests/test_reinforce.py | 12 +++ tests/test_trpo.py | 4 +- 8 files changed, 190 insertions(+), 27 deletions(-) create mode 100644 fast_rl/agents/old_trpo.py rename fast_rl/agents/{trpo_models.py => old_trpo_models.py} (100%) create mode 100644 fast_rl/agents/reinforce.py create mode 100644 fast_rl/agents/reinforce_models.py create mode 100644 tests/test_reinforce.py diff --git a/fast_rl/agents/old_trpo.py b/fast_rl/agents/old_trpo.py new file mode 100644 index 0000000..b20205d --- /dev/null +++ b/fast_rl/agents/old_trpo.py @@ -0,0 +1,27 @@ +from fastai.basic_train import LearnerCallback + +from fast_rl.core.agent_core import Experience, ExplorationStrategy +from fast_rl.core.basic_train import AgentLearner, listify, torch, Any, List +from fast_rl.core.data_block import MDPDataBunch, MDPStep + + +class TRPOLearner(AgentLearner): + def __init__(self,data:MDPDataBunch,model,memory,trainers,opt=torch.optim.RMSprop, + **learn_kwargs): + self.memory:Experience=memory + super().__init__(data=data,model=model,opt=opt,**learn_kwargs) + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + + +class TRPOTrainer(LearnerCallback): + @property + def learn(self)->TRPOLearner: + return self._learn() + + def on_loss_begin(self, **kwargs: Any): + """Performs tree updates, exploration updates, and model optimization.""" + if self.learn.model.training: self.learn.memory.update(item=self.learn.data.x.items[-1]) + if not self.learn.warming_up: + samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) + self.learn.model.optimize(samples,visitation_freq=1/len(self.learn.memory)) diff --git a/fast_rl/agents/trpo_models.py b/fast_rl/agents/old_trpo_models.py similarity index 100% rename from fast_rl/agents/trpo_models.py rename to fast_rl/agents/old_trpo_models.py diff --git a/fast_rl/agents/reinforce.py b/fast_rl/agents/reinforce.py new file mode 100644 index 0000000..4dfd03f --- /dev/null +++ b/fast_rl/agents/reinforce.py @@ -0,0 +1,88 @@ +from typing import * +from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify + +import numpy as np +from fastai.tabular import TabularModel +from torch.distributions import Categorical +from torch.nn import Sequential + +from fast_rl.core.agent_core import ExplorationStrategy +from fast_rl.core.basic_train import AgentLearner +from fast_rl.core.data_block import MDPStep +from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper + + +class GaussianBasedExploration(ExplorationStrategy): + r""" Exploration via gaussian distribution of action outputs. + + This is per the usefulness noted in [1] pg 15. + + References: + [1] .. (Williams, 1992) [REINFORCE] Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning + """ + def perturb(self, action, action_space) -> np.ndarray: + m=Categorical(action) + a=m.sample() + return a + + +class LogBasedExploration(ExplorationStrategy): + def __init__(self): + super().__init__() + self.log_prob_a=0 + + r""" Exploration via log based probability distribution of action outputs. """ + def perturb(self, action, action_space) -> np.ndarray: + m=Categorical(action) + a=m.sample() + self.log_prob_a=m.log_prob(a) + return a + + +class REINFORCEStepWiseTrainer(LearnerCallback): + def __init__(self, learn): + super().__init__(learn) + self._order=1 + + def on_loss_begin(self, last_output,**kwargs): + r""" Loss will require the reward also """ + return {'last_output':{'last_output':last_output, + 'reward':self.learn.data.x.items[-1].reward.float().to(device=self.learn.data.device), + 'log_prob':self.learn.exploration_strategy.log_prob_a}} + + def on_step_end(self, **kwargs:Any) ->None: + self.learn.exploration_strategy.log_prob_a + + +def log_wise_loss(out, *args): + return -1*out['log_prob']*out['reward'] + + +class REINFORCELearner(AgentLearner): + def __init__(self, data,model,trainers=None,**kwargs): + trainers=ifnone(trainers,REINFORCEStepWiseTrainer) + super().__init__(data=data, model=model,**kwargs) + self.loss_func=log_wise_loss + self.exploration_strategy=LogBasedExploration() + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + + def predict(self, element, **kwargs): + training=self.model.training + if element.shape[0]==1: self.model.eval() + pred=self.model(element) + if training: self.model.train() + return self.exploration_strategy.perturb(pred, self.data.action.action_space) + + +def lazy_conv_out(m:Module,w,h,nc,switched)->int: + r""" A Lazier way to determining the conv block output. """ + is_training=m.training + m.eval() + ni=int(m(torch.zeros((1, w, h, nc) if switched else (1, nc, w, h))).view(-1, ).shape[0]) + if is_training: m.train(True) + return ni + + + + diff --git a/fast_rl/agents/reinforce_models.py b/fast_rl/agents/reinforce_models.py new file mode 100644 index 0000000..dd58419 --- /dev/null +++ b/fast_rl/agents/reinforce_models.py @@ -0,0 +1,58 @@ +from typing import * +from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify + +import numpy as np +from fastai.tabular import TabularModel +from torch.distributions import Categorical +from torch.nn import Sequential + +from fast_rl.agents.reinforce import lazy_conv_out +from fast_rl.core.agent_core import ExplorationStrategy +from fast_rl.core.basic_train import AgentLearner +from fast_rl.core.data_block import MDPStep +from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper + + + +class REINFORCEModel(Module): + def __init__(self, ni: int, na: int, layers: Optional[List[int]] = None, conv_layers: Optional[List[int]] = None, + stride: Optional[List[int]] = None, padding: Optional[List[int]] = None, use_bn=False, + nc: Optional[int] = None, + w: Optional[int] = None, h: Optional[int] = None, embed_szs: Optional[List[int]] = None): + super().__init__() + self.switched=False + self.action_model=Sequential() + if self.setup_convolutional_layers(ni, nc, conv_layers, stride, padding, use_bn): + ni=lazy_conv_out(self.action_model, w, h, nc, self.switched) + self.setup_linear_layers(ni, ifnone(embed_szs, []), ifnone(layers, [32, 32]), na, use_bn) + + def set_opt(self, _): + pass + + def fix_switched_channels(self, current_channels, expected_channels, layers: list): + if current_channels==expected_channels: return layers + self.switched=True + return [ChannelTranspose()]+layers + + def setup_convolutional_layers(self, ni, nc, cv_l, stride, padding, use_bn) -> bool: + if cv_l is None or len(cv_l)==0: return False + # gen a list of conv blocks based on the input size and the list of filter sizes + conv_blocks=[conv_bn_lrelu(_ni, nf, s, p, bn=use_bn) for _ni, nf, s, p in + zip([ni]+cv_l[:-1], cv_l[1:], stride, padding)] + fixed_conv_blocks=self.fix_switched_channels(ni, nc, conv_blocks) + self.action_model.add_module('conv_block', Sequential(fixed_conv_blocks+[Flatten()])) + return True + + def setup_linear_layers(self, ni, emb_szs, layers, ao, use_bn): + tabular_model=TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, + use_bn=use_bn) + if not emb_szs: tabular_model.embeds=None + if not use_bn: tabular_model.bn_cont=FakeBatchNorm() + self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) + + def forward(self, xi: Tensor): + training=self.training + if xi.shape[0]==1: self.eval() + pred=self.action_model(xi) + if training: self.train() + return pred \ No newline at end of file diff --git a/fast_rl/agents/trpo.py b/fast_rl/agents/trpo.py index b20205d..f764b17 100644 --- a/fast_rl/agents/trpo.py +++ b/fast_rl/agents/trpo.py @@ -1,27 +1,3 @@ -from fastai.basic_train import LearnerCallback -from fast_rl.core.agent_core import Experience, ExplorationStrategy -from fast_rl.core.basic_train import AgentLearner, listify, torch, Any, List -from fast_rl.core.data_block import MDPDataBunch, MDPStep - -class TRPOLearner(AgentLearner): - def __init__(self,data:MDPDataBunch,model,memory,trainers,opt=torch.optim.RMSprop, - **learn_kwargs): - self.memory:Experience=memory - super().__init__(data=data,model=model,opt=opt,**learn_kwargs) - self.trainers=listify(trainers) - for t in self.trainers: self.callbacks.append(t(self)) - - -class TRPOTrainer(LearnerCallback): - @property - def learn(self)->TRPOLearner: - return self._learn() - - def on_loss_begin(self, **kwargs: Any): - """Performs tree updates, exploration updates, and model optimization.""" - if self.learn.model.training: self.learn.memory.update(item=self.learn.data.x.items[-1]) - if not self.learn.warming_up: - samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) - self.learn.model.optimize(samples,visitation_freq=1/len(self.learn.memory)) +class GEAEstimator(): \ No newline at end of file diff --git a/fast_rl/core/basic_train.py b/fast_rl/core/basic_train.py index 9cc0ed9..82c08d2 100644 --- a/fast_rl/core/basic_train.py +++ b/fast_rl/core/basic_train.py @@ -3,6 +3,7 @@ from fastai.basic_train import Learner, load_callback from fastai.torch_core import * +from fast_rl.core.agent_core import ExplorationStrategy from fast_rl.core.data_block import MDPDataBunch @@ -39,6 +40,7 @@ def __init__(self, data, loss_func=None, callback_fns=None, opt=torch.optim.Adam self.model.set_opt(opt) self.loss_func = None self.trainers = None + self.exploration_strategy: Union[None,ExplorationStrategy]=None self._loss_func = WrapperLossFunc(self) @property diff --git a/tests/test_reinforce.py b/tests/test_reinforce.py new file mode 100644 index 0000000..14c82d1 --- /dev/null +++ b/tests/test_reinforce.py @@ -0,0 +1,12 @@ +# from fastai.core import ifnone +# +# from fast_rl.agents.reinforce import REINFORCELearner +# from fast_rl.agents.reinforce_models import REINFORCEModel +# from fast_rl.core.data_block import MDPDataBunch, FEED_TYPE_STATE +# +# +# def test_reinforce_fit(): +# data=MDPDataBunch.from_env('CartPole-v1') +# model=REINFORCEModel(4,2) +# reinforce_learner=REINFORCELearner(data,model) +# reinforce_learner.fit(3) \ No newline at end of file diff --git a/tests/test_trpo.py b/tests/test_trpo.py index fdc3425..6616885 100644 --- a/tests/test_trpo.py +++ b/tests/test_trpo.py @@ -1,5 +1,5 @@ -from fast_rl.agents.trpo import TRPOLearner, TRPOTrainer -from fast_rl.agents.trpo_models import TRPOModule +from fast_rl.agents.old_trpo import TRPOLearner, TRPOTrainer +from fast_rl.agents.old_trpo_models import TRPOModule from fast_rl.core.agent_core import ExperienceReplay from fast_rl.core.data_block import MDPDataBunch From c44a6aaa9110a72337c3bc13e64803ba7a6ef1ca Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 23 Feb 2020 18:04:29 -0500 Subject: [PATCH 16/29] Added: - REINFORCE is training now, but doesnt work. What happens when the actions are binary? An action with probability 1 is always going ot be sampled! --- fast_rl/agents/reinforce.py | 49 +++++++++++++++++++++++++----- fast_rl/agents/reinforce_models.py | 16 ++++------ tests/test_reinforce.py | 44 +++++++++++++++++++-------- 3 files changed, 80 insertions(+), 29 deletions(-) diff --git a/fast_rl/agents/reinforce.py b/fast_rl/agents/reinforce.py index 4dfd03f..a76569d 100644 --- a/fast_rl/agents/reinforce.py +++ b/fast_rl/agents/reinforce.py @@ -1,5 +1,5 @@ from typing import * -from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify +from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify, OptimWrapper import numpy as np from fastai.tabular import TabularModel @@ -44,26 +44,61 @@ def __init__(self, learn): super().__init__(learn) self._order=1 + def on_backward_begin(self, **kwargs:Any): return {'skip_bwd': False} + def on_loss_begin(self, last_output,**kwargs): - r""" Loss will require the reward also """ + r""" Loss will require the reward also. """ return {'last_output':{'last_output':last_output, 'reward':self.learn.data.x.items[-1].reward.float().to(device=self.learn.data.device), 'log_prob':self.learn.exploration_strategy.log_prob_a}} - def on_step_end(self, **kwargs:Any) ->None: - self.learn.exploration_strategy.log_prob_a + +def discount_reward(r:List,discount): + discounts=discount**torch.arange(len(r)) + if discounts.shape[0]==1: discounts=discounts.unsqueeze(0) + discount_r=torch.cat(r).view(-1).dot(discounts.squeeze(0).float()) + if len(discount_r.shape)==0: discount_r=discount_r.unsqueeze(0).unsqueeze(0) + elif len(discount_r.shape)==1: discount_r=discount_r.unsqueeze(0) + return discount_r + +class REINFORCEEpisodicTrainer(LearnerCallback): + def __init__(self, learn): + super().__init__(learn) + self._order=1 + self.reward_buffer=[] + self.log_prob_buffer=[] + + def on_backward_begin(self, **kwargs: Any): + return {'skip_bwd': not bool(self.learn.data.x.items[-1].done)} + + def on_loss_begin(self, last_output,**kwargs): + r""" Loss will require the reward also. """ + self.reward_buffer.append(self.learn.data.x.items[-1].reward.float()) + self.log_prob_buffer.append(self.learn.exploration_strategy.log_prob_a) + return {'last_output':{'last_output':last_output, + 'reward':discount_reward(self.reward_buffer,self.learn.discount).to(device=self.learn.data.device), + 'log_prob':self.log_prob_buffer}} + + def on_epoch_end(self, **kwargs:Any) ->None: + self.reward_buffer=[] + self.log_prob_buffer=[] def log_wise_loss(out, *args): - return -1*out['log_prob']*out['reward'] + if len(out['log_prob'])<2: + return (-1*torch.cat(out['log_prob'])*out['reward']).squeeze(0).squeeze(0) + else: + return (-1*torch.cat(out['log_prob'],-1)*out['reward'].squeeze(0)).sum() class REINFORCELearner(AgentLearner): - def __init__(self, data,model,trainers=None,**kwargs): + def __init__(self, data,model,trainers=None, lr=0.005,exploration_strategy=None,discount=None,**kwargs): + self.discount=ifnone(discount,0.99) trainers=ifnone(trainers,REINFORCEStepWiseTrainer) super().__init__(data=data, model=model,**kwargs) + self.opt=OptimWrapper.create(self.opt_func, lr=lr,layer_groups=[self.model.action_model]) self.loss_func=log_wise_loss - self.exploration_strategy=LogBasedExploration() + self.exploration_strategy=ifnone(exploration_strategy,LogBasedExploration()) self.trainers=listify(trainers) for t in self.trainers: self.callbacks.append(t(self)) diff --git a/fast_rl/agents/reinforce_models.py b/fast_rl/agents/reinforce_models.py index dd58419..08a7bd4 100644 --- a/fast_rl/agents/reinforce_models.py +++ b/fast_rl/agents/reinforce_models.py @@ -1,33 +1,28 @@ from typing import * -from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify -import numpy as np +from fastai.basic_train import Module, ifnone, Tensor from fastai.tabular import TabularModel -from torch.distributions import Categorical from torch.nn import Sequential from fast_rl.agents.reinforce import lazy_conv_out -from fast_rl.core.agent_core import ExplorationStrategy -from fast_rl.core.basic_train import AgentLearner -from fast_rl.core.data_block import MDPStep from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper - class REINFORCEModel(Module): def __init__(self, ni: int, na: int, layers: Optional[List[int]] = None, conv_layers: Optional[List[int]] = None, stride: Optional[List[int]] = None, padding: Optional[List[int]] = None, use_bn=False, - nc: Optional[int] = None, + nc: Optional[int] = None, model_base_line=0, w: Optional[int] = None, h: Optional[int] = None, embed_szs: Optional[List[int]] = None): super().__init__() + self.model_base_line=model_base_line self.switched=False self.action_model=Sequential() if self.setup_convolutional_layers(ni, nc, conv_layers, stride, padding, use_bn): ni=lazy_conv_out(self.action_model, w, h, nc, self.switched) self.setup_linear_layers(ni, ifnone(embed_szs, []), ifnone(layers, [32, 32]), na, use_bn) - def set_opt(self, _): - pass + def set_opt(self, opt): + None def fix_switched_channels(self, current_channels, expected_channels, layers: list): if current_channels==expected_channels: return layers @@ -55,4 +50,5 @@ def forward(self, xi: Tensor): if xi.shape[0]==1: self.eval() pred=self.action_model(xi) if training: self.train() + pred[pred<0]=self.model_base_line+0.0001 # TODO sometimes this fails due to a de-synchronization error return pred \ No newline at end of file diff --git a/tests/test_reinforce.py b/tests/test_reinforce.py index 14c82d1..4495038 100644 --- a/tests/test_reinforce.py +++ b/tests/test_reinforce.py @@ -1,12 +1,32 @@ -# from fastai.core import ifnone -# -# from fast_rl.agents.reinforce import REINFORCELearner -# from fast_rl.agents.reinforce_models import REINFORCEModel -# from fast_rl.core.data_block import MDPDataBunch, FEED_TYPE_STATE -# -# -# def test_reinforce_fit(): -# data=MDPDataBunch.from_env('CartPole-v1') -# model=REINFORCEModel(4,2) -# reinforce_learner=REINFORCELearner(data,model) -# reinforce_learner.fit(3) \ No newline at end of file +from fastai.core import ifnone, np +from fastai.tabular.data import emb_sz_rule + +from fast_rl.agents.reinforce import REINFORCELearner, REINFORCEStepWiseTrainer, REINFORCEEpisodicTrainer +from fast_rl.agents.reinforce_models import REINFORCEModel +from fast_rl.core.data_block import MDPDataBunch, FEED_TYPE_STATE, partial, ResolutionWrapper + + +def test_reinforce_fit_step_wise(): + data=MDPDataBunch.from_env('maze-random-5x5-v0',max_steps=100,render='human',k=0, res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3),add_valid=False) + bs, state, action=data.bs, data.state, data.action + if np.any(state.n_possible_values==np.inf): + emb_szs=[] + else: + emb_szs=[(d+1, int(emb_sz_rule(d))) for d in state.n_possible_values.reshape(-1, )] + + model=REINFORCEModel(2,2,embed_szs=emb_szs) + reinforce_learner=REINFORCELearner(data,model,trainers=[REINFORCEStepWiseTrainer]) + reinforce_learner.fit(450,lr=0.005) + +def test_reinforce_fit_episodic(): + data=MDPDataBunch.from_env('maze-random-5x5-v0',max_steps=100,render='human',k=0, + res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3),add_valid=False,device='cpu') + bs, state, action=data.bs, data.state, data.action + if np.any(state.n_possible_values==np.inf): + emb_szs=[] + else: + emb_szs=[(d+1, int(emb_sz_rule(d))) for d in state.n_possible_values.reshape(-1, )] + + model=REINFORCEModel(2,2,embed_szs=emb_szs) + reinforce_learner=REINFORCELearner(data,model,trainers=[REINFORCEEpisodicTrainer]) + reinforce_learner.fit(450,lr=0.005) \ No newline at end of file From 57d922cdb7db8da430b9d26f31acba8be5cbee4f Mon Sep 17 00:00:00 2001 From: josiah Date: Sat, 29 Feb 2020 18:56:23 -0500 Subject: [PATCH 17/29] Added: - cross entropy method. Does not seem to work great right now, pretty sure an existing bug in the code.. Removed: - reinforce and trpo code. Need to start over... --- fast_rl/agents/cem.py | 115 ++++++++++++++++++++++++++++++ fast_rl/agents/cem_models.py | 72 +++++++++++++++++++ fast_rl/agents/old_trpo.py | 27 ------- fast_rl/agents/old_trpo_models.py | 95 ------------------------ fast_rl/agents/trpo.py | 3 - fast_rl/core/agent_core.py | 3 + fast_rl/core/data_block.py | 22 +++--- fast_rl/core/metrics.py | 31 +++++++- tests/test_cem.py | 21 ++++++ tests/test_trpo.py | 43 ----------- 10 files changed, 253 insertions(+), 179 deletions(-) create mode 100644 fast_rl/agents/cem.py create mode 100644 fast_rl/agents/cem_models.py delete mode 100644 fast_rl/agents/old_trpo.py delete mode 100644 fast_rl/agents/old_trpo_models.py delete mode 100644 fast_rl/agents/trpo.py create mode 100644 tests/test_cem.py delete mode 100644 tests/test_trpo.py diff --git a/fast_rl/agents/cem.py b/fast_rl/agents/cem.py new file mode 100644 index 0000000..710cdec --- /dev/null +++ b/fast_rl/agents/cem.py @@ -0,0 +1,115 @@ +from typing import * + +import gym +from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify, OptimWrapper + +import numpy as np +from fastai.tabular import TabularModel +from torch import nn +from torch.distributions import Categorical +from torch.nn import Sequential + +from fast_rl.core.agent_core import ExplorationStrategy, Experience +from fast_rl.core.basic_train import AgentLearner +from fast_rl.core.data_block import MDPStep +from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper + + + +class EpisodeBuffer(Experience): + def __init__(self, memory_size,**kwargs): + super().__init__(memory_size,**kwargs) + self.episodes:List[Dict[str,List[MDPStep]]]=[{}] + self.current_episode_reward=0 + + def __len__(self): return len(self.episodes) + + def not_empty_episodes(self): return [e for e in self.episodes if e] + + def update(self, item, **kwargs): + if 'episode' not in self.episodes[-1]: self.episodes[-1]['episode']=[] + self.episodes[-1]['episode'].append(item) + self.current_episode_reward+=item.reward + if item.done: + self.episodes[-1]['reward']=self.current_episode_reward + self.current_episode_reward=0 + self.episodes.append({}) + + +class CEMTrainer(LearnerCallback): + def __init__(self, learn): + super().__init__(learn) + self.cache_loss=None + + def on_batch_begin(self,**kwargs): + return {'last_target':self.learn.data.x.items[-1].a.squeeze(0).to(device=self.learn.data.device)} + + def on_backward_begin(self,smooth_loss, **kwargs:Any): + self.cache_loss=ifnone(self.cache_loss,smooth_loss) + if len(self.learn.memory)None: + if self.learn.model.training: self.learn.memory.update(item=self.learn.data.x.items[-1]) + + +class Probabilistic(ExplorationStrategy): + def __init__(self): + super().__init__() + self.sm=nn.Softmax(dim=1) + + def perturb(self, action, action_space: gym.Space): + action=self.sm(action) + a_prob=action.squeeze(0).data.detach().cpu().numpy() + return np.random.choice(len(a_prob),p=a_prob) + + +class CEMLearner(AgentLearner): + def __init__(self, data,model,percentile=70,trainers=None,lr=0.01,exploration_strategy=None,**kwargs): + self.percentile=percentile + trainers=ifnone(trainers,CEMTrainer) + super().__init__(data=data, model=model,**kwargs) + self.opt=OptimWrapper.create(self.opt_func, lr=lr,layer_groups=[self.model.action_model]) + self.loss_func=nn.CrossEntropyLoss() + self.exploration_strategy=ifnone(exploration_strategy,Probabilistic()) + self.trainers=listify(trainers) + self.memory=EpisodeBuffer(self.data.batch_size) + for t in self.trainers: self.callbacks.append(t(self)) + + def filter_memory(self): + r=list(map(lambda x: x['reward'],self.memory.not_empty_episodes())) + r_boundary=np.percentile(r,self.percentile) + r_mean=float(np.mean(r)) + + s=[] + a=[] + for e in self.memory.not_empty_episodes(): + if e['reward'] bool: + if cv_l is None or len(cv_l)==0: return False + # gen a list of conv blocks based on the input size and the list of filter sizes + conv_blocks=[conv_bn_lrelu(_ni, nf, s, p, bn=use_bn) for _ni, nf, s, p in + zip([ni]+cv_l[:-1], cv_l[1:], stride, padding)] + fixed_conv_blocks=self.fix_switched_channels(ni, nc, conv_blocks) + self.action_model.add_module('conv_block', Sequential(fixed_conv_blocks+[Flatten()])) + return True + + def setup_linear_layers(self, ni, emb_szs, layers, ao, use_bn): + tabular_model=TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, + use_bn=use_bn) + if not emb_szs: tabular_model.embeds=None + if not use_bn: tabular_model.bn_cont=FakeBatchNorm() + self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) + + def forward(self, xi: Tensor): + training=self.training + if xi.shape[0]==1: self.eval() + pred=self.action_model(xi) + if training: self.train() + return pred +# +# class CEMModel(Module): +# def __init__(self, ni: int, na: int, layers: Optional[List[int]] = None, conv_layers: Optional[List[int]] = None, +# stride: Optional[List[int]] = None, padding: Optional[List[int]] = None, use_bn=False, +# nc: Optional[int] = None, model_base_line=0, +# w: Optional[int] = None, h: Optional[int] = None, embed_szs: Optional[List[int]] = None): +# super().__init__() +# self.action_model=nn.Sequential(nn.Linear(ni,layers[0]),nn.ReLU(),nn.Linear(layers[0],na)) +# +# def set_opt(self, opt): +# None +# +# def forward(self, xi: Tensor): +# training=self.training +# if xi.shape[0]==1: self.eval() +# pred=self.action_model(xi) +# if training: self.train() +# return pred \ No newline at end of file diff --git a/fast_rl/agents/old_trpo.py b/fast_rl/agents/old_trpo.py deleted file mode 100644 index b20205d..0000000 --- a/fast_rl/agents/old_trpo.py +++ /dev/null @@ -1,27 +0,0 @@ -from fastai.basic_train import LearnerCallback - -from fast_rl.core.agent_core import Experience, ExplorationStrategy -from fast_rl.core.basic_train import AgentLearner, listify, torch, Any, List -from fast_rl.core.data_block import MDPDataBunch, MDPStep - - -class TRPOLearner(AgentLearner): - def __init__(self,data:MDPDataBunch,model,memory,trainers,opt=torch.optim.RMSprop, - **learn_kwargs): - self.memory:Experience=memory - super().__init__(data=data,model=model,opt=opt,**learn_kwargs) - self.trainers=listify(trainers) - for t in self.trainers: self.callbacks.append(t(self)) - - -class TRPOTrainer(LearnerCallback): - @property - def learn(self)->TRPOLearner: - return self._learn() - - def on_loss_begin(self, **kwargs: Any): - """Performs tree updates, exploration updates, and model optimization.""" - if self.learn.model.training: self.learn.memory.update(item=self.learn.data.x.items[-1]) - if not self.learn.warming_up: - samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) - self.learn.model.optimize(samples,visitation_freq=1/len(self.learn.memory)) diff --git a/fast_rl/agents/old_trpo_models.py b/fast_rl/agents/old_trpo_models.py deleted file mode 100644 index bcc45b7..0000000 --- a/fast_rl/agents/old_trpo_models.py +++ /dev/null @@ -1,95 +0,0 @@ -from fastai.torch_core import * -from scipy.stats import entropy - - -class QModule(Module): - def __init__(self, ni, na): - super().__init__() - self.ni,self.na=ni,na - -class VModule(Module): - def __init__(self, ni): - super().__init__() - self.ni=ni - - -def kl_divergence(p: np.array, q: np.array): return entropy(p, q) -def advantage(s,a,q_net:QModule,v_net:VModule): return q_net(s,a)-v_net(s) - -def update_q(): pass -def update_v(): pass - - -class TRPOModule(Module): - """ - Implementation of the TRPO (Trust Region Policy Optimization) algorithm. - - Policy Gradient based algorithm for reinforcement learning in discrete - and continuous state and action spaces. Details of the algorithm's mathematical background can be found in [1]. - - References: - [1] (Schulman et al., 2017) Trust Region Policy Optimization. - """ - def __init__(self,ni:int,na:int,discount:float,fc_layers:List[int]=None,conv_filters:List[int]=None,nc=3,bn=False, - q_lr=1e-3,v_lr=1e-4,ks:List[int]=None,stride:List[int]=None,discrete:bool=True,paths='single', - n_timesteps=5,training=True,kl_e=0.1): - r""" - Implementation of the TRPO (Trust Region Policy Optimization) algorithm. - - Args: - ni: Number of inputs. Typically will be the number of dimensions of the state space. - na: Number of actions. Typically the number of action dimensions. - discount: Discount factor of q value estimation. - fc_layers: If the state input is not image based, then this is required. - conv_filters: Alternative image based state input/ - nc: Number of channels of input images - bn: Whether to use batch norm. If True typically produces unfavorable results, so default is False. - q_lr: Learning rate for the q value neural net. - v_lr: Learning rate for the v value neural net. - ks: Kernel size for conv layers for image based state inputs. - stride: Stride for conv layers for image based state inputs. - discrete: Whether the action space is discrete or not. - paths: TRPO has 2 options: vine or single paths. - n_timesteps: - """ - super().__init__() - self.kl_e=kl_e - self.discount=discount - self.discrete=discrete - self.q_net=QModule(ni,na) - self.v_net=VModule(ni) - self.training=True - - def forward(self, xi): - training = self.training - if xi.shape[0] == 1: self.eval() - pred = self.v_net(xi) - if training: self.train() - return pred - - def step(self,samples:List,visitation_freq:float): - # s_0 ~ p_0(s_0) - with torch.no_grad(): - r = torch.cat([item.reward.float() for item in samples]) - s_prime = torch.cat([item.s_prime for item in samples]) - s = torch.cat([item.s for item in samples]) - # [1] actions are chosen according to pi - a=self.forward(s) - - # p_pi(s) = P(s_0=s)+discount*P(s_1=s)+discount^2*P(s_2=s) ... - p=sum([visitation_freq*(self.discount**i) for i in range(len(samples))]) - # policy_prime(s) = argmax_a (A_pi (s,a)) - policy_prime=torch.argmax(advantage(s,a,self.q_net,self.v_net),1) - - adv=advantage(s,a,self.q_net,self.v_net) - - # C = (4*e*discount) / (1 - discount) ^ 2 - c=(4*self.kl_e*self.discount)/((1-self.discount)**2) - - v_net_target=deepcopy(self.v_net) - for target_param, local_param in zip(v_net_target.parameters(), self.v_net.parameters()): - # n(pi)= sum_s(p_pi(s) * sum_a (policy_prime(s,a)) * A(s,a)) - l_pi=target_param.data+p*sum(policy_prime*adv) - # pi_prime=L_pi(policy) - C * D(pi_i+1,pi) - target_param.data.copy_(l_pi-c*kl_divergence(target_param.data,local_param.data)) - diff --git a/fast_rl/agents/trpo.py b/fast_rl/agents/trpo.py deleted file mode 100644 index f764b17..0000000 --- a/fast_rl/agents/trpo.py +++ /dev/null @@ -1,3 +0,0 @@ - - -class GEAEstimator(): \ No newline at end of file diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index 419a675..64e2b49 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -84,6 +84,9 @@ def __init__(self, memory_size, reduce_ram=False): self.max_size=memory_size self.callbacks=[] + def __len__(self): + raise NotImplementedError('Experience needs a concept of size') + @property def memory(self): return None def sample(self, **kwargs): pass diff --git a/fast_rl/core/data_block.py b/fast_rl/core/data_block.py index 190cdca..ec56d95 100644 --- a/fast_rl/core/data_block.py +++ b/fast_rl/core/data_block.py @@ -393,10 +393,11 @@ class MDPStep(object): step: int def __post_init__(self): - self.action = deepcopy(self.action) - self.state = deepcopy(self.state) - self.reward = torch.tensor(data=self.reward).reshape(1, -1).float() - self.done = torch.tensor(data=self.done).reshape(1, -1).float() + with torch.no_grad(): + self.action = deepcopy(self.action) + self.state = deepcopy(self.state) + self.reward = torch.tensor(data=self.reward).reshape(1, -1).float() + self.done = torch.tensor(data=self.done).reshape(1, -1).float() def to(self, device): self.reward = self.reward.to(device=device) @@ -451,9 +452,10 @@ def __init__(self, learn, keep_env_open=True): def on_batch_begin(self, last_input, last_target, train, **kwargs: Any): r""" Set the Action of a dataset, determine if still warming up. """ a = self.learn.predict(last_input) - if self.learn.model.training: - self.train_ds.action = Action(taken_action=a, action_space=self.train_ds.action.action_space) - else: self.valid_ds.action = Action(taken_action=a, action_space=self.train_ds.action.action_space) + with torch.no_grad(): + if self.learn.model.training: + self.train_ds.action = Action(taken_action=a, action_space=self.train_ds.action.action_space) + else: self.valid_ds.action = Action(taken_action=a, action_space=self.train_ds.action.action_space) self.train_ds.is_warming_up = self.learn.warming_up if self.valid_ds is not None: self.valid_ds.is_warming_up = self.learn.warming_up if not self.learn.warming_up and self.learn.loss_func is None: self.learn.init_loss_func() @@ -655,9 +657,9 @@ def new(self, _): self.s_prime, reward, done, _, self.alt_s_prime = self.stage_2_env_step() # If both the current item and the done are both true, then we need to retry the env if self.item is not None and self.item.d and done: return self.new(_) - - self.state = State(s, self.s_prime, alt_s, self.alt_s_prime, self.env.observation_space, self.feed_type) - self.item = MDPStep(self.action, self.state, done, reward, self.episode, self.counter) + with torch.no_grad(): + self.state = State(s, self.s_prime, alt_s, self.alt_s_prime, self.env.observation_space, self.feed_type) + self.item = MDPStep(self.action, self.state, done, reward, self.episode, self.counter) self.counter += 1 return MDPList([self.item]) diff --git a/fast_rl/core/metrics.py b/fast_rl/core/metrics.py index 02d293b..e66b216 100644 --- a/fast_rl/core/metrics.py +++ b/fast_rl/core/metrics.py @@ -1,6 +1,9 @@ +from collections import deque + import torch -from fastai.basic_train import LearnerCallback, Any +from fastai.basic_train import LearnerCallback, Any, ifnone from fastai.callback import Callback, is_listy, add_metrics +import numpy as np class EpsilonMetric(LearnerCallback): @@ -43,3 +46,29 @@ def on_train_begin(self, **kwargs): def on_epoch_end(self, last_metrics, **kwargs: Any): return add_metrics(last_metrics, [sum(self.train_reward), sum(self.valid_reward)]) + +class RollingRewardMetric(LearnerCallback): + _order = -20 + + def __init__(self, learn,rolling_size=None): + super().__init__(learn) + self.rolling_sz=ifnone(rolling_size,self.learn.data.bs) + self.train_reward, self.valid_reward = [], [] + self.train_rolling_reward,self.valid_rolling_reward=deque([],maxlen=self.rolling_sz), deque([],maxlen=self.rolling_sz) + + def on_epoch_begin(self, **kwargs:Any): + self.train_reward, self.valid_reward = [], [] + + def on_batch_end(self, **kwargs: Any): + if self.learn.model.training: self.train_reward.append(self.learn.data.train_ds.item.reward.cpu().numpy()[0][0]) + elif not self.learn.recorder.no_val: self.valid_reward.append(self.learn.data.valid_ds.item.reward.cpu().numpy()[0][0]) + + def on_train_begin(self, **kwargs): + metric_names = ['train_rolling_reward'] if self.learn.recorder.no_val else ['train_rolling_reward', 'valid_rolling_reward'] + self.learn.recorder.add_metric_names(metric_names) + + def on_epoch_end(self, last_metrics, **kwargs: Any): + self.train_rolling_reward.append(sum(self.train_reward)) + self.valid_rolling_reward.append(sum(self.valid_reward)) + return add_metrics(last_metrics, [np.average(self.train_rolling_reward), np.average(self.valid_rolling_reward)]) + diff --git a/tests/test_cem.py b/tests/test_cem.py new file mode 100644 index 0000000..ec99d86 --- /dev/null +++ b/tests/test_cem.py @@ -0,0 +1,21 @@ +from fastai.tabular.data import emb_sz_rule + +from fast_rl.agents.cem import CEMLearner, CEMTrainer +from fast_rl.agents.cem_models import CEMModel +from fast_rl.core.data_block import MDPDataBunch +import numpy as np + +from fast_rl.core.metrics import RewardMetric, RollingRewardMetric + + +def test_cem(): + data=MDPDataBunch.from_env('CartPole-v0',render='human',add_valid=False,bs=16) + bs, state, action=data.bs, data.state, data.action + if np.any(state.n_possible_values==np.inf): + emb_szs=[] + else: + emb_szs=[(d+1, int(emb_sz_rule(d))) for d in state.n_possible_values.reshape(-1, )] + + model=CEMModel(4,2,embed_szs=emb_szs,layers=[128]) + reinforce_learner=CEMLearner(data,model,trainers=[CEMTrainer],callback_fns=[RewardMetric,RollingRewardMetric]) + reinforce_learner.fit(1000,lr=0.01) diff --git a/tests/test_trpo.py b/tests/test_trpo.py deleted file mode 100644 index 6616885..0000000 --- a/tests/test_trpo.py +++ /dev/null @@ -1,43 +0,0 @@ -from fast_rl.agents.old_trpo import TRPOLearner, TRPOTrainer -from fast_rl.agents.old_trpo_models import TRPOModule -from fast_rl.core.agent_core import ExperienceReplay -from fast_rl.core.data_block import MDPDataBunch - - -def test_trpo_learner_init_discrete(): - trpo_learner=TRPOLearner( - data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), - model=TRPOModule(4,2,0.001), - memory=ExperienceReplay(100), - trainers=TRPOTrainer - ) - -def test_trpo_learner_init_continuous(): - trpo_learner=TRPOLearner( - data=MDPDataBunch.from_env('AntPyBulletEnv-v0',bs=8,add_valid=False), - model=TRPOModule(4,8,0.001,discrete=False), - memory=ExperienceReplay(100), - trainers=TRPOTrainer - ) - - -def test_trpo_learner_discrete_fit(): - trpo_learner=TRPOLearner( - data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), - model=TRPOModule(4,2,0.001), - memory=ExperienceReplay(100), - trainers=TRPOTrainer - ) - trpo_learner.fit(4) - - -def test_trpo_model_calc_q(): - trpo_learner=TRPOLearner( - data=MDPDataBunch.from_env('CartPole-v1',bs=8,add_valid=False), - model=TRPOModule(4,2,0.001), - memory=ExperienceReplay(100), - trainers=TRPOTrainer - ) - -def test_trpo_model_calc_v(): pass -def test_trpo_model_calc_adv(): pass From 5a3094b9e549dcfbb05dc10a588f6780dbc029cc Mon Sep 17 00:00:00 2001 From: josiah Date: Sat, 29 Feb 2020 22:04:07 -0500 Subject: [PATCH 18/29] Fixed: - OK THIS IS BIG, WEIGHT DECAY FUCKS THINGS. This might mean that other RL models might perform better also with weight decay set to 0... --- fast_rl/agents/cem.py | 18 +++++++----------- fast_rl/agents/cem_models.py | 18 ------------------ tests/test_cem.py | 2 +- 3 files changed, 8 insertions(+), 30 deletions(-) diff --git a/fast_rl/agents/cem.py b/fast_rl/agents/cem.py index 710cdec..61190cf 100644 --- a/fast_rl/agents/cem.py +++ b/fast_rl/agents/cem.py @@ -1,19 +1,13 @@ from typing import * import gym -from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify, OptimWrapper - import numpy as np -from fastai.tabular import TabularModel +from fastai.basic_train import LearnerCallback, torch, ifnone, listify, OptimWrapper from torch import nn -from torch.distributions import Categorical -from torch.nn import Sequential from fast_rl.core.agent_core import ExplorationStrategy, Experience from fast_rl.core.basic_train import AgentLearner from fast_rl.core.data_block import MDPStep -from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper - class EpisodeBuffer(Experience): @@ -29,8 +23,8 @@ def not_empty_episodes(self): return [e for e in self.episodes if e] def update(self, item, **kwargs): if 'episode' not in self.episodes[-1]: self.episodes[-1]['episode']=[] self.episodes[-1]['episode'].append(item) - self.current_episode_reward+=item.reward - if item.done: + self.current_episode_reward+=item.reward.item() + if item.d: self.episodes[-1]['reward']=self.current_episode_reward self.current_episode_reward=0 self.episodes.append({}) @@ -88,19 +82,21 @@ def __init__(self, data,model,percentile=70,trainers=None,lr=0.01,exploration_st for t in self.trainers: self.callbacks.append(t(self)) def filter_memory(self): - r=list(map(lambda x: x['reward'],self.memory.not_empty_episodes())) + episodes=self.memory.not_empty_episodes() + r=list(map(lambda x: x['reward'],episodes)) r_boundary=np.percentile(r,self.percentile) r_mean=float(np.mean(r)) s=[] a=[] - for e in self.memory.not_empty_episodes(): + for e in episodes: if e['reward'] Date: Sat, 29 Feb 2020 22:10:40 -0500 Subject: [PATCH 19/29] Changed: - current cem test is now flagged as a performance test. --- fast_rl/agents/cem.py | 4 ++-- tests/test_cem.py | 4 +++- 2 files changed, 5 insertions(+), 3 deletions(-) diff --git a/fast_rl/agents/cem.py b/fast_rl/agents/cem.py index 61190cf..bf8d93e 100644 --- a/fast_rl/agents/cem.py +++ b/fast_rl/agents/cem.py @@ -70,10 +70,10 @@ def perturb(self, action, action_space: gym.Space): class CEMLearner(AgentLearner): - def __init__(self, data,model,percentile=70,trainers=None,lr=0.01,exploration_strategy=None,**kwargs): + def __init__(self, data,model,percentile=70,trainers=None,lr=0.01,exploration_strategy=None,wd=0,**kwargs): self.percentile=percentile trainers=ifnone(trainers,CEMTrainer) - super().__init__(data=data, model=model,**kwargs) + super().__init__(data=data, model=model,wd=wd,**kwargs) self.opt=OptimWrapper.create(self.opt_func, lr=lr,layer_groups=[self.model.action_model]) self.loss_func=nn.CrossEntropyLoss() self.exploration_strategy=ifnone(exploration_strategy,Probabilistic()) diff --git a/tests/test_cem.py b/tests/test_cem.py index b13ba50..40db469 100644 --- a/tests/test_cem.py +++ b/tests/test_cem.py @@ -1,3 +1,4 @@ +import pytest from fastai.tabular.data import emb_sz_rule from fast_rl.agents.cem import CEMLearner, CEMTrainer @@ -8,6 +9,7 @@ from fast_rl.core.metrics import RewardMetric, RollingRewardMetric +@pytest.mark.usefixtures('skip_performance_check') def test_cem(): data=MDPDataBunch.from_env('CartPole-v0',render='human',add_valid=False,bs=16) bs, state, action=data.bs, data.state, data.action @@ -18,4 +20,4 @@ def test_cem(): model=CEMModel(4,2,embed_szs=emb_szs,layers=[128]) reinforce_learner=CEMLearner(data,model,trainers=[CEMTrainer],callback_fns=[RewardMetric,RollingRewardMetric]) - reinforce_learner.fit(1000,lr=0.01,wd=0) + reinforce_learner.fit(600,lr=0.01,wd=0) From cab3452d39cc78d6d277b969d698303936745924 Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 1 Mar 2020 16:21:18 -0500 Subject: [PATCH 20/29] Added: - NStep Experience replay. Very very promising --- fast_rl/agents/cem.py | 1 - fast_rl/core/agent_core.py | 40 ++++++++++++++++++++++++++++++++++++++ tests/test_dqn.py | 20 ++++++++++++++++--- 3 files changed, 57 insertions(+), 4 deletions(-) diff --git a/fast_rl/agents/cem.py b/fast_rl/agents/cem.py index bf8d93e..280fb58 100644 --- a/fast_rl/agents/cem.py +++ b/fast_rl/agents/cem.py @@ -96,7 +96,6 @@ def filter_memory(self): return s,a,r_boundary,r_mean def optimize(self): - self.opt.zero_grad() s,a,boundary,r_mean=self.filter_memory() s,a=torch.cat(s).to(device=self.data.device),torch.cat(a).to(device=self.data.device).squeeze(1) a_scores=self.model(s) diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index 64e2b49..b31279b 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -128,6 +128,46 @@ def update(self, item, **kwargs): self._memory.append(item) +class NStepExperienceReplay(Experience): + def __init__(self, memory_size,step_sz=2,**kwargs): + r""" + Basic store-er of s space transitions for training agents. + + References: + [1] Mnih, Volodymyr, et al. "Playing atari with deep reinforcement learning." + arXiv preprint arXiv:1312.5602 (2013). + + Args: + memory_size (int): Max N samples to store + """ + super().__init__(memory_size, **kwargs) + self.step_sz=step_sz + self.max_size=memory_size + self._memory=deque(maxlen=memory_size) + + @property + def memory(self): + return self._memory + + def __len__(self): + return len(self._memory) + + def sample(self, batch, **kwargs): + if len(self._memory) Date: Sun, 1 Mar 2020 18:13:50 -0500 Subject: [PATCH 21/29] Added: - guassian noise layers. They do not seem to improve performance on cartpole, but may do better on Atari games - ROADMAP items --- README.md | 21 ++-- ROADMAP.md | 24 +++-- fast_rl/agents/dqn_models.py | 15 +-- fast_rl/core/agent_core.py | 2 +- fast_rl/core/layers.py | 203 ++++++++++++++++++++++++++--------- tests/test_dqn.py | 66 +++++------- 6 files changed, 219 insertions(+), 112 deletions(-) diff --git a/README.md b/README.md index 22196b2..a9ab6b4 100644 --- a/README.md +++ b/README.md @@ -108,11 +108,14 @@ OpenAI environments. ## RoadMap -- [ ] **Working on** **1.0.0** Base version is completed with working model visualizations proving performance / expected failure. At -this point, all models should have guaranteed environments they should succeed in. - [ ] 1.1.0 More Traditional RL models - - [ ] Add PPO - - [ ] Add TRPO + - [X] Add Cross Entropy Method CEM + - [X] NStep Experience replay + - [X] Gaussian and Factored Gaussian Noise exploration replacement + - [ ] Add RAINBOW DQN + - [ ] **Working on** Add REINFORCE + - [ ] **Working on** Add PPO + - [ ] **Working on** Add TRPO - [ ] Add D4PG - [ ] Add A2C - [ ] Add A3C @@ -143,10 +146,12 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Skills augmentation to DQN based models - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models -- [ ] 1.9.0 -- [ ] 2.0.0 Add PyBullet Fetch Environments - - [ ] 2.0.0 Not part of this repo, however the envs need to subclass the OpenAI `gym.GoalEnv` - - [ ] 2.0.0 Add HER +- [ ] 1.9.0 Add PyBullet Fetch Environments + - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` + - [ ] Add HER +- [ ] 2.0.0 Breaking refactor of all methods + - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second. + - [ ] Unify common code pieces shared in all models ## Contribution diff --git a/ROADMAP.md b/ROADMAP.md index 805a12b..b381f3e 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -1,11 +1,16 @@ - [X] 0.7.0 Full test suite using multi-processing. Connect to CI. - [X] 0.8.0 Comprehensive model eval **debug/verify**. Each model should succeed at at least a few known environments. Also, massive refactoring will be needed. - [X] 0.9.0 Notebook demonstrations of basic model usage. -- [ ] **Working on** **1.0.0** Base version is completed with working model visualizations proving performance / expected failure. At +- [X] **1.0.0** Base version is completed with working model visualizations proving performance / expected failure. At this point, all models should have guaranteed environments they should succeed in. - [ ] 1.1.0 More Traditional RL models - - [ ] Add PPO - - [ ] Add TRPO + - [X] Add Cross Entropy Method CEM + - [X] NStep Experience replay + - [X] Gaussian and Factored Gaussian Noise exploration replacement + - [ ] Add RAINBOW DQN + - [ ] **Working on** Add REINFORCE + - [ ] **Working on** Add PPO + - [ ] **Working on** Add TRPO - [ ] Add D4PG - [ ] Add A2C - [ ] Add A3C @@ -27,6 +32,7 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Add STRategic Attentive Writer (STRAW) - [ ] Add H-DRLN - [ ] Add Abstract Markov Decision Process (AMDP) + - [ ] Add conda integration so that installation can be truly one step. - [ ] 1.6.0 HRL Options models *Possibly will already be implemented in a previous model* - [ ] Options augmentation to DQN based models - [ ] Options augmentation to actor critic models @@ -35,7 +41,11 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Skills augmentation to DQN based models - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models -- [ ] 1.9.0 -- [ ] 2.0.0 Add PyBullet Fetch Environments - - [ ] 2.0.0 Not part of this repo, however the envs need to subclass the OpenAI `gym.GoalEnv` - - [ ] 2.0.0 Add HER \ No newline at end of file +- [ ] 1.9.0 Add PyBullet Fetch Environments + - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` + - [ ] Add HER +- [ ] 2.0.0 Breaking refactor of all methods + - [ ] Move to fastai 2.0 + - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second + - [ ] fastrl needs to handle ram better + - [ ] Unify common code pieces shared in all models \ No newline at end of file diff --git a/fast_rl/agents/dqn_models.py b/fast_rl/agents/dqn_models.py index f4d6306..a0014ae 100644 --- a/fast_rl/agents/dqn_models.py +++ b/fast_rl/agents/dqn_models.py @@ -8,7 +8,7 @@ class DQNModule(Module): def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = 0.99, lr=0.001, n_conv_blocks: Collection[int] = 0, nc=3, opt=None, emb_szs: ListSizes = None, loss_func=None, w=-1, h=-1, ks: Union[None, list]=None, stride: Union[None, list]=None, grad_clip=5, - conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False): + conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False,lin_cls=nn.Linear): r""" Basic DQN Module. @@ -21,6 +21,7 @@ def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = nc: Number of channels that will be expected by the convolutional blocks. """ super().__init__() + self.lin_cls=lin_cls self.name = 'DQN' self.loss = None self.loss_func = loss_func @@ -52,7 +53,7 @@ def setup_conv_block(self, _layers, ni, nc, w, h): return ni def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): - tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, use_bn=self.batch_norm) + tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, use_bn=self.batch_norm,lin_cls=self.lin_cls) if not emb_szs: tabular_model.embeds = None if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) @@ -72,7 +73,7 @@ def forward(self, xi: Tensor): return pred def init_weights(self, m): - if type(m) == nn.Linear: + if issubclass(m.__class__,nn.Linear): torch.nn.init.xavier_uniform_(m.weight) m.bias.data.fill_(0.01) @@ -162,11 +163,11 @@ def calc_y(self, s_prime, masking, r, y_hat): class DuelingBlock(nn.Module): - def __init__(self, ao, stream_input_size): + def __init__(self, ao, stream_input_size,lin_cls=nn.Linear): super().__init__() - self.val = nn.Linear(stream_input_size, 1) - self.adv = nn.Linear(stream_input_size, ao) + self.val = lin_cls(stream_input_size, 1) + self.adv = lin_cls(stream_input_size, ao) def forward(self, xi): r"""Splits the base neural net output into 2 streams to evaluate the advantage and v of the s space and @@ -189,7 +190,7 @@ def __init__(self, **kwargs): def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, - use_bn=self.batch_norm) + use_bn=self.batch_norm,lin_cls=self.lin_cls) if not emb_szs: tabular_model.embeds = None if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() tabular_model.layers, removed_layer = split_model(tabular_model.layers, [last_layer(tabular_model)]) diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index b31279b..b093e2f 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -10,7 +10,7 @@ class ExplorationStrategy: def __init__(self, explore: bool = True): self.explore=explore - def update(self, max_episodes, explore, **kwargs): self.explore=explore + def update(self,episode, max_episodes, explore, **kwargs): self.explore=explore def perturb(self, action, action_space) -> np.ndarray: """ Base method just returns the action. Subclass, and change to return randomly / augmented actions. diff --git a/fast_rl/core/layers.py b/fast_rl/core/layers.py index 3009f25..44220a2 100644 --- a/fast_rl/core/layers.py +++ b/fast_rl/core/layers.py @@ -1,89 +1,190 @@ r"""`fast_rl.layers` provides essential functions to building and modifying `model` architectures""" from math import ceil +from fastai.layers import embedding from fastai.torch_core import * -from fastai.tabular import TabularModel +from torch.distributions import Normal + + +def bn_drop_lin(n_in:int, n_out:int, bn:bool=True, p:float=0., actn:Optional[nn.Module]=None,lin_cls=nn.Linear): + "Sequence of batchnorm (if `bn`), dropout (with `p`) and linear (`n_in`,`n_out`) layers followed by `actn`." + layers = [nn.BatchNorm1d(n_in)] if bn else [] + if p != 0: layers.append(nn.Dropout(p)) + layers.append(lin_cls(n_in, n_out)) + if actn is not None: layers.append(actn) + return layers + + +class TabularModel(Module): + "Basic model for tabular data." + def __init__(self, emb_szs:ListSizes, n_cont:int, out_sz:int, layers:Collection[int], ps:Collection[float]=None, + emb_drop:float=0., y_range:OptRange=None, use_bn:bool=True, bn_final:bool=False,lin_cls=nn.Linear): + super().__init__() + ps = ifnone(ps, [0]*len(layers)) + ps = listify(ps, layers) + self.embeds = nn.ModuleList([embedding(ni, nf) for ni,nf in emb_szs]) + self.emb_drop = nn.Dropout(emb_drop) + self.bn_cont = nn.BatchNorm1d(n_cont) + n_emb = sum(e.embedding_dim for e in self.embeds) + self.n_emb,self.n_cont,self.y_range = n_emb,n_cont,y_range + sizes = self.get_sizes(layers, out_sz) + actns = [nn.ReLU(inplace=True) for _ in range(len(sizes)-2)] + [None] + layers = [] + for i,(n_in,n_out,dp,act) in enumerate(zip(sizes[:-1],sizes[1:],[0.]+ps,actns)): + layers += bn_drop_lin(n_in, n_out, bn=use_bn and i!=0, p=dp, actn=act,lin_cls=lin_cls) + if bn_final: layers.append(nn.BatchNorm1d(sizes[-1])) + self.layers = nn.Sequential(*layers) + + def get_sizes(self, layers, out_sz): + return [self.n_emb + self.n_cont] + layers + [out_sz] + + def forward(self, x_cat:Tensor, x_cont:Tensor) -> Tensor: + if self.n_emb != 0: + x = [e(x_cat[:,i]) for i,e in enumerate(self.embeds)] + x = torch.cat(x, 1) + x = self.emb_drop(x) + if self.n_cont != 0: + x_cont = self.bn_cont(x_cont) + x = torch.cat([x, x_cont], 1) if self.n_emb != 0 else x_cont + x = self.layers(x) + if self.y_range is not None: + x = (self.y_range[1]-self.y_range[0]) * torch.sigmoid(x) + self.y_range[0] + return x def init_cnn(mod: Any): - r""" Utility for initializing cnn Modules. """ - if getattr(mod, 'bias', None) is not None: nn.init.constant_(mod.bias, 0) - if isinstance(mod, (nn.Conv2d, nn.Linear)): nn.init.kaiming_normal_(mod.weight) - for sub_mod in mod.children(): init_cnn(sub_mod) + r""" Utility for initializing cnn Modules. """ + if getattr(mod, 'bias', None) is not None: nn.init.constant_(mod.bias, 0) + if isinstance(mod, (nn.Conv2d, nn.Linear)): nn.init.kaiming_normal_(mod.weight) + for sub_mod in mod.children(): init_cnn(sub_mod) def ks_stride(ks, stride, w, h, n_blocks, kern_proportion=.1, stride_proportion=0.3): - r""" Utility for determing the the kernel size and stride. """ - kernels, strides, max_dim = [], [], max((w, h)) - for i in range(len(n_blocks)): - kernels.append(max_dim * kern_proportion) - strides.append(kernels[-1] * stride_proportion) - max_dim = (max_dim - kernels[-1]) / strides[-1] - assert max_dim > 1 + r""" Utility for determing the the kernel size and stride. """ + kernels, strides, max_dim=[], [], max((w, h)) + for i in range(len(n_blocks)): + kernels.append(max_dim*kern_proportion) + strides.append(kernels[-1]*stride_proportion) + max_dim=(max_dim-kernels[-1])/strides[-1] + assert max_dim>1 - return ifnone(ks, map(ceil, kernels)), ifnone(stride, map(ceil, strides)) + return ifnone(ks, map(ceil, kernels)), ifnone(stride, map(ceil, strides)) class Flatten(nn.Module): - def forward(self, y): return y.view(y.size(0), -1) + def forward(self, y): return y.view(y.size(0), -1) class FakeBatchNorm(Module): - r""" If we want all the batch norm layers gone, then we will replace the tabular batch norm with this. """ - def forward(self, xi: Tensor, *args): return xi + r""" If we want all the batch norm layers gone, then we will replace the tabular batch norm with this. """ + def forward(self, xi: Tensor, *args): return xi + + +class GaussianNoisyLinear(nn.Linear): + def __init__(self, in_features, out_features, sigma_init=0.017, bias=True): + super().__init__(in_features, out_features, bias=bias) + self.sigma_weight=nn.Parameter(torch.full((out_features, in_features), sigma_init)) + self.register_buffer("epsilon_weight",torch.zeros(out_features,in_features)) + self.normal=Normal(0,1) + if bias: + self.sigma_bias=nn.Parameter(torch.full((out_features,),sigma_init)) + self.register_buffer("epsilon_bias", torch.zeros(out_features)) + self.reset_parameters() + + def reset_parameters(self): + std=math.sqrt(3/self.in_features) + self.weight.data.uniform_(-std,std) + self.bias.data.uniform_(-std,std) + + def forward(self, xi): + # self.normal=Normal(0,1) + self.epsilon_weight.data.copy_(self.normal.sample(self.epsilon_weight.shape)) + bias=self.bias + if bias is not None: + # self.epsilon_bias.normal_() + self.epsilon_bias.data.copy_(self.normal.sample(self.epsilon_bias.shape)) + bias=bias+self.sigma_bias*self.epsilon_bias + return F.linear(xi,self.weight+self.sigma_weight*self.epsilon_weight,bias) + + +class GaussianNoisyFactorizedLinear(nn.Linear): + def __init__(self, in_features, out_features,sigma_zero=0.4,bias=True): + super().__init__(in_features, out_features,bias=bias) + sigma_init=sigma_zero/math.sqrt(in_features) + self.sigma_weight=nn.Parameter(torch.full((out_features,in_features),sigma_init)) + self.register_buffer("epsilon_input",torch.zeros((1,in_features))) + self.register_buffer("epsilon_output", torch.zeros((out_features,1))) + if bias: + self.sigma_bias=nn.Parameter(torch.full((out_features,),sigma_init)) + + def square_direction(self,x): return torch.sign(x)*torch.sqrt(torch.abs(x)) + + def forward(self, xi): + self.epsilon_input.normal_() + self.epsilon_output.normal_() + + eps_in,eps_out=self.square_direction(self.epsilon_input),self.square_direction(self.epsilon_output) + + bias=self.bias + if bias is not None: + bias=bias+self.sigma_bias*eps_out.t() + noise_v=torch.mul(eps_in,eps_out) + return F.linear(xi,self.weight+self.sigma_weight*noise_v,bias) + def conv_bn_lrelu(ni: int, nf: int, ks: int = 3, stride: int = 1, pad=True, bn=True) -> nn.Sequential: - r""" Create a sequence Conv2d->BatchNorm2d->LeakyReLu layer. (from darknet.py). Allows excluding BatchNorm2d Layer.""" - return nn.Sequential( - nn.Conv2d(ni, nf, kernel_size=ks, bias=False, stride=stride, padding=(ks // 2) if pad else 0), - nn.BatchNorm2d(nf) if bn else FakeBatchNorm(), - nn.LeakyReLU(negative_slope=0.1, inplace=True)) + r""" Create a sequence Conv2d->BatchNorm2d->LeakyReLu layer. (from darknet.py). Allows excluding BatchNorm2d Layer.""" + return nn.Sequential( + nn.Conv2d(ni, nf, kernel_size=ks, bias=False, stride=stride, padding=(ks//2) if pad else 0), + nn.BatchNorm2d(nf) if bn else FakeBatchNorm(), + nn.LeakyReLU(negative_slope=0.1, inplace=True)) class ChannelTranspose(Module): - r""" Runtime image input channel changing. Useful for handling different image channel outputs from different envs. """ - def forward(self, xi: Tensor): - return xi.transpose(3, 1).transpose(3, 2) + r""" Runtime image input channel changing. Useful for handling different image channel outputs from different envs. """ + def forward(self, xi: Tensor): + return xi.transpose(3, 1).transpose(3, 2) class StateActionSplitter(Module): - r""" `Actor / Critic` models require breaking the state and action into 2 streams. """ + r""" `Actor / Critic` models require breaking the state and action into 2 streams. """ - def forward(self, s_a_tuple: Tuple[Tensor]): - r""" Returns tensors as -> (State Tensor, Action Tensor) """ - return s_a_tuple[0], s_a_tuple[1] + def forward(self, s_a_tuple: Tuple[Tensor]): + r""" Returns tensors as -> (State Tensor, Action Tensor) """ + return s_a_tuple[0], s_a_tuple[1] class StateActionPassThrough(nn.Module): - r""" Passes action input untouched, but runs the state tensors through a sub module. """ - def __init__(self, layers): - super().__init__() - self.layers = layers + r""" Passes action input untouched, but runs the state tensors through a sub module. """ + def __init__(self, layers): + super().__init__() + self.layers=layers - def forward(self, state_action): - return self.layers(state_action[0]), state_action[1] + def forward(self, state_action): + return self.layers(state_action[0]), state_action[1] class TabularEmbedWrapper(Module): - r""" Basic `TabularModel` compatibility wrapper. Typically, state inputs will be either categorical or continuous. """ - def __init__(self, tabular_model: TabularModel): - super().__init__() - self.tabular_model = tabular_model + r""" Basic `TabularModel` compatibility wrapper. Typically, state inputs will be either categorical or continuous. """ + def __init__(self, tabular_model: TabularModel): + super().__init__() + self.tabular_model=tabular_model - def forward(self, xi: Tensor, *args): - return self.tabular_model(xi, xi) + def forward(self, xi: Tensor, *args): + return self.tabular_model(xi, xi) class CriticTabularEmbedWrapper(Module): - r""" Similar to `TabularEmbedWrapper` but assumes input is state / action and requires concatenation. """ - def __init__(self, tabular_model: TabularModel, exclude_cat): - super().__init__() - self.tabular_model = tabular_model - self.exclude_cat = exclude_cat - - def forward(self, args): - if not self.exclude_cat: - return self.tabular_model(*args) - else: - return self.tabular_model(0, torch.cat(args, 1)) + r""" Similar to `TabularEmbedWrapper` but assumes input is state / action and requires concatenation. """ + def __init__(self, tabular_model: TabularModel, exclude_cat): + super().__init__() + self.tabular_model=tabular_model + self.exclude_cat=exclude_cat + + def forward(self, args): + if not self.exclude_cat: + return self.tabular_model(*args) + else: + return self.tabular_model(0, torch.cat(args, 1)) + diff --git a/tests/test_dqn.py b/tests/test_dqn.py index f2547f5..b8f8b08 100644 --- a/tests/test_dqn.py +++ b/tests/test_dqn.py @@ -6,7 +6,8 @@ from fast_rl.agents.dqn import create_dqn_model, dqn_learner, DQNLearner from fast_rl.agents.dqn_models import * -from fast_rl.core.agent_core import ExperienceReplay, PriorityExperienceReplay, GreedyEpsilon, NStepExperienceReplay +from fast_rl.core.agent_core import ExperienceReplay, PriorityExperienceReplay, GreedyEpsilon, NStepExperienceReplay, \ + ExplorationStrategy from fast_rl.core.data_block import MDPDataBunch, FEED_TYPE_STATE, FEED_TYPE_IMAGE, ResolutionWrapper from fast_rl.core.metrics import RewardMetric, EpsilonMetric, RollingRewardMetric from fast_rl.core.train import GroupAgentInterpretation, AgentInterpretation @@ -14,7 +15,7 @@ p_model = [DQNModule, FixedTargetDQNModule,DoubleDuelingModule,DuelingDQNModule,DoubleDQNModule] p_exp = [ExperienceReplay, - PriorityExperienceReplay] + PriorityExperienceReplay,NStepExperienceReplay] p_format = [FEED_TYPE_STATE]#, FEED_TYPE_IMAGE] p_envs = ['CartPole-v1'] @@ -37,17 +38,19 @@ def learner2gif(lnr:DQNLearner,s_format,group_interp:GroupAgentInterpretation,na def trained_learner(model_cls, env, s_format, experience, bs, layers, memory_size=1000000, decay=0.001, - copy_over_frequency=300, lr=None, epochs=450,**kwargs): + copy_over_frequency=300, lr=None, epochs=450,lin_cls=None,explore=None,**kwargs): if lr is None: lr = [0.001, 0.00025] memory = experience(memory_size=memory_size, reduce_ram=True) - explore = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=decay) + metrics=[RewardMetric, RollingRewardMetric] + if explore is None: metrics.append(EpsilonMetric) + explore = ifnone(explore,GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=decay)) if type(lr) == list: lr = lr[0] if model_cls == DQNModule else lr[1] data = MDPDataBunch.from_env(env, render='human', bs=bs, add_valid=False, keep_env_open=False, feed_type=s_format, memory_management_strategy='k_partitions_top', k=3,**kwargs) - if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.RMSprop) - else: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers) + if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.RMSprop,lin_cls=ifnone(lin_cls,nn.Linear)) + else: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers,lin_cls=ifnone(lin_cls,nn.Linear)) learn = dqn_learner(data, model, memory=memory, exploration_method=explore, copy_over_frequency=copy_over_frequency, - callback_fns=[RewardMetric, EpsilonMetric,RollingRewardMetric]) + callback_fns=metrics) learn.fit(epochs) return learn @@ -103,28 +106,6 @@ def test_dqn_fit_maze_env(model_cls, s_format, mem): memory_size=1000000, decay=0.00001, res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3)) learner2gif(learn,s_format,group_interp,'maze_5x5',extra_s) - # success = False - # while not success: - # try: - # data = MDPDataBunch.from_env('maze-random-5x5-v0', render='rgb_array', bs=5, max_steps=20, - # add_valid=False, keep_env_open=False, feed_type=s_format) - # model = create_dqn_model(data, model_cls, opt=torch.optim.RMSprop) - # memory = ExperienceReplay(10000) - # exploration_method = GreedyEpsilon(epsilon_start=1, epsilon_end=0.1, decay=0.001) - # learner = dqn_learner(data=data, model=model, memory=memory, exploration_method=exploration_method, - # callback_fns=[RewardMetric, EpsilonMetric]) - # learner.fit(2) - # - # assert config_env_expectations['maze-random-5x5-v0']['action_shape'] == ( - # 1, data.action.n_possible_values.item()) - # if s_format == FEED_TYPE_STATE: - # assert config_env_expectations['maze-random-5x5-v0']['state_shape'] == data.state.s.shape - # sleep(1) - # success = True - # except Exception as e: - # if not str(e).__contains__('Surface'): - # raise Exception - @pytest.mark.usefixtures('skip_performance_check') @pytest.mark.parametrize(["model_cls", "s_format", 'experience'], list(product(p_model, p_format, p_exp))) @@ -155,15 +136,6 @@ def test_dqn_models_cartpole(model_cls, s_format, experience): memory_size=1000000, decay=0.001) learner2gif(learn,s_format,group_interp,'cartpole',extra_s) - # meta = f'{experience.__name__}_{"FEED_TYPE_STATE" if s_format == FEED_TYPE_STATE else "FEED_TYPE_IMAGE"}' - # interp = AgentInterpretation(learn, ds_type=DatasetType.Train) - # interp.plot_rewards(cumulative=True, per_episode=True, group_name=meta) - # group_interp.add_interpretation(interp) - # filename = f'{learn.model.name.lower()}_{meta}' - # group_interp.to_pickle(f'../docs_src/data/cartpole_{learn.model.name.lower()}/', filename) - # [g.write('../res/run_gifs/cartpole') for g in interp.generate_gif()] - # del learn - @pytest.mark.usefixtures('skip_performance_check') @pytest.mark.parametrize(["model_cls", "s_format"], @@ -179,6 +151,24 @@ def test_dqn_models_nstep_cartpole(model_cls, s_format): learner2gif(learn,s_format,group_interp,'cartpole',extra_s) +layer_clss=[GaussianNoisyLinear,GaussianNoisyFactorizedLinear] + + +@pytest.mark.usefixtures('skip_performance_check') +@pytest.mark.parametrize(["model_cls", "s_format",'layer_cls'], + list(product(p_model, p_format,layer_clss))) +def test_dqn_models_noisy_layers_cartpole(model_cls, s_format,layer_cls): + experience=NStepExperienceReplay + group_interp = GroupAgentInterpretation() + extra_s=f'{experience.__name__}_{model_cls.__name__}_{s_format}_{layer_cls.__name__}' + for i in range(1): + # Since we are using noisy layers, just use default exploration strategy (no exploration) + learn = trained_learner(model_cls, 'CartPole-v1', s_format, experience, bs=32, layers=[64, 64], + memory_size=1000000, decay=0.001,lin_cls=layer_cls,explore=ExplorationStrategy(),epochs=450) + + learner2gif(learn,s_format,group_interp,'cartpole_layer_exp',extra_s) + + @pytest.mark.usefixtures('skip_performance_check') @pytest.mark.parametrize(["model_cls", "s_format", 'experience'], list(product(p_model, p_format, p_exp))) def test_dqn_models_lunarlander(model_cls, s_format, experience): From af78818f3be46e3a34ee3cea8865a5ab4a63f79b Mon Sep 17 00:00:00 2001 From: josiah Date: Sun, 1 Mar 2020 21:21:51 -0500 Subject: [PATCH 22/29] Fixed: - Greedy epsilon crashing lol --- README.md | 2 ++ ROADMAP.md | 4 +++- fast_rl/core/agent_core.py | 2 +- 3 files changed, 6 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index a9ab6b4..2fe6160 100644 --- a/README.md +++ b/README.md @@ -112,6 +112,7 @@ OpenAI environments. - [X] Add Cross Entropy Method CEM - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement + - [ ] Distributional DQN - [ ] Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO @@ -119,6 +120,7 @@ OpenAI environments. - [ ] Add D4PG - [ ] Add A2C - [ ] Add A3C + - [ ] Add SAC - [ ] 1.2.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* - [ ] Add SMDP - [ ] Add Goal oriented MDPs. Will Require a new "Step" diff --git a/ROADMAP.md b/ROADMAP.md index b381f3e..552b112 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -7,13 +7,15 @@ this point, all models should have guaranteed environments they should succeed i - [X] Add Cross Entropy Method CEM - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - - [ ] Add RAINBOW DQN + - [ ] **Working on** Add Distributional DQN + - [ ] **Working on** Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO - [ ] Add D4PG - [ ] Add A2C - [ ] Add A3C + - [ ] Add SAC - [ ] 1.2.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* - [ ] Add SMDP - [ ] Add Goal oriented MDPs. Will Require a new "Step" diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index b093e2f..361ef0a 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -42,7 +42,7 @@ def perturb(self, action, action_space: gym.Space): return action_space.sample() if np.random.random() Date: Sun, 1 Mar 2020 21:30:42 -0500 Subject: [PATCH 23/29] Fixed: - old reinforcement failing unit tests. --- tests/test_reinforce.py | 32 -------------------------------- 1 file changed, 32 deletions(-) delete mode 100644 tests/test_reinforce.py diff --git a/tests/test_reinforce.py b/tests/test_reinforce.py deleted file mode 100644 index 4495038..0000000 --- a/tests/test_reinforce.py +++ /dev/null @@ -1,32 +0,0 @@ -from fastai.core import ifnone, np -from fastai.tabular.data import emb_sz_rule - -from fast_rl.agents.reinforce import REINFORCELearner, REINFORCEStepWiseTrainer, REINFORCEEpisodicTrainer -from fast_rl.agents.reinforce_models import REINFORCEModel -from fast_rl.core.data_block import MDPDataBunch, FEED_TYPE_STATE, partial, ResolutionWrapper - - -def test_reinforce_fit_step_wise(): - data=MDPDataBunch.from_env('maze-random-5x5-v0',max_steps=100,render='human',k=0, res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3),add_valid=False) - bs, state, action=data.bs, data.state, data.action - if np.any(state.n_possible_values==np.inf): - emb_szs=[] - else: - emb_szs=[(d+1, int(emb_sz_rule(d))) for d in state.n_possible_values.reshape(-1, )] - - model=REINFORCEModel(2,2,embed_szs=emb_szs) - reinforce_learner=REINFORCELearner(data,model,trainers=[REINFORCEStepWiseTrainer]) - reinforce_learner.fit(450,lr=0.005) - -def test_reinforce_fit_episodic(): - data=MDPDataBunch.from_env('maze-random-5x5-v0',max_steps=100,render='human',k=0, - res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3),add_valid=False,device='cpu') - bs, state, action=data.bs, data.state, data.action - if np.any(state.n_possible_values==np.inf): - emb_szs=[] - else: - emb_szs=[(d+1, int(emb_sz_rule(d))) for d in state.n_possible_values.reshape(-1, )] - - model=REINFORCEModel(2,2,embed_szs=emb_szs) - reinforce_learner=REINFORCELearner(data,model,trainers=[REINFORCEEpisodicTrainer]) - reinforce_learner.fit(450,lr=0.005) \ No newline at end of file From bc1c2b939f81b7f8e70f34ef8251ccbd35cd4b7f Mon Sep 17 00:00:00 2001 From: josiah Date: Fri, 6 Mar 2020 18:22:01 -0500 Subject: [PATCH 24/29] Changed: - resolution wrapper handles other returns from render better Added: - distributional dqn. Does not seem to work well with cartpole, investigating --- README.md | 2 +- ROADMAP.md | 2 +- fast_rl/agents/dqn.py | 3 +- fast_rl/agents/dqn_models.py | 435 +++++++++++++++++++++-------------- fast_rl/core/basic_train.py | 2 +- fast_rl/core/data_block.py | 2 +- tests/test_dqn.py | 31 ++- 7 files changed, 293 insertions(+), 184 deletions(-) diff --git a/README.md b/README.md index 2fe6160..10c840b 100644 --- a/README.md +++ b/README.md @@ -112,7 +112,7 @@ OpenAI environments. - [X] Add Cross Entropy Method CEM - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - - [ ] Distributional DQN + - [X] Distributional DQN - [ ] Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO diff --git a/ROADMAP.md b/ROADMAP.md index 552b112..53513f0 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -7,7 +7,7 @@ this point, all models should have guaranteed environments they should succeed i - [X] Add Cross Entropy Method CEM - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - - [ ] **Working on** Add Distributional DQN + - [X] Add Distributional DQN - [ ] **Working on** Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO diff --git a/fast_rl/agents/dqn.py b/fast_rl/agents/dqn.py index 04a5afa..d60b825 100644 --- a/fast_rl/agents/dqn.py +++ b/fast_rl/agents/dqn.py @@ -101,7 +101,8 @@ def create_dqn_model(data: MDPDataBunch, base_arch: DQNModule, layers=None, igno DoubleDQNModule: [BaseDQNTrainer, FixedTargetDQNTrainer], DuelingDQNModule: [BaseDQNTrainer, FixedTargetDQNTrainer], DoubleDuelingModule: [BaseDQNTrainer, FixedTargetDQNTrainer], - FixedTargetDQNModule: [BaseDQNTrainer, FixedTargetDQNTrainer] + FixedTargetDQNModule: [BaseDQNTrainer, FixedTargetDQNTrainer], + DistributionalDQN: [BaseDQNTrainer, FixedTargetDQNTrainer] } diff --git a/fast_rl/agents/dqn_models.py b/fast_rl/agents/dqn_models.py index a0014ae..d091b80 100644 --- a/fast_rl/agents/dqn_models.py +++ b/fast_rl/agents/dqn_models.py @@ -3,203 +3,294 @@ from fast_rl.core.layers import * +def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): + """ + Perform distribution projection aka Catergorical Algorithm from the + "A Distributional Perspective on RL" paper + """ + batch_size = len(rewards) + rewards=rewards.detach().cpu().numpy().flatten() + dones=dones.detach().cpu().numpy().flatten().astype(np.bool) + proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) + next_distr=next_distr.numpy() + delta_z = (Vmax - Vmin) / (n_atoms - 1) + for atom in range(n_atoms): + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + proj_distr[eq_mask, l[eq_mask]] += next_distr[eq_mask, atom] + ne_mask = u != l + proj_distr[ne_mask, l[ne_mask]] += next_distr[ne_mask, atom] * (u - b_j)[ne_mask] + proj_distr[ne_mask, u[ne_mask]] += next_distr[ne_mask, atom] * (b_j - l)[ne_mask] + if dones.any(): + proj_distr[dones] = 0.0 + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards[dones])) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + eq_dones = dones.copy() + eq_dones[dones] = eq_mask + if eq_dones.any(): + proj_distr[eq_dones, l[eq_mask]] = 1.0 + ne_mask = u != l + ne_dones = dones.copy() + ne_dones[dones] = ne_mask + if ne_dones.any(): + proj_distr[ne_dones, l[ne_mask]] = (u - b_j)[ne_mask] + proj_distr[ne_dones, u[ne_mask]] = (b_j - l)[ne_mask] + return proj_distr + + class DQNModule(Module): - def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = 0.99, lr=0.001, - n_conv_blocks: Collection[int] = 0, nc=3, opt=None, emb_szs: ListSizes = None, loss_func=None, - w=-1, h=-1, ks: Union[None, list]=None, stride: Union[None, list]=None, grad_clip=5, - conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False,lin_cls=nn.Linear): - r""" - Basic DQN Module. - - Args: - ni: Number of inputs. Expecting a flat state `[1 x ni]` - ao: Number of actions to output. - layers: Number of layers where is determined per element. - n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added - to the head on top of existing linear layers. - nc: Number of channels that will be expected by the convolutional blocks. - """ - super().__init__() - self.lin_cls=lin_cls - self.name = 'DQN' - self.loss = None - self.loss_func = loss_func - self.discount = discount - self.gradient_clipping_norm = grad_clip - self.lr = lr - self.batch_norm = batch_norm - self.switched = False - # self.ks, self.stride = ([], []) if len(n_conv_blocks) == 0 else ks_stride(ks, stride, w, h, n_conv_blocks, conv_kern_proportion, stride_proportion) - self.ks, self.stride=([], []) if len(n_conv_blocks)==0 else (ifnone(ks, [10, 10, 10]), ifnone(stride, [5, 5, 5])) - self.action_model = nn.Sequential() - _layers = [conv_bn_lrelu(ch, self.nf, ks=ks, stride=stride, pad=pad, bn=self.batch_norm) for ch, self.nf, ks, stride in zip([nc]+n_conv_blocks[:-1],n_conv_blocks, self.ks, self.stride)] - - if _layers: ni = self.setup_conv_block(_layers=_layers, ni=ni, nc=nc, w=w, h=h) - self.setup_linear_block(_layers=_layers, ni=ni, nc=nc, w=w, h=h, emb_szs=emb_szs, layers=layers, ao=ao) - self.init_weights(self.action_model) - self.opt = None - self.set_opt(opt) - - def set_opt(self, opt): - self.opt=OptimWrapper.create(ifnone(optim.Adam, opt), lr=self.lr, layer_groups=[self.action_model]) - - def setup_conv_block(self, _layers, ni, nc, w, h): - self.action_model.add_module('conv_block', nn.Sequential(*(self.fix_switched_channels(ni, nc, _layers) + [Flatten()]))) - training = self.action_model.training - self.action_model.eval() - ni = int(self.action_model(torch.zeros((1, w, h, nc) if self.switched else (1, nc, w, h))).view(-1, ).shape[0]) - self.action_model.train(training) - return ni - - def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): - tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, use_bn=self.batch_norm,lin_cls=self.lin_cls) - if not emb_szs: tabular_model.embeds = None - if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() - self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) - - def fix_switched_channels(self, current_channels, expected_channels, layers: list): - if current_channels == expected_channels: - return layers - else: - self.switched = True - return [ChannelTranspose()] + layers - - def forward(self, xi: Tensor): - training = self.training - if xi.shape[0] == 1: self.eval() - pred = self.action_model(xi) - if training: self.train() - return pred - - def init_weights(self, m): - if issubclass(m.__class__,nn.Linear): - torch.nn.init.xavier_uniform_(m.weight) - m.bias.data.fill_(0.01) - - def sample_mask(self, d): - return torch.sub(1.0, d) - - def optimize(self, sampled): - r"""Uses ER to optimize the Q-net (without fixed targets). - - Uses the equation: - - .. math:: - Q^{*}(s, a) = \mathbb{E}_{s'∼ \Big\epsilon} \Big[r + \lambda \displaystyle\max_{a'}(Q^{*}(s' , a')) - \;|\; s, a \Big] - - - Returns (dict): Optimization information - - """ - with torch.no_grad(): - r = torch.cat([item.reward.float() for item in sampled]) - s_prime = torch.cat([item.s_prime for item in sampled]) - s = torch.cat([item.s for item in sampled]) - a = torch.cat([item.a.long() for item in sampled]) - d = torch.cat([item.done.float() for item in sampled]) - masking = self.sample_mask(d) - - y_hat = self.y_hat(s, a) - y = self.y(s_prime, masking, r, y_hat) - - loss = self.loss_func(y, y_hat) - - if self.training: - self.opt.zero_grad() - loss.backward() - torch.nn.utils.clip_grad_norm_(self.action_model.parameters(), self.gradient_clipping_norm) - for param in self.action_model.parameters(): - if param.grad is not None: param.grad.data.clamp_(-1, 1) - self.opt.step() - - with torch.no_grad(): - self.loss = loss - post_info = {'td_error': to_detach(y - y_hat).cpu().numpy()} - return post_info - - def y_hat(self, s, a): - return self.action_model(s).gather(1, a) - - def y(self, s_prime, masking, r, y_hat): - return self.discount * self.action_model(s_prime).max(1)[0].unsqueeze(1) * masking + r.expand_as(y_hat) + def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = 0.99, lr=0.001, + n_conv_blocks: Collection[int] = 0, nc=3, opt=None, emb_szs: ListSizes = None, loss_func=None, + w=-1, h=-1, ks: Union[None, list]=None, stride: Union[None, list]=None, grad_clip=5, + conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False,lin_cls=nn.Linear): + r""" + Basic DQN Module. + + Args: + ni: Number of inputs. Expecting a flat state `[1 x ni]` + ao: Number of actions to output. + layers: Number of layers where is determined per element. + n_conv_blocks: If `n_conv_blocks` is not 0, then convolutional blocks will be added + to the head on top of existing linear layers. + nc: Number of channels that will be expected by the convolutional blocks. + """ + super().__init__() + self.lin_cls=lin_cls + self.name = 'DQN' + self.loss = None + self.loss_func = loss_func + self.discount = discount + self.gradient_clipping_norm = grad_clip + self.lr = lr + self.batch_norm = batch_norm + self.switched = False + # self.ks, self.stride = ([], []) if len(n_conv_blocks) == 0 else ks_stride(ks, stride, w, h, n_conv_blocks, conv_kern_proportion, stride_proportion) + self.ks, self.stride=([], []) if len(n_conv_blocks)==0 else (ifnone(ks, [10, 10, 10]), ifnone(stride, [5, 5, 5])) + self.action_model = nn.Sequential() + _layers = [conv_bn_lrelu(ch, self.nf, ks=ks, stride=stride, pad=pad, bn=self.batch_norm) for ch, self.nf, ks, stride in zip([nc]+n_conv_blocks[:-1],n_conv_blocks, self.ks, self.stride)] + + if _layers: ni = self.setup_conv_block(_layers=_layers, ni=ni, nc=nc, w=w, h=h) + self.setup_linear_block(_layers=_layers, ni=ni, nc=nc, w=w, h=h, emb_szs=emb_szs, layers=layers, ao=ao) + self.init_weights(self.action_model) + self.opt = None + self.set_opt(opt) + + def set_opt(self, opt): + self.opt=OptimWrapper.create(ifnone(optim.Adam, opt), lr=self.lr, layer_groups=[self.action_model]) + + def setup_conv_block(self, _layers, ni, nc, w, h): + self.action_model.add_module('conv_block', nn.Sequential(*(self.fix_switched_channels(ni, nc, _layers) + [Flatten()]))) + training = self.action_model.training + self.action_model.eval() + ni = int(self.action_model(torch.zeros((1, w, h, nc) if self.switched else (1, nc, w, h))).view(-1, ).shape[0]) + self.action_model.train(training) + return ni + + def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): + tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, use_bn=self.batch_norm,lin_cls=self.lin_cls) + if not emb_szs: tabular_model.embeds = None + if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() + self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) + + def fix_switched_channels(self, current_channels, expected_channels, layers: list): + if current_channels == expected_channels: + return layers + else: + self.switched = True + return [ChannelTranspose()] + layers + + def forward(self, xi: Tensor): + training = self.training + if xi.shape[0] == 1: self.eval() + pred = self.action_model(xi) + if training: self.train() + return pred + + def init_weights(self, m): + if issubclass(m.__class__,nn.Linear): + torch.nn.init.xavier_uniform_(m.weight) + m.bias.data.fill_(0.01) + + def sample_mask(self, d): + return torch.sub(1.0, d) + + def optimize(self, sampled): + r"""Uses ER to optimize the Q-net (without fixed targets). + + Uses the equation: + + .. math:: + Q^{*}(s, a) = \mathbb{E}_{s'∼ \Big\epsilon} \Big[r + \lambda \displaystyle\max_{a'}(Q^{*}(s' , a')) + \;|\; s, a \Big] + + + Returns (dict): Optimization information + + """ + with torch.no_grad(): + r = torch.cat([item.reward.float() for item in sampled]) + s_prime = torch.cat([item.s_prime for item in sampled]) + s = torch.cat([item.s for item in sampled]) + a = torch.cat([item.a.long() for item in sampled]) + d = torch.cat([item.done.float() for item in sampled]) + masking = self.sample_mask(d) + + y_hat = self.y_hat(s, a,s_prime,r,masking) + y = self.y(s_prime, masking, r, y_hat,s,a) + + loss = self.loss_func(y, y_hat) + + if self.training: + self.opt.zero_grad() + loss.backward() + torch.nn.utils.clip_grad_norm_(self.action_model.parameters(), self.gradient_clipping_norm) + for param in self.action_model.parameters(): + if param.grad is not None: param.grad.data.clamp_(-1, 1) + self.opt.step() + + with torch.no_grad(): + self.loss = loss + post_info = {'td_error': to_detach(y - y_hat).cpu().numpy()} + return post_info + + def y_hat(self, s, a,s_prime,r,masking): + return self.action_model(s).gather(1, a) + + def y(self, s_prime, masking, r, y_hat,s,a): + return self.discount * self.action_model(s_prime).max(1)[0].unsqueeze(1) * masking + r.expand_as(y_hat) class FixedTargetDQNModule(DQNModule): - def __init__(self, ni: int, ao: int, layers: Collection[int], tau=1, **kwargs): - super().__init__(ni, ao, layers, **kwargs) - self.name = 'Fixed Target DQN' - self.tau = tau - self.target_model = copy(self.action_model) + def __init__(self, ni: int, ao: int, layers: Collection[int], tau=1, **kwargs): + super().__init__(ni, ao, layers, **kwargs) + self.name = 'Fixed Target DQN' + self.tau = tau + self.target_model = copy(self.action_model) - def target_copy_over(self): - r""" Updates the target network from calls in the FixedTargetDQNTrainer callback.""" - # self.target_net.load_state_dict(self.action_model.state_dict()) - for target_param, local_param in zip(self.target_model.parameters(), self.action_model.parameters()): - target_param.data.copy_(self.tau * local_param.data + (1.0 - self.tau) * target_param.data) + def target_copy_over(self): + r""" Updates the target network from calls in the FixedTargetDQNTrainer callback.""" + # self.target_net.load_state_dict(self.action_model.state_dict()) + for target_param, local_param in zip(self.target_model.parameters(), self.action_model.parameters()): + target_param.data.copy_(self.tau * local_param.data + (1.0 - self.tau) * target_param.data) - def y(self, s_prime, masking, r, y_hat): - r""" - Uses the equation: + def y(self, s_prime, masking, r, y_hat,s,a): + r""" + Uses the equation: - .. math:: + .. math:: - Q^{*}(s, a) = \mathbb{E}_{s'∼ \Big\epsilon} \Big[r + \lambda \displaystyle\max_{a'}(Q^{*}(s' , a')) - \;|\; s, a \Big] + Q^{*}(s, a) = \mathbb{E}_{s'∼ \Big\epsilon} \Big[r + \lambda \displaystyle\max_{a'}(Q^{*}(s' , a')) + \;|\; s, a \Big] - """ - return self.discount * self.target_model(s_prime).max(1)[0].unsqueeze(1) * masking + r.expand_as(y_hat) + """ + return self.discount * self.target_model(s_prime).max(1)[0].unsqueeze(1) * masking + r.expand_as(y_hat) class DoubleDQNModule(FixedTargetDQNModule): - def __init__(self, ni: int, ao: int, layers: Collection[int], **kwargs): - super().__init__(ni, ao, layers, **kwargs) - self.name = 'DDQN' + def __init__(self, ni: int, ao: int, layers: Collection[int], **kwargs): + super().__init__(ni, ao, layers, **kwargs) + self.name = 'DDQN' - def calc_y(self, s_prime, masking, r, y_hat): - return self.discount * self.target_model(s_prime).gather(1, self.action_model(s_prime).argmax(1).unsqueeze( - 1)) * masking + r.expand_as(y_hat) + def y(self, s_prime, masking, r, y_hat,s,a): + return self.discount * self.target_model(s_prime).gather(1, self.action_model(s_prime).argmax(1).unsqueeze( + 1)) * masking + r.expand_as(y_hat) class DuelingBlock(nn.Module): - def __init__(self, ao, stream_input_size,lin_cls=nn.Linear): - super().__init__() + def __init__(self, ao, stream_input_size,lin_cls=nn.Linear): + super().__init__() - self.val = lin_cls(stream_input_size, 1) - self.adv = lin_cls(stream_input_size, ao) + self.val = lin_cls(stream_input_size, 1) + self.adv = lin_cls(stream_input_size, ao) - def forward(self, xi): - r"""Splits the base neural net output into 2 streams to evaluate the advantage and v of the s space and - corresponding actions. + def forward(self, xi): + r"""Splits the base neural net output into 2 streams to evaluate the advantage and v of the s space and + corresponding actions. - .. math:: - Q(s,a;\; \Theta, \\alpha, \\beta) = V(s;\; \Theta, \\beta) + A(s, a;\; \Theta, \\alpha) - \\frac{1}{|A|} - \\Big\\sum_{a'} A(s, a';\; \Theta, \\alpha) + .. math:: + Q(s,a;\; \Theta, \\alpha, \\beta) = V(s;\; \Theta, \\beta) + A(s, a;\; \Theta, \\alpha) - \\frac{1}{|A|} + \\Big\\sum_{a'} A(s, a';\; \Theta, \\alpha) - """ - val, adv = self.val(xi), self.adv(xi) - xi = val.expand_as(adv) + (adv - adv.mean()).squeeze(0) - return xi + """ + val, adv = self.val(xi), self.adv(xi) + xi = val.expand_as(adv) + (adv - adv.mean()).squeeze(0) + return xi class DuelingDQNModule(FixedTargetDQNModule): - def __init__(self, **kwargs): - super().__init__(**kwargs) - self.name = 'Dueling DQN' + def __init__(self, **kwargs): + super().__init__(**kwargs) + self.name = 'Dueling DQN' - def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): - tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, - use_bn=self.batch_norm,lin_cls=self.lin_cls) - if not emb_szs: tabular_model.embeds = None - if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() - tabular_model.layers, removed_layer = split_model(tabular_model.layers, [last_layer(tabular_model)]) - ni = removed_layer[0].in_features - self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) - self.action_model.add_module('dueling_block', DuelingBlock(ao, ni)) + def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao): + tabular_model = TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, + use_bn=self.batch_norm,lin_cls=self.lin_cls) + if not emb_szs: tabular_model.embeds = None + if not self.batch_norm: tabular_model.bn_cont = FakeBatchNorm() + tabular_model.layers, removed_layer = split_model(tabular_model.layers, [last_layer(tabular_model)]) + ni = removed_layer[0].in_features + self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) + self.action_model.add_module('dueling_block', DuelingBlock(ao, ni)) class DoubleDuelingModule(DuelingDQNModule, DoubleDQNModule): - def __init__(self, **kwargs): - super().__init__(**kwargs) - self.name = 'DDDQN' + def __init__(self, **kwargs): + super().__init__(**kwargs) + self.name = 'DDDQN' + + +def distributional_loss_fn(s_log_sm_v,proj_distr_v): + return (-s_log_sm_v*proj_distr_v).sum(dim=1).mean() + + +class DistributionalDQN(FixedTargetDQNModule): + def __init__(self,ao,n_atoms=51,v_min=-10,v_max=10,**kwargs): + self.z_delta=(v_max-v_min)/(n_atoms-1) + self.n_atoms=n_atoms + self.v_min=v_min + self.v_max=v_max + super().__init__(ao=ao*n_atoms,**kwargs) + self.name='Distributional DQN' + + self.action_model.register_buffer('supports',torch.arange(v_min,v_max+self.z_delta,self.z_delta)) + self.sm=nn.Softmax(dim=1) + + self.loss_func=distributional_loss_fn + + def both(self,xi): + cat_out=self(xi,False) + probs=self.apply_softmax(cat_out) + weights=probs*self.action_model.supports + res=weights.sum(dim=2) + return cat_out,res + + def q_vals(self,xi): + return self.both(xi)[1] + + def apply_softmax(self,t): + return self.sm(t.view(-1,self.n_atoms)).view(t.size()) + + def y(self, s_prime, masking, r, y_hat,s,a): + distr_v=self(s,only_q=False) + state_action_values=distr_v[range(s.size()[0]), a.data] + state_log_sm_v=F.log_softmax(state_action_values, dim=1) + return state_log_sm_v + + def y_hat(self, s, a,s_prime,r,masking): + next_distr_v, next_q_vals_v=self.both(s_prime) + next_actions=next_q_vals_v.max(1)[1].data.cpu().numpy() + next_distr=self.apply_softmax(next_distr_v).data.cpu() + next_best_distr=next_distr[range(s_prime.size()[0]),next_actions] + proj_distr=distr_projection(next_best_distr,r,masking,self.v_min,self.v_max,self.n_atoms,self.discount) + proj_distr_v=torch.tensor(proj_distr).to(device=self.action_model.supports.device) + return proj_distr_v + + def forward(self, xi: Tensor,only_q=True): + return self.q_vals(xi) if only_q else super(DistributionalDQN,self).forward(xi).view(xi.size()[0],-1,self.n_atoms) \ No newline at end of file diff --git a/fast_rl/core/basic_train.py b/fast_rl/core/basic_train.py index 82c08d2..4bff6a9 100644 --- a/fast_rl/core/basic_train.py +++ b/fast_rl/core/basic_train.py @@ -36,7 +36,7 @@ class AgentLearner(Learner): def __init__(self, data, loss_func=None, callback_fns=None, opt=torch.optim.Adam, **kwargs): super().__init__(data=data, callback_fns=ifnone(callback_fns, []) + data.callback, **kwargs) - self.model.loss_func = ifnone(loss_func, F.mse_loss) + self.model.loss_func = ifnone(ifnone(loss_func,self.model.loss_func), F.mse_loss) self.model.set_opt(opt) self.loss_func = None self.trainers = None diff --git a/fast_rl/core/data_block.py b/fast_rl/core/data_block.py index ec56d95..d4d7347 100644 --- a/fast_rl/core/data_block.py +++ b/fast_rl/core/data_block.py @@ -157,7 +157,7 @@ def __init__(self,env,w_step:int,h_step:int): def render(self,mode='human',**kwargs): img = super(ResolutionWrapper,self).render(mode=mode,**kwargs) - return img if len(img)==0 else img[::self.w_step,::self.h_step,:] + return img if type(img)==bool or len(img)==0 else img[::self.w_step,::self.h_step,:] @dataclass class Bounds(object): diff --git a/tests/test_dqn.py b/tests/test_dqn.py index b8f8b08..e1463fe 100644 --- a/tests/test_dqn.py +++ b/tests/test_dqn.py @@ -38,8 +38,9 @@ def learner2gif(lnr:DQNLearner,s_format,group_interp:GroupAgentInterpretation,na def trained_learner(model_cls, env, s_format, experience, bs, layers, memory_size=1000000, decay=0.001, - copy_over_frequency=300, lr=None, epochs=450,lin_cls=None,explore=None,**kwargs): + copy_over_frequency=300, lr=None, epochs=450,lin_cls=None,explore=None,model_kwargs=None,**kwargs): if lr is None: lr = [0.001, 0.00025] + model_kwargs=ifnone(model_kwargs,{}) memory = experience(memory_size=memory_size, reduce_ram=True) metrics=[RewardMetric, RollingRewardMetric] if explore is None: metrics.append(EpsilonMetric) @@ -47,8 +48,8 @@ def trained_learner(model_cls, env, s_format, experience, bs, layers, memory_siz if type(lr) == list: lr = lr[0] if model_cls == DQNModule else lr[1] data = MDPDataBunch.from_env(env, render='human', bs=bs, add_valid=False, keep_env_open=False, feed_type=s_format, memory_management_strategy='k_partitions_top', k=3,**kwargs) - if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.RMSprop,lin_cls=ifnone(lin_cls,nn.Linear)) - else: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers,lin_cls=ifnone(lin_cls,nn.Linear)) + if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.RMSprop,lin_cls=ifnone(lin_cls,nn.Linear),**model_kwargs) + else: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers,lin_cls=ifnone(lin_cls,nn.Linear),**model_kwargs) learn = dqn_learner(data, model, memory=memory, exploration_method=explore, copy_over_frequency=copy_over_frequency, callback_fns=metrics) learn.fit(epochs) @@ -138,10 +139,10 @@ def test_dqn_models_cartpole(model_cls, s_format, experience): learner2gif(learn,s_format,group_interp,'cartpole',extra_s) @pytest.mark.usefixtures('skip_performance_check') -@pytest.mark.parametrize(["model_cls", "s_format"], - list(product(p_model, p_format))) -def test_dqn_models_nstep_cartpole(model_cls, s_format): - experience=NStepExperienceReplay +@pytest.mark.parametrize(["s_format", 'experience'], + list(product(p_format, p_exp))) +def test_dqn_models_categorical_cartpole(s_format, experience): + model_cls=DistributionalDQN group_interp = GroupAgentInterpretation() extra_s=f'{experience.__name__}_{model_cls.__name__}_{s_format}' for i in range(5): @@ -151,6 +152,22 @@ def test_dqn_models_nstep_cartpole(model_cls, s_format): learner2gif(learn,s_format,group_interp,'cartpole',extra_s) +@pytest.mark.usefixtures('skip_performance_check') +@pytest.mark.parametrize(["s_format"], + list(product(p_format))) +def test_dqn_models_distributional_cartpole(s_format): + experience=ExperienceReplay + group_interp = GroupAgentInterpretation() + model_cls=DistributionalDQN + extra_s=f'{experience.__name__}_{model_cls.__name__}_{s_format}' + for i in range(5): + learn = trained_learner(model_cls, 'CartPole-v1', s_format, experience, bs=32, layers=[512, 512],lr=[1e-4,1e-4], + memory_size=1000000, decay=0.001,model_kwargs={'v_max':400,'v_min':-1,'n_atoms':51},epochs=900, + res_wrap=partial(ResolutionWrapper, w_step=3, h_step=3)) + + learner2gif(learn,s_format,group_interp,'cartpole',extra_s) + + layer_clss=[GaussianNoisyLinear,GaussianNoisyFactorizedLinear] From deee785cacebc6f193c640d9b12d900e3e76ea15 Mon Sep 17 00:00:00 2001 From: josiah Date: Thu, 9 Apr 2020 06:32:53 -0400 Subject: [PATCH 25/29] Added: - alternate dist dqn, which trains quickly now --- README.md | 9 +- ROADMAP.md | 1 + docs_src/rl.agents.cem.ipynb | 61 + fast_rl/agents/dist_dqn.py | 223 ++++ fast_rl/agents/dist_dqn_models.py | 72 ++ fast_rl/agents/dqn_models.py | 200 +++- fast_rl/agents/native_dist_dqn.py | 1722 +++++++++++++++++++++++++++++ fast_rl/core/agent_core.py | 2 +- tests/test_dist_dqn.py | 13 + tests/test_dqn.py | 30 +- 10 files changed, 2270 insertions(+), 63 deletions(-) create mode 100644 docs_src/rl.agents.cem.ipynb create mode 100644 fast_rl/agents/dist_dqn.py create mode 100644 fast_rl/agents/dist_dqn_models.py create mode 100644 fast_rl/agents/native_dist_dqn.py create mode 100644 tests/test_dist_dqn.py diff --git a/README.md b/README.md index 10c840b..1a8bf23 100644 --- a/README.md +++ b/README.md @@ -112,8 +112,8 @@ OpenAI environments. - [X] Add Cross Entropy Method CEM - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - - [X] Distributional DQN - - [ ] Add RAINBOW DQN + - [X] Add Distributional DQN + - [ ] **Working on** Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO @@ -152,7 +152,10 @@ OpenAI environments. - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` - [ ] Add HER - [ ] 2.0.0 Breaking refactor of all methods - - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second. + - [ ] Move to fastai 2.0 + - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second + - [ ] fastrl needs to handle ram better + - [ ] Use yield instead of return for the MDPDataset object - [ ] Unify common code pieces shared in all models diff --git a/ROADMAP.md b/ROADMAP.md index 53513f0..611e1a3 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -50,4 +50,5 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Move to fastai 2.0 - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second - [ ] fastrl needs to handle ram better + - [ ] Use yield instead of return for the MDPDataset object - [ ] Unify common code pieces shared in all models \ No newline at end of file diff --git a/docs_src/rl.agents.cem.ipynb b/docs_src/rl.agents.cem.ipynb new file mode 100644 index 0000000..ce45d6d --- /dev/null +++ b/docs_src/rl.agents.cem.ipynb @@ -0,0 +1,61 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Can't import one of these: No module named 'pybullet'\n", + "pygame 2.0.0.dev6 (SDL 2.0.10, python 3.6.7)\n", + "Hello from the pygame community. https://www.pygame.org/contribute.html\n", + "Can't import one of these: No module named 'gym_minigrid'\n" + ] + } + ], + "source": [ + "from fastai.tabular.data import emb_sz_rule\n", + "from fast_rl.agents.cem import CEMLearner, CEMTrainer\n", + "from fast_rl.agents.cem_models import CEMModel\n", + "from fast_rl.core.data_block import MDPDataBunch\n", + "import numpy as np\n", + "from fast_rl.core.metrics import RewardMetric, RollingRewardMetric" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.6.7" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/fast_rl/agents/dist_dqn.py b/fast_rl/agents/dist_dqn.py new file mode 100644 index 0000000..1687a19 --- /dev/null +++ b/fast_rl/agents/dist_dqn.py @@ -0,0 +1,223 @@ +import collections +from copy import deepcopy + +from fastai.basic_train import LearnerCallback +from fastai.imports import torch, Any + +from fast_rl.agents.dist_dqn_models import TargetNet +from fast_rl.core.agent_core import ExperienceReplay, NStepExperienceReplay +from fast_rl.core.basic_train import AgentLearner, listify, List +from fast_rl.core.data_block import MDPDataBunch, MDPStep +from fastai.imports import torch + +import gym +import numpy as np +import argparse + +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.optim as optim + +Vmax = 10 +Vmin = -10 +N_ATOMS = 51 +DELTA_Z = (Vmax - Vmin) / (N_ATOMS - 1) + +ExperienceFirstLast = collections.namedtuple('ExperienceFirstLast', ('state', 'action', 'reward', 'last_state','done')) + + + + +def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): + """ + Perform distribution projection aka Catergorical Algorithm from the + "A Distributional Perspective on RL" paper + """ + batch_size = len(rewards) + proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) + delta_z = (Vmax - Vmin) / (n_atoms - 1) + for atom in range(n_atoms): + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + proj_distr[eq_mask, l[eq_mask]] += next_distr[eq_mask, atom] + ne_mask = u != l + proj_distr[ne_mask, l[ne_mask]] += next_distr[ne_mask, atom] * (u - b_j)[ne_mask] + proj_distr[ne_mask, u[ne_mask]] += next_distr[ne_mask, atom] * (b_j - l)[ne_mask] + if dones.any(): + proj_distr[dones] = 0.0 + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards[dones])) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + eq_dones = dones.copy() + eq_dones[dones] = eq_mask + if eq_dones.any(): + proj_distr[eq_dones, l[eq_mask]] = 1.0 + ne_mask = u != l + ne_dones = dones.copy() + ne_dones[dones] = ne_mask + if ne_dones.any(): + proj_distr[ne_dones, l[ne_mask]] = (u - b_j)[ne_mask] + proj_distr[ne_dones, u[ne_mask]] = (b_j - l)[ne_mask] + return proj_distr + + + +def unpack_batch(batch): + states, actions, rewards, dones, last_states = [], [], [], [], [] + for exp in batch: + state = np.array(exp.state, copy=False) + states.append(state) + actions.append(exp.action) + rewards.append(exp.reward) + dones.append(exp.done) + # if exp.last_state is None: + # last_states.append(state) # the result will be masked anyway + # else: + last_states.append(np.array(exp.last_state, copy=False)) + return np.array(states, copy=False), np.array(actions), np.array(rewards, dtype=np.float32), \ + np.array(dones, dtype=np.uint8), np.array(last_states, copy=False) + + +def calc_loss(batch, net, tgt_net, gamma, device="cpu", save_prefix=None): + states, actions, rewards, dones, next_states = unpack_batch(batch) + batch_size = len(batch) + + states_v = torch.tensor(states).to(device) + actions_v = torch.tensor(actions).to(device) + next_states_v = torch.tensor(next_states).to(device) + + # next state distribution + next_distr_v, next_qvals_v = tgt_net.both(next_states_v) + next_actions = next_qvals_v.max(1)[1].data.cpu().numpy() + next_distr = tgt_net.apply_softmax(next_distr_v).data.cpu().numpy() + + next_best_distr = next_distr[range(batch_size), next_actions] + dones = dones.astype(np.bool) + + # project our distribution using Bellman update + proj_distr = distr_projection(next_best_distr, rewards, dones, Vmin, Vmax, N_ATOMS, gamma) + + # calculate net output + distr_v = net(states_v) + state_action_values = distr_v[range(batch_size), actions_v.data] + state_log_sm_v = F.log_softmax(state_action_values, dim=1) + proj_distr_v = torch.tensor(proj_distr).to(device) + + loss_v = -state_log_sm_v * proj_distr_v + return loss_v.sum(dim=1).mean() + + + +class BaseDistDQNTrainer(LearnerCallback): + def __init__(self, learn: 'DistDQNLearner', max_episodes=None): + r"""Handles basic DQN end of step model optimization.""" + super().__init__(learn) + self.n_skipped = 0 + self._persist = max_episodes is not None + self.max_episodes = max_episodes + self.episode = -1 + self.iteration = 0 + # For the callback handler + self._order = 0 + self.previous_item = None + + @property + def learn(self)->'DistDQNLearner': + return self._learn() + + def on_train_begin(self, n_epochs, **kwargs: Any): + self.max_episodes = n_epochs if not self._persist else self.max_episodes + + def on_epoch_begin(self, epoch, **kwargs: Any): + pass + + def on_backward_begin(self, **kwargs: Any):return {'skip_bwd': self.learn.warming_up} + def on_backward_end(self, **kwargs:Any): return {'skip_step':False} + def on_step_end(self, **kwargs: Any):return {'skip_zero': False} + + def on_loss_begin(self, **kwargs: Any): + r"""Performs tree updates, exploration updates, and model optimization.""" + if self.learn.model.training: + self.learn.memory.update(item=self.learn.data.x.items[-1]) + self.iteration+=1 + self.learn.epsilon_tracker.frame(self.iteration) + + if not self.learn.warming_up: + samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) + batch=[ExperienceFirstLast(state=deepcopy(s.s[0]),action=deepcopy(s.action.taken_action), + reward=deepcopy(s.reward),last_state=deepcopy(s.s_prime[0]),done=deepcopy(s.done)) for s in samples] + # model_func=lambda x: self.learn.model.qvals(x) + loss=calc_loss(batch,self.learn.model,self.learn.target_net.target_model,gamma=0.99,device=self.learn.data.device,save_prefix=None) + return {'last_output':loss} + else: return None + + def on_batch_end(self, **kwargs:Any) ->None: + if self.iteration % 300 == 0: + self.learn.target_net.sync() + + +class ArgmaxActionSelector(object): + """ + Selects actions using argmax + """ + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + return np.argmax(scores, axis=1) + + +class EpsilonGreedyActionSelector(object): + def __init__(self, epsilon=0.05, selector=None): + self.epsilon = epsilon + self.selector = selector if selector is not None else ArgmaxActionSelector() + + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + batch_size, n_actions = scores.shape + actions = self.selector(scores) + mask = np.random.random(size=batch_size) < self.epsilon + rand_actions = np.random.choice(n_actions, sum(mask)) + actions[mask] = rand_actions + return actions + +class EpsilonTracker: + def __init__(self, epsilon_greedy_selector, params): + self.epsilon_greedy_selector = epsilon_greedy_selector + self.epsilon_start = params['epsilon_start'] + self.epsilon_final = params['epsilon_final'] + self.epsilon_frames = params['epsilon_frames'] + self.frame(0) + + def frame(self, frame): + self.epsilon_greedy_selector.epsilon = \ + max(self.epsilon_final, self.epsilon_start - frame / self.epsilon_frames) + + + +class DistDQNLearner(AgentLearner): + def __init__(self, data: MDPDataBunch, model, trainers, loss_func=None,opt=torch.optim.Adam,**learn_kwargs): + super().__init__(data=data, model=model, opt=opt,loss_func=loss_func, **learn_kwargs) + self._loss_func=loss_func + self.memory=NStepExperienceReplay(100000) + self.target_net=TargetNet(self.model) + self.exploration_method=EpsilonGreedyActionSelector(1.0) + self.epsilon_tracker=EpsilonTracker(self.exploration_method, {'epsilon_frames': 100, 'epsilon_start': 1.0, + 'epsilon_final': 0.02}) + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + + def init(self, init):pass + # def init_loss_func(self):pass + + def predict(self, element, **kwargs): + model_func=lambda x: self.model.qvals(x) + q_v=model_func(element) + q=q_v.data.cpu().numpy() + actions=self.exploration_method(q) + return actions + diff --git a/fast_rl/agents/dist_dqn_models.py b/fast_rl/agents/dist_dqn_models.py new file mode 100644 index 0000000..f191ca5 --- /dev/null +++ b/fast_rl/agents/dist_dqn_models.py @@ -0,0 +1,72 @@ +import copy + +import torch +import torch.nn as nn +from fastai.imports import torch + +Vmax = 10 +Vmin = -10 +N_ATOMS = 51 +DELTA_Z = (Vmax - Vmin) / (N_ATOMS - 1) + + +class TargetNet: + """ + Wrapper around model which provides copy of it instead of trained weights + """ + def __init__(self, model): + self.model = model + self.target_model = copy.deepcopy(model) + + def sync(self): + self.target_model.load_state_dict(self.model.state_dict()) + + def alpha_sync(self, alpha): + """ + Blend params of target net with params from the model + :param alpha: + """ + assert isinstance(alpha, float) + assert 0.0 < alpha <= 1.0 + state = self.model.state_dict() + tgt_state = self.target_model.state_dict() + for k, v in state.items(): + tgt_state[k] = tgt_state[k] * alpha + (1 - alpha) * v + self.target_model.load_state_dict(tgt_state) + + +class DistributionalDQN(nn.Module): + def __init__(self, input_shape, n_actions): + super(DistributionalDQN, self).__init__() + + self.fc = nn.Sequential( + nn.Linear(input_shape[0], 512), + nn.ReLU(), + nn.Linear(512, n_actions * N_ATOMS) + ) + + self.register_buffer("supports", torch.arange(Vmin, Vmax+DELTA_Z, DELTA_Z)) + self.softmax = nn.Softmax(dim=1) + + self.loss_func=None + + def set_opt(self,_):pass + + def forward(self, x): + batch_size = x.size()[0] + fc_out = self.fc(x.float()) + return fc_out.view(batch_size, -1, N_ATOMS) + + def both(self, x): + cat_out = self(x) + probs = self.apply_softmax(cat_out) + weights = probs * self.supports + res = weights.sum(dim=2) + return cat_out, res + + def qvals(self, x): + return self.both(x)[1] + + def apply_softmax(self, t): + return self.softmax(t.view(-1, N_ATOMS)).view(t.size()) + diff --git a/fast_rl/agents/dqn_models.py b/fast_rl/agents/dqn_models.py index d091b80..ffceec8 100644 --- a/fast_rl/agents/dqn_models.py +++ b/fast_rl/agents/dqn_models.py @@ -1,6 +1,7 @@ from fastai.callback import OptimWrapper from fast_rl.core.layers import * +# import copy def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): @@ -9,10 +10,7 @@ def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): "A Distributional Perspective on RL" paper """ batch_size = len(rewards) - rewards=rewards.detach().cpu().numpy().flatten() - dones=dones.detach().cpu().numpy().flatten().astype(np.bool) proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) - next_distr=next_distr.numpy() delta_z = (Vmax - Vmin) / (n_atoms - 1) for atom in range(n_atoms): tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) @@ -44,12 +42,14 @@ def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): return proj_distr + class DQNModule(Module): def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = 0.99, lr=0.001, n_conv_blocks: Collection[int] = 0, nc=3, opt=None, emb_szs: ListSizes = None, loss_func=None, w=-1, h=-1, ks: Union[None, list]=None, stride: Union[None, list]=None, grad_clip=5, - conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False,lin_cls=nn.Linear): + conv_kern_proportion=0.1, stride_proportion=0.1, pad=False, batch_norm=False,lin_cls=nn.Linear, + do_grad_clipping=True): r""" Basic DQN Module. @@ -71,6 +71,7 @@ def __init__(self, ni: int, ao: int, layers: Collection[int], discount: float = self.lr = lr self.batch_norm = batch_norm self.switched = False + self.do_grad_clipping=do_grad_clipping # self.ks, self.stride = ([], []) if len(n_conv_blocks) == 0 else ks_stride(ks, stride, w, h, n_conv_blocks, conv_kern_proportion, stride_proportion) self.ks, self.stride=([], []) if len(n_conv_blocks)==0 else (ifnone(ks, [10, 10, 10]), ifnone(stride, [5, 5, 5])) self.action_model = nn.Sequential() @@ -144,15 +145,15 @@ def optimize(self, sampled): y_hat = self.y_hat(s, a,s_prime,r,masking) y = self.y(s_prime, masking, r, y_hat,s,a) - + self.opt.zero_grad() loss = self.loss_func(y, y_hat) if self.training: - self.opt.zero_grad() loss.backward() - torch.nn.utils.clip_grad_norm_(self.action_model.parameters(), self.gradient_clipping_norm) - for param in self.action_model.parameters(): - if param.grad is not None: param.grad.data.clamp_(-1, 1) + if self.do_grad_clipping: + torch.nn.utils.clip_grad_norm_(self.action_model.parameters(), self.gradient_clipping_norm) + for param in self.action_model.parameters(): + if param.grad is not None: param.grad.data.clamp_(-1, 1) self.opt.step() with torch.no_grad(): @@ -172,13 +173,14 @@ def __init__(self, ni: int, ao: int, layers: Collection[int], tau=1, **kwargs): super().__init__(ni, ao, layers, **kwargs) self.name = 'Fixed Target DQN' self.tau = tau - self.target_model = copy(self.action_model) + self.target_model = deepcopy(self.action_model) def target_copy_over(self): r""" Updates the target network from calls in the FixedTargetDQNTrainer callback.""" # self.target_net.load_state_dict(self.action_model.state_dict()) - for target_param, local_param in zip(self.target_model.parameters(), self.action_model.parameters()): - target_param.data.copy_(self.tau * local_param.data + (1.0 - self.tau) * target_param.data) + # for target_param, local_param in zip(self.target_model.parameters(), self.action_model.parameters()): + # target_param.data.copy_(self.tau * local_param.data + (1.0 - self.tau) * target_param.data) + self.target_model.load_state_dict(self.action_model.state_dict()) def y(self, s_prime, masking, r, y_hat,s,a): r""" @@ -247,8 +249,94 @@ def __init__(self, **kwargs): def distributional_loss_fn(s_log_sm_v,proj_distr_v): - return (-s_log_sm_v*proj_distr_v).sum(dim=1).mean() + loss= (-s_log_sm_v*proj_distr_v) + return loss.sum(dim=1).mean() + + +# class DistributionalDQN(FixedTargetDQNModule): +# def __init__(self,ao,n_atoms=51,v_min=-10,v_max=10,**kwargs): +# self.z_delta=(v_max-v_min)/(n_atoms-1) +# self.n_atoms=n_atoms +# self.v_min=v_min +# self.v_max=v_max +# super().__init__(ao=ao*n_atoms,**kwargs) +# self.name='Distributional DQN' +# # self.sm=nn.Softmax(dim=1) +# +# self.loss_func=distributional_loss_fn +# +# def init_weights(self, m):pass +# +# def setup_linear_block(self, **kwargs): +# super(DistributionalDQN,self).setup_linear_block(**kwargs) +# self.action_model.register_buffer('supports', torch.arange(self.v_min, self.v_max+self.z_delta, self.z_delta)) +# self.action_model.add_module('softmax_buff',nn.Softmax(dim=1)) +# +# def both(self,xi,use_target=False): +# if not use_target: cat_out=self(xi,False) +# else: cat_out=self.target_model(xi).view(xi.size()[0],-1,self.n_atoms) +# probs=self.apply_softmax(cat_out,use_target) +# if not use_target: weights=probs*self.action_model.supports +# else: weights=probs*self.target_model.supports +# res=weights.sum(dim=2) +# return cat_out,res +# +# def q_vals(self,xi): +# return self.both(xi)[1] +# +# def apply_softmax(self,t,use_target=False): +# if not use_target: return self.action_model.softmax_buff(t.view(-1,self.n_atoms)).view(t.size()) +# return self.target_model.softmax_buff(t.view(-1,self.n_atoms)).view(t.size()) +# +# def y(self, s_prime, masking, r, y_hat,s,a): +# distr_v=self(s,only_q=False) +# state_action_values=distr_v[range(s.size()[0]), a.data] +# state_log_sm_v=F.log_softmax(state_action_values, dim=1) +# return state_log_sm_v +# +# def y_hat(self, s, a,s_prime,r,masking): +# next_distr_v, next_q_vals_v=self.both(s_prime,True) # target +# next_actions=next_q_vals_v.max(1)[1].data.cpu().numpy() +# next_distr=self.apply_softmax(next_distr_v,True).data.cpu() # target +# next_best_distr=next_distr[range(s_prime.size()[0]),next_actions] +# proj_distr=distr_projection(next_best_distr,r,masking,self.v_min,self.v_max,self.n_atoms,self.discount) +# proj_distr_v=torch.tensor(proj_distr).to(device=self.action_model.supports.device) +# return proj_distr_v +# +# def forward(self, xi: Tensor,only_q=True): +# return self.q_vals(xi) if only_q else super(DistributionalDQN,self).forward(xi).view(xi.size()[0],-1,self.n_atoms) + +class DistributionalDQNModule(nn.Module): + def __init__(self, input_shape, n_actions,n_atoms=51,v_min=-10,v_max=10,): + super(DistributionalDQNModule, self).__init__() + self.n_atoms=n_atoms + self.v_min=v_min + self.v_max=v_max + self.z_delta=(v_max-v_min)/(n_atoms-1) + + self.fc = nn.Sequential( + nn.Linear(input_shape, 512), + nn.ReLU(), + nn.Linear(512, n_actions * self.n_atoms) + ) + + self.register_buffer("supports", torch.arange(self.v_min, self.v_max+self.z_delta, self.z_delta)) + self.softmax = nn.Softmax(dim=1) + def forward(self, x): + batch_size = x.size()[0] + fc_out = self.fc(x.float()) + return fc_out.view(batch_size, -1, self.n_atoms) + + def both(self, x): + cat_out = self(x) + probs = self.apply_softmax(cat_out) + weights = probs * self.supports + res = weights.sum(dim=2) + return cat_out, res + + def qvals(self, x): return self.both(x)[1] + def apply_softmax(self, t): return self.softmax(t.view(-1, self.n_atoms)).view(t.size()) class DistributionalDQN(FixedTargetDQNModule): def __init__(self,ao,n_atoms=51,v_min=-10,v_max=10,**kwargs): @@ -256,41 +344,73 @@ def __init__(self,ao,n_atoms=51,v_min=-10,v_max=10,**kwargs): self.n_atoms=n_atoms self.v_min=v_min self.v_max=v_max - super().__init__(ao=ao*n_atoms,**kwargs) + super().__init__(ao=ao,**kwargs) + self.do_grad_clipping=False self.name='Distributional DQN' - - self.action_model.register_buffer('supports',torch.arange(v_min,v_max+self.z_delta,self.z_delta)) - self.sm=nn.Softmax(dim=1) + # self.sm=nn.Softmax(dim=1) self.loss_func=distributional_loss_fn - def both(self,xi): - cat_out=self(xi,False) - probs=self.apply_softmax(cat_out) - weights=probs*self.action_model.supports - res=weights.sum(dim=2) - return cat_out,res + def init_weights(self, m):pass - def q_vals(self,xi): - return self.both(xi)[1] + def setup_linear_block(self, _layers, ni, nc, w, h, emb_szs, layers, ao,**kwargs): + self.action_model=DistributionalDQNModule(ni,ao) - def apply_softmax(self,t): - return self.sm(t.view(-1,self.n_atoms)).view(t.size()) + def optimize(self, sampled): + with torch.no_grad(): + r = torch.cat([item.reward.float() for item in sampled]).flatten().cpu().numpy() + s_prime = torch.cat([item.s_prime for item in sampled]) + s = torch.cat([item.s for item in sampled]) + a = torch.cat([item.a.long() for item in sampled]) + d = torch.cat([item.done.float() for item in sampled]).flatten().cpu().numpy() + # masking = self.sample_mask(d) - def y(self, s_prime, masking, r, y_hat,s,a): - distr_v=self(s,only_q=False) - state_action_values=distr_v[range(s.size()[0]), a.data] + batch_size=len(r) + + # next state distribution + next_distr_v, next_qvals_v=self.target_model.both(s_prime) + next_actions=next_qvals_v.max(1)[1].data.cpu().numpy() + next_distr=self.target_model.apply_softmax(next_distr_v).data.cpu().numpy() + + next_best_distr=next_distr[range(batch_size), next_actions] + dones=d.astype(np.bool) + + # project our distribution using Bellman update + proj_distr=distr_projection(next_best_distr, r, dones, self.v_min, self.v_max, self.n_atoms, self.discount) + + # calculate net output + distr_v=self.action_model(s) + state_action_values=distr_v[range(batch_size), a.data] state_log_sm_v=F.log_softmax(state_action_values, dim=1) - return state_log_sm_v + proj_distr_v=torch.tensor(proj_distr).to(self.action_model.supports.device) - def y_hat(self, s, a,s_prime,r,masking): - next_distr_v, next_q_vals_v=self.both(s_prime) - next_actions=next_q_vals_v.max(1)[1].data.cpu().numpy() - next_distr=self.apply_softmax(next_distr_v).data.cpu() - next_best_distr=next_distr[range(s_prime.size()[0]),next_actions] - proj_distr=distr_projection(next_best_distr,r,masking,self.v_min,self.v_max,self.n_atoms,self.discount) - proj_distr_v=torch.tensor(proj_distr).to(device=self.action_model.supports.device) - return proj_distr_v + loss=-state_log_sm_v*proj_distr_v + loss= loss.sum(dim=1).mean() + + with torch.no_grad(): + self.loss = loss + _,y=self.action_model.both(s.to(device=self.action_model.supports.device)) + post_info = {'td_error': to_detach(y - next_qvals_v).cpu().numpy()} + return post_info + + def q_vals(self,xi): + return self.action_model.both(xi)[1] + + # def y(self, s_prime, masking, r, y_hat,s,a): + # distr_v=self(s,only_q=False) + # state_action_values=distr_v[range(s.size()[0]), a.data] + # state_log_sm_v=F.log_softmax(state_action_values, dim=1) + # return state_log_sm_v + # + # def y_hat(self, s, a,s_prime,r,masking): + # next_distr_v, next_q_vals_v=self.both(s_prime,True) # target + # next_actions=next_q_vals_v.max(1)[1].data.cpu().numpy() + # next_distr=self.apply_softmax(next_distr_v,True).data.cpu() # target + # next_best_distr=next_distr[range(s_prime.size()[0]),next_actions] + # proj_distr=distr_projection(next_best_distr,r,masking,self.v_min,self.v_max,self.n_atoms,self.discount) + # proj_distr_v=torch.tensor(proj_distr).to(device=self.action_model.supports.device) + # return proj_distr_v def forward(self, xi: Tensor,only_q=True): - return self.q_vals(xi) if only_q else super(DistributionalDQN,self).forward(xi).view(xi.size()[0],-1,self.n_atoms) \ No newline at end of file + bs=xi.size()[0] + return self.q_vals(xi) if only_q else super(DistributionalDQN,self).forward(xi).view(bs,-1,self.n_atoms) \ No newline at end of file diff --git a/fast_rl/agents/native_dist_dqn.py b/fast_rl/agents/native_dist_dqn.py new file mode 100644 index 0000000..eab0cc4 --- /dev/null +++ b/fast_rl/agents/native_dist_dqn.py @@ -0,0 +1,1722 @@ +#!/usr/bin/env python3 +import gym + +import numpy as np +import argparse + +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.optim as optim + +"""basic wrappers, useful for reinforcement learning on gym envs""" +# Mostly copy-pasted from https://github.com/openai/baselines/blob/master/baselines/common/atari_wrappers.py +import numpy as np +from collections import deque +import gym +from gym import spaces +import cv2 + +import gym +import torch +import random +import collections +from torch.autograd import Variable + +import numpy as np + +from collections import namedtuple, deque + + +# one single experience step +Experience = namedtuple('Experience', ['state', 'action', 'reward', 'done']) + + +import numpy as np + +import sys +import time +import operator +from datetime import timedelta +import numpy as np +import collections + +import torch +import torch.nn as nn + + +class SMAQueue: + """ + Queue of fixed size with mean, max, min operations + """ + def __init__(self, size): + self.queue = collections.deque() + self.size = size + + def __iadd__(self, other): + if isinstance(other, (list, tuple)): + self.queue.extend(other) + else: + self.queue.append(other) + while len(self.queue) > self.size: + self.queue.popleft() + return self + + def __len__(self): + return len(self.queue) + + def __repr__(self): + return "SMAQueue(size=%d)" % self.size + + def __str__(self): + return "SMAQueue(size=%d, len=%d)" % (self.size, len(self.queue)) + + def min(self): + if not self.queue: + return None + return np.min(self.queue) + + def mean(self): + if not self.queue: + return None + return np.mean(self.queue) + + def max(self): + if not self.queue: + return None + return np.max(self.queue) + + +class SpeedMonitor: + def __init__(self, batch_size, autostart=True): + self.batch_size = batch_size + self.start_ts = None + self.batches = None + if autostart: + self.reset() + + def epoch(self): + if self.epoches is not None: + self.epoches += 1 + + def batch(self): + if self.batches is not None: + self.batches += 1 + + def reset(self): + self.start_ts = time.time() + self.batches = 0 + self.epoches = 0 + + def seconds(self): + """ + Seconds since last reset + :return: + """ + return time.time() - self.start_ts + + def samples_per_sec(self): + """ + Calculate samples per second since last reset() call + :return: float count samples per second or None if not started + """ + if self.start_ts is None: + return None + secs = self.seconds() + if abs(secs) < 1e-5: + return 0.0 + return (self.batches + 1) * self.batch_size / secs + + def epoch_time(self): + """ + Calculate average epoch time + :return: timedelta object + """ + if self.start_ts is None: + return None + s = self.seconds() + if self.epoches > 0: + s /= self.epoches + 1 + return timedelta(seconds=s) + + def batch_time(self): + """ + Calculate average batch time + :return: timedelta object + """ + if self.start_ts is None: + return None + s = self.seconds() + if self.batches > 0: + s /= self.batches + 1 + return timedelta(seconds=s) + + +class WeightedMSELoss(nn.Module): + def __init__(self, size_average=True): + super(WeightedMSELoss, self).__init__() + self.size_average = size_average + + def forward(self, input, target, weights=None): + if weights is None: + return nn.MSELoss(self.size_average)(input, target) + + loss_rows = (input - target) ** 2 + if len(loss_rows.size()) != 1: + loss_rows = torch.sum(loss_rows, dim=1) + res = (weights * loss_rows).sum() + if self.size_average: + res /= len(weights) + return res + + +class SegmentTree(object): + def __init__(self, capacity, operation, neutral_element): + """Build a Segment Tree data structure. + + https://en.wikipedia.org/wiki/Segment_tree + + Can be used as regular array, but with two + important differences: + + a) setting item's value is slightly slower. + It is O(lg capacity) instead of O(1). + b) user has access to an efficient `reduce` + operation which reduces `operation` over + a contiguous subsequence of items in the + array. + + Paramters + --------- + capacity: int + Total size of the array - must be a power of two. + operation: lambda obj, obj -> obj + and operation for combining elements (eg. sum, max) + must for a mathematical group together with the set of + possible values for array elements. + neutral_element: obj + neutral element for the operation above. eg. float('-inf') + for max and 0 for sum. + """ + assert capacity > 0 and capacity & (capacity - 1) == 0, "capacity must be positive and a power of 2." + self._capacity = capacity + self._value = [neutral_element for _ in range(2 * capacity)] + self._operation = operation + + def _reduce_helper(self, start, end, node, node_start, node_end): + if start == node_start and end == node_end: + return self._value[node] + mid = (node_start + node_end) // 2 + if end <= mid: + return self._reduce_helper(start, end, 2 * node, node_start, mid) + else: + if mid + 1 <= start: + return self._reduce_helper(start, end, 2 * node + 1, mid + 1, node_end) + else: + return self._operation( + self._reduce_helper(start, mid, 2 * node, node_start, mid), + self._reduce_helper(mid + 1, end, 2 * node + 1, mid + 1, node_end) + ) + + def reduce(self, start=0, end=None): + """Returns result of applying `self.operation` + to a contiguous subsequence of the array. + + self.operation(arr[start], operation(arr[start+1], operation(... arr[end]))) + + Parameters + ---------- + start: int + beginning of the subsequence + end: int + end of the subsequences + + Returns + ------- + reduced: obj + result of reducing self.operation over the specified range of array elements. + """ + if end is None: + end = self._capacity + if end < 0: + end += self._capacity + end -= 1 + return self._reduce_helper(start, end, 1, 0, self._capacity - 1) + + def __setitem__(self, idx, val): + # index of the leaf + idx += self._capacity + self._value[idx] = val + idx //= 2 + while idx >= 1: + self._value[idx] = self._operation( + self._value[2 * idx], + self._value[2 * idx + 1] + ) + idx //= 2 + + def __getitem__(self, idx): + assert 0 <= idx < self._capacity + return self._value[self._capacity + idx] + + +class SumSegmentTree(SegmentTree): + def __init__(self, capacity): + super(SumSegmentTree, self).__init__( + capacity=capacity, + operation=operator.add, + neutral_element=0.0 + ) + + def sum(self, start=0, end=None): + """Returns arr[start] + ... + arr[end]""" + return super(SumSegmentTree, self).reduce(start, end) + + def find_prefixsum_idx(self, prefixsum): + """Find the highest index `i` in the array such that + sum(arr[0] + arr[1] + ... + arr[i - i]) <= prefixsum + + if array values are probabilities, this function + allows to sample indexes according to the discrete + probability efficiently. + + Parameters + ---------- + perfixsum: float + upperbound on the sum of array prefix + + Returns + ------- + idx: int + highest index satisfying the prefixsum constraint + """ + assert 0 <= prefixsum <= self.sum() + 1e-5 + idx = 1 + while idx < self._capacity: # while non-leaf + if self._value[2 * idx] > prefixsum: + idx = 2 * idx + else: + prefixsum -= self._value[2 * idx] + idx = 2 * idx + 1 + return idx - self._capacity + + +class MinSegmentTree(SegmentTree): + def __init__(self, capacity): + super(MinSegmentTree, self).__init__( + capacity=capacity, + operation=min, + neutral_element=float('inf') + ) + + def min(self, start=0, end=None): + """Returns min(arr[start], ..., arr[end])""" + + return super(MinSegmentTree, self).reduce(start, end) + + +class TBMeanTracker: + """ + TensorBoard value tracker: allows to batch fixed amount of historical values and write their mean into TB + + Designed and tested with pytorch-tensorboard in mind + """ + def __init__(self, writer, batch_size): + """ + :param writer: writer with close() and add_scalar() methods + :param batch_size: integer size of batch to track + """ + assert isinstance(batch_size, int) + assert writer is not None + self.writer = writer + self.batch_size = batch_size + + def __enter__(self): + self._batches = collections.defaultdict(list) + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + self.writer.close() + + @staticmethod + def _as_float(value): + assert isinstance(value, (float, int, np.ndarray, np.generic, torch.autograd.Variable)) or torch.is_tensor(value) + tensor_val = None + if isinstance(value, torch.autograd.Variable): + tensor_val = value.data + elif torch.is_tensor(value): + tensor_val = value + + if tensor_val is not None: + return tensor_val.float().mean() + elif isinstance(value, np.ndarray): + return float(np.mean(value)) + else: + return float(value) + + def track(self, param_name, value, iter_index): + assert isinstance(param_name, str) + assert isinstance(iter_index, int) + + data = self._batches[param_name] + data.append(self._as_float(value)) + + if len(data) >= self.batch_size: + self.writer.add_scalar(param_name, np.mean(data), iter_index) + data.clear() + + +class RewardTracker: + def __init__(self, writer): + self.writer = writer + + def __enter__(self): + self.ts = time.time() + self.ts_frame = 0 + self.total_rewards = [] + return self + + def __exit__(self, *args): + self.writer.close() + + def reward(self, reward, frame, epsilon=None): + self.total_rewards.append(reward) + speed = (frame - self.ts_frame) / (time.time() - self.ts) + self.ts_frame = frame + self.ts = time.time() + mean_reward = np.mean(self.total_rewards[-100:]) + epsilon_str = "" if epsilon is None else ", eps %.2f" % epsilon + print("%d: done %d episodes, mean reward %.3f, speed %.2f f/s%s" % ( + frame, len(self.total_rewards), mean_reward, speed, epsilon_str + )) + sys.stdout.flush() + if epsilon is not None: + self.writer.add_scalar("epsilon", epsilon, frame) + self.writer.add_scalar("speed", speed, frame) + self.writer.add_scalar("reward_100", mean_reward, frame) + self.writer.add_scalar("reward", reward, frame) + return mean_reward if len(self.total_rewards) > 30 else None + + + +class ActionSelector: + """ + Abstract class which converts scores to the actions + """ + def __call__(self, scores): + raise NotImplementedError + + +class ArgmaxActionSelector(ActionSelector): + """ + Selects actions using argmax + """ + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + return np.argmax(scores, axis=1) + + +class EpsilonGreedyActionSelector(ActionSelector): + def __init__(self, epsilon=0.05, selector=None): + self.epsilon = epsilon + self.selector = selector if selector is not None else ArgmaxActionSelector() + + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + batch_size, n_actions = scores.shape + actions = self.selector(scores) + mask = np.random.random(size=batch_size) < self.epsilon + rand_actions = np.random.choice(n_actions, sum(mask)) + actions[mask] = rand_actions + return actions + + +class ProbabilityActionSelector(ActionSelector): + """ + Converts probabilities of actions into action by sampling them + """ + def __call__(self, probs): + assert isinstance(probs, np.ndarray) + actions = [] + for prob in probs: + actions.append(np.random.choice(len(prob), p=prob)) + return np.array(actions) + + + +class ExperienceSource: + """ + Simple n-step experience source using single or multiple environments + + Every experience contains n list of Experience entries + """ + def __init__(self, env, agent, steps_count=2, steps_delta=1, vectorized=False): + """ + Create simple experience source + :param env: environment or list of environments to be used + :param agent: callable to convert batch of states into actions to take + :param steps_count: count of steps to track for every experience chain + :param steps_delta: how many steps to do between experience items + :param vectorized: support of vectorized envs from OpenAI universe + """ + assert isinstance(env, (gym.Env, list, tuple)) + assert isinstance(agent, BaseAgent) + assert isinstance(steps_count, int) + assert steps_count >= 1 + assert isinstance(vectorized, bool) + if isinstance(env, (list, tuple)): + self.pool = env + else: + self.pool = [env] + self.agent = agent + self.steps_count = steps_count + self.steps_delta = steps_delta + self.total_rewards = [] + self.total_steps = [] + self.vectorized = vectorized + + def __iter__(self): + states, agent_states, histories, cur_rewards, cur_steps = [], [], [], [], [] + env_lens = [] + for env in self.pool: + obs = env.reset() + # if the environment is vectorized, all it's output is lists of results. + # Details are here: https://github.com/openai/universe/blob/master/doc/env_semantics.rst + if self.vectorized: + obs_len = len(obs) + states.extend(obs) + else: + obs_len = 1 + states.append(obs) + env_lens.append(obs_len) + + for _ in range(obs_len): + histories.append(deque(maxlen=self.steps_count)) + cur_rewards.append(0.0) + cur_steps.append(0) + agent_states.append(self.agent.initial_state()) + + iter_idx = 0 + while True: + actions = [None] * len(states) + states_input = [] + states_indices = [] + for idx, state in enumerate(states): + if state is None: + actions[idx] = self.pool[0].action_space.sample() # assume that all envs are from the same family + else: + states_input.append(state) + states_indices.append(idx) + if states_input: + states_actions, new_agent_states = self.agent(states_input, agent_states) + for idx, action in enumerate(states_actions): + g_idx = states_indices[idx] + actions[g_idx] = action + agent_states[g_idx] = new_agent_states[idx] + grouped_actions = _group_list(actions, env_lens) + + global_ofs = 0 + for env_idx, (env, action_n) in enumerate(zip(self.pool, grouped_actions)): + if self.vectorized: + next_state_n, r_n, is_done_n, _ = env.step(action_n) + else: + next_state, r, is_done, _ = env.step(action_n[0]) + next_state_n, r_n, is_done_n = [next_state], [r], [is_done] + + for ofs, (action, next_state, r, is_done) in enumerate(zip(action_n, next_state_n, r_n, is_done_n)): + idx = global_ofs + ofs + state = states[idx] + history = histories[idx] + + cur_rewards[idx] += r + cur_steps[idx] += 1 + if state is not None: + history.append(Experience(state=state, action=action, reward=r, done=is_done)) + if len(history) == self.steps_count and iter_idx % self.steps_delta == 0: + yield tuple(history) + states[idx] = next_state + if is_done: + # generate tail of history + while len(history) >= 1: + yield tuple(history) + history.popleft() + self.total_rewards.append(cur_rewards[idx]) + self.total_steps.append(cur_steps[idx]) + cur_rewards[idx] = 0.0 + cur_steps[idx] = 0 + # vectorized envs are reset automatically + states[idx] = env.reset() if not self.vectorized else None + agent_states[idx] = self.agent.initial_state() + history.clear() + global_ofs += len(action_n) + iter_idx += 1 + + def pop_total_rewards(self): + r = self.total_rewards + if r: + self.total_rewards = [] + self.total_steps = [] + return r + + def pop_rewards_steps(self): + res = list(zip(self.total_rewards, self.total_steps)) + if res: + self.total_rewards, self.total_steps = [], [] + return res + + +def _group_list(items, lens): + """ + Unflat the list of items by lens + :param items: list of items + :param lens: list of integers + :return: list of list of items grouped by lengths + """ + res = [] + cur_ofs = 0 + for g_len in lens: + res.append(items[cur_ofs:cur_ofs+g_len]) + cur_ofs += g_len + return res + + +# those entries are emitted from ExperienceSourceFirstLast. Reward is discounted over the trajectory piece +ExperienceFirstLast = collections.namedtuple('ExperienceFirstLast', ('state', 'action', 'reward', 'last_state')) + + +class ExperienceSourceFirstLast(ExperienceSource): + """ + This is a wrapper around ExperienceSource to prevent storing full trajectory in replay buffer when we need + only first and last states. For every trajectory piece it calculates discounted reward and emits only first + and last states and action taken in the first state. + + If we have partial trajectory at the end of episode, last_state will be None + """ + def __init__(self, env, agent, gamma, steps_count=1, steps_delta=1, vectorized=False): + assert isinstance(gamma, float) + super(ExperienceSourceFirstLast, self).__init__(env, agent, steps_count+1, steps_delta, vectorized=vectorized) + self.gamma = gamma + self.steps = steps_count + + def __iter__(self): + for exp in super(ExperienceSourceFirstLast, self).__iter__(): + if exp[-1].done and len(exp) <= self.steps: + last_state = None + elems = exp + else: + last_state = exp[-1].state + elems = exp[:-1] + total_reward = 0.0 + for e in reversed(elems): + total_reward *= self.gamma + total_reward += e.reward + yield ExperienceFirstLast(state=exp[0].state, action=exp[0].action, + reward=total_reward, last_state=last_state) + + +def discount_with_dones(rewards, dones, gamma): + discounted = [] + r = 0 + for reward, done in zip(rewards[::-1], dones[::-1]): + r = reward + gamma*r*(1.-done) + discounted.append(r) + return discounted[::-1] + + +class ExperienceSourceRollouts: + """ + N-step rollout experience source following A3C rollouts scheme. Have to be used with agent, + keeping the value in its state (for example, agent.ActorCriticAgent). + + Yields batches of num_envs * n_steps samples with the following arrays: + 1. observations + 2. actions + 3. discounted rewards, with values approximation + 4. values + """ + def __init__(self, env, agent, gamma, steps_count=5): + """ + Constructs the rollout experience source + :param env: environment or list of environments to be used + :param agent: callable to convert batch of states into actions + :param steps_count: how many steps to perform rollouts + """ + assert isinstance(env, (gym.Env, list, tuple)) + assert isinstance(agent, BaseAgent) + assert isinstance(gamma, float) + assert isinstance(steps_count, int) + assert steps_count >= 1 + + if isinstance(env, (list, tuple)): + self.pool = env + else: + self.pool = [env] + self.agent = agent + self.gamma = gamma + self.steps_count = steps_count + self.total_rewards = [] + self.total_steps = [] + + def __iter__(self): + pool_size = len(self.pool) + states = [np.array(e.reset()) for e in self.pool] + mb_states = np.zeros((pool_size, self.steps_count) + states[0].shape, dtype=states[0].dtype) + mb_rewards = np.zeros((pool_size, self.steps_count), dtype=np.float32) + mb_values = np.zeros((pool_size, self.steps_count), dtype=np.float32) + mb_actions = np.zeros((pool_size, self.steps_count), dtype=np.int64) + mb_dones = np.zeros((pool_size, self.steps_count), dtype=np.bool) + total_rewards = [0.0] * pool_size + total_steps = [0] * pool_size + agent_states = None + step_idx = 0 + + while True: + actions, agent_states = self.agent(states, agent_states) + rewards = [] + dones = [] + new_states = [] + for env_idx, (e, action) in enumerate(zip(self.pool, actions)): + o, r, done, _ = e.step(action) + total_rewards[env_idx] += r + total_steps[env_idx] += 1 + if done: + o = e.reset() + self.total_rewards.append(total_rewards[env_idx]) + self.total_steps.append(total_steps[env_idx]) + total_rewards[env_idx] = 0.0 + total_steps[env_idx] = 0 + new_states.append(np.array(o)) + dones.append(done) + rewards.append(r) + # we need an extra step to get values approximation for rollouts + if step_idx == self.steps_count: + # calculate rollout rewards + for env_idx, (env_rewards, env_dones, last_value) in enumerate(zip(mb_rewards, mb_dones, agent_states)): + env_rewards = env_rewards.tolist() + env_dones = env_dones.tolist() + if not env_dones[-1]: + env_rewards = discount_with_dones(env_rewards + [last_value], env_dones + [False], self.gamma)[:-1] + else: + env_rewards = discount_with_dones(env_rewards, env_dones, self.gamma) + mb_rewards[env_idx] = env_rewards + yield mb_states.reshape((-1,) + mb_states.shape[2:]), mb_rewards.flatten(), mb_actions.flatten(), mb_values.flatten() + step_idx = 0 + mb_states[:, step_idx] = states + mb_rewards[:, step_idx] = rewards + mb_values[:, step_idx] = agent_states + mb_actions[:, step_idx] = actions + mb_dones[:, step_idx] = dones + step_idx += 1 + states = new_states + + def pop_total_rewards(self): + r = self.total_rewards + if r: + self.total_rewards = [] + self.total_steps = [] + return r + + def pop_rewards_steps(self): + res = list(zip(self.total_rewards, self.total_steps)) + if res: + self.total_rewards, self.total_steps = [], [] + return res + + +class ExperienceSourceBuffer: + """ + The same as ExperienceSource, but takes episodes from the buffer + """ + def __init__(self, buffer, steps_count=1): + """ + Create buffered experience source + :param buffer: list of episodes, each is a list of Experience object + :param steps_count: count of steps in every entry + """ + self.update_buffer(buffer) + self.steps_count = steps_count + + def update_buffer(self, buffer): + self.buffer = buffer + self.lens = list(map(len, buffer)) + + def __iter__(self): + """ + Infinitely sample episode from the buffer and then sample item offset + """ + while True: + episode = random.randrange(len(self.buffer)) + ofs = random.randrange(self.lens[episode] - self.steps_count - 1) + yield self.buffer[episode][ofs:ofs+self.steps_count] + + +class ExperienceReplayBuffer: + def __init__(self, experience_source, buffer_size): + assert isinstance(experience_source, (ExperienceSource, type(None))) + assert isinstance(buffer_size, int) + self.experience_source_iter = None if experience_source is None else iter(experience_source) + self.buffer = [] + self.capacity = buffer_size + self.pos = 0 + + def __len__(self): + return len(self.buffer) + + def __iter__(self): + return iter(self.buffer) + + def sample(self, batch_size): + """ + Get one random batch from experience replay + TODO: implement sampling order policy + :param batch_size: + :return: + """ + if len(self.buffer) <= batch_size: + return self.buffer + # Warning: replace=False makes random.choice O(n) + keys = np.random.choice(len(self.buffer), batch_size, replace=True) + return [self.buffer[key] for key in keys] + + def _add(self, sample): + if len(self.buffer) < self.capacity: + self.buffer.append(sample) + else: + self.buffer[self.pos] = sample + self.pos = (self.pos + 1) % self.capacity + + def populate(self, samples): + """ + Populates samples into the buffer + :param samples: how many samples to populate + """ + for _ in range(samples): + entry = next(self.experience_source_iter) + self._add(entry) + +class PrioReplayBufferNaive: + def __init__(self, exp_source, buf_size, prob_alpha=0.6): + self.exp_source_iter = iter(exp_source) + self.prob_alpha = prob_alpha + self.capacity = buf_size + self.pos = 0 + self.buffer = [] + self.priorities = np.zeros((buf_size, ), dtype=np.float32) + + def __len__(self): + return len(self.buffer) + + def populate(self, count): + max_prio = self.priorities.max() if self.buffer else 1.0 + for _ in range(count): + sample = next(self.exp_source_iter) + if len(self.buffer) < self.capacity: + self.buffer.append(sample) + else: + self.buffer[self.pos] = sample + self.priorities[self.pos] = max_prio + self.pos = (self.pos + 1) % self.capacity + + def sample(self, batch_size, beta=0.4): + if len(self.buffer) == self.capacity: + prios = self.priorities + else: + prios = self.priorities[:self.pos] + probs = np.array(prios, dtype=np.float32) ** self.prob_alpha + + probs /= probs.sum() + indices = np.random.choice(len(self.buffer), batch_size, p=probs, replace=True) + samples = [self.buffer[idx] for idx in indices] + total = len(self.buffer) + weights = (total * probs[indices]) ** (-beta) + weights /= weights.max() + return samples, indices, np.array(weights, dtype=np.float32) + + def update_priorities(self, batch_indices, batch_priorities): + for idx, prio in zip(batch_indices, batch_priorities): + self.priorities[idx] = prio + + +class PrioritizedReplayBuffer(ExperienceReplayBuffer): + def __init__(self, experience_source, buffer_size, alpha): + super(PrioritizedReplayBuffer, self).__init__(experience_source, buffer_size) + assert alpha > 0 + self._alpha = alpha + + it_capacity = 1 + while it_capacity < buffer_size: + it_capacity *= 2 + + self._it_sum = SumSegmentTree(it_capacity) + self._it_min = MinSegmentTree(it_capacity) + self._max_priority = 1.0 + + def _add(self, *args, **kwargs): + idx = self.pos + super()._add(*args, **kwargs) + self._it_sum[idx] = self._max_priority ** self._alpha + self._it_min[idx] = self._max_priority ** self._alpha + + def _sample_proportional(self, batch_size): + res = [] + for _ in range(batch_size): + mass = random.random() * self._it_sum.sum(0, len(self) - 1) + idx = self._it_sum.find_prefixsum_idx(mass) + res.append(idx) + return res + + def sample(self, batch_size, beta): + assert beta > 0 + + idxes = self._sample_proportional(batch_size) + + weights = [] + p_min = self._it_min.min() / self._it_sum.sum() + max_weight = (p_min * len(self)) ** (-beta) + + for idx in idxes: + p_sample = self._it_sum[idx] / self._it_sum.sum() + weight = (p_sample * len(self)) ** (-beta) + weights.append(weight / max_weight) + weights = np.array(weights, dtype=np.float32) + samples = [self.buffer[idx] for idx in idxes] + return samples, idxes, weights + + def update_priorities(self, idxes, priorities): + assert len(idxes) == len(priorities) + for idx, priority in zip(idxes, priorities): + assert priority > 0 + assert 0 <= idx < len(self) + self._it_sum[idx] = priority ** self._alpha + self._it_min[idx] = priority ** self._alpha + + self._max_priority = max(self._max_priority, priority) + + +class BatchPreprocessor: + """ + Abstract preprocessor class descendants to which converts experience + batch to form suitable to learning. + """ + def preprocess(self, batch): + raise NotImplementedError + + +class QLearningPreprocessor(BatchPreprocessor): + """ + Supports SimpleDQN, TargetDQN, DoubleDQN and can additionally feed TD-error back to + experience replay buffer. + + To use different modes, use appropriate class method + """ + def __init__(self, model, target_model, use_double_dqn=False, batch_td_error_hook=None, gamma=0.99, device="cpu"): + self.model = model + self.target_model = target_model + self.use_double_dqn = use_double_dqn + self.batch_dt_error_hook = batch_td_error_hook + self.gamma = gamma + self.device = device + + @staticmethod + def simple_dqn(model, **kwargs): + return QLearningPreprocessor(model=model, target_model=None, use_double_dqn=False, **kwargs) + + @staticmethod + def target_dqn(model, target_model, **kwards): + return QLearningPreprocessor(model, target_model, use_double_dqn=False, **kwards) + + @staticmethod + def double_dqn(model, target_model, **kwargs): + return QLearningPreprocessor(model, target_model, use_double_dqn=True, **kwargs) + + def _calc_Q(self, states_first, states_last): + """ + Calculates apropriate q values for first and last states. Way of calculate depends on our settings. + :param states_first: numpy array of first states + :param states_last: numpy array of last states + :return: tuple of numpy arrays of q values + """ + # here we need both first and last values calculated using our main model, so we + # combine both states into one batch for efficiency and separate results later + if self.target_model is None or self.use_double_dqn: + states_t = torch.tensor(np.concatenate((states_first, states_last), axis=0)).to(self.device) + res_both = self.model(states_t).data.cpu().numpy() + return res_both[:len(states_first)], res_both[len(states_first):] + + # in this case we have target_model set and use_double_dqn==False + # so, we should calculate first_q and last_q using different models + states_first_v = torch.tensor(states_first).to(self.device) + states_last_v = torch.tensor(states_last).to(self.device) + q_first = self.model(states_first_v).data + q_last = self.target_model(states_last_v).data + return q_first.cpu().numpy(), q_last.cpu().numpy() + + def _calc_target_rewards(self, states_last, q_last): + """ + Calculate rewards from final states according to variants from our construction: + 1. simple DQN: max(Q(states, model)) + 2. target DQN: max(Q(states, target_model)) + 3. double DQN: Q(states, target_model)[argmax(Q(states, model)] + :param states_last: numpy array of last states from the games + :param q_last: numpy array of last q values + :return: vector of target rewards + """ + # in this case we handle both simple DQN and target DQN + if self.target_model is None or not self.use_double_dqn: + return q_last.max(axis=1) + + # here we have target_model set and use_double_dqn==True + actions = q_last.argmax(axis=1) + # calculate Q values using target net + states_last_v = torch.tensor(states_last).to(self.device) + q_last_target = self.target_model(states_last_v).data.cpu().numpy() + return q_last_target[range(q_last_target.shape[0]), actions] + + def preprocess(self, batch): + """ + Calculates data for Q learning from batch of observations + :param batch: list of lists of Experience objects + :return: tuple of numpy arrays: + 1. states -- observations + 2. target Q-values + 3. vector of td errors for every batch entry + """ + # first and last states for every entry + state_0 = np.array([exp[0].state for exp in batch], dtype=np.float32) + state_L = np.array([exp[-1].state for exp in batch], dtype=np.float32) + + q0, qL = self._calc_Q(state_0, state_L) + rewards = self._calc_target_rewards(state_L, qL) + + td = np.zeros(shape=(len(batch),)) + + for idx, (total_reward, exps) in enumerate(zip(rewards, batch)): + # game is done, no final reward + if exps[-1].done: + total_reward = 0.0 + for exp in reversed(exps[:-1]): + total_reward *= self.gamma + total_reward += exp.reward + # update total reward and calculate td error + act = exps[0].action + td[idx] = q0[idx][act] - total_reward + q0[idx][act] = total_reward + + return state_0, q0, td + + +class NoopResetEnv(gym.Wrapper): + def __init__(self, env=None, noop_max=30): + """Sample initial states by taking random number of no-ops on reset. + No-op is assumed to be action 0. + """ + super(NoopResetEnv, self).__init__(env) + self.noop_max = noop_max + self.override_num_noops = None + assert env.unwrapped.get_action_meanings()[0] == 'NOOP' + + def step(self, action): + return self.env.step(action) + + def reset(self): + """ Do no-op action for a number of steps in [1, noop_max].""" + self.env.reset() + if self.override_num_noops is not None: + noops = self.override_num_noops + else: + noops = np.random.randint(1, self.noop_max + 1) + assert noops > 0 + obs = None + for _ in range(noops): + obs, _, done, _ = self.env.step(0) + if done: + obs = self.env.reset() + return obs + + +class FireResetEnv(gym.Wrapper): + def __init__(self, env=None): + """For environments where the user need to press FIRE for the game to start.""" + super(FireResetEnv, self).__init__(env) + assert env.unwrapped.get_action_meanings()[1] == 'FIRE' + assert len(env.unwrapped.get_action_meanings()) >= 3 + + def step(self, action): + return self.env.step(action) + + def reset(self): + self.env.reset() + obs, _, done, _ = self.env.step(1) + if done: + self.env.reset() + obs, _, done, _ = self.env.step(2) + if done: + self.env.reset() + return obs + + +class EpisodicLifeEnv(gym.Wrapper): + def __init__(self, env=None): + """Make end-of-life == end-of-episode, but only reset on true game over. + Done by DeepMind for the DQN and co. since it helps value estimation. + """ + super(EpisodicLifeEnv, self).__init__(env) + self.lives = 0 + self.was_real_done = True + self.was_real_reset = False + + def step(self, action): + obs, reward, done, info = self.env.step(action) + self.was_real_done = done + # check current lives, make loss of life terminal, + # then update lives to handle bonus lives + lives = self.env.unwrapped.ale.lives() + if lives < self.lives and lives > 0: + # for Qbert somtimes we stay in lives == 0 condtion for a few frames + # so its important to keep lives > 0, so that we only reset once + # the environment advertises done. + done = True + self.lives = lives + return obs, reward, done, info + + def reset(self): + """Reset only when lives are exhausted. + This way all states are still reachable even though lives are episodic, + and the learner need not know about any of this behind-the-scenes. + """ + if self.was_real_done: + obs = self.env.reset() + self.was_real_reset = True + else: + # no-op step to advance from terminal/lost life state + obs, _, _, _ = self.env.step(0) + self.was_real_reset = False + self.lives = self.env.unwrapped.ale.lives() + return obs + + +class MaxAndSkipEnv(gym.Wrapper): + def __init__(self, env=None, skip=4): + """Return only every `skip`-th frame""" + super(MaxAndSkipEnv, self).__init__(env) + # most recent raw observations (for max pooling across time steps) + self._obs_buffer = deque(maxlen=2) + self._skip = skip + + def step(self, action): + total_reward = 0.0 + done = None + for _ in range(self._skip): + obs, reward, done, info = self.env.step(action) + self._obs_buffer.append(obs) + total_reward += reward + if done: + break + + max_frame = np.max(np.stack(self._obs_buffer), axis=0) + + return max_frame, total_reward, done, info + + def reset(self): + """Clear past frame buffer and init. to first obs. from inner env.""" + self._obs_buffer.clear() + obs = self.env.reset() + self._obs_buffer.append(obs) + return obs + + +class ProcessFrame84(gym.ObservationWrapper): + def __init__(self, env=None): + super(ProcessFrame84, self).__init__(env) + self.observation_space = spaces.Box(low=0, high=255, shape=(84, 84, 1), dtype=np.uint8) + + def observation(self, obs): + return ProcessFrame84.process(obs) + + @staticmethod + def process(frame): + if frame.size == 210 * 160 * 3: + img = np.reshape(frame, [210, 160, 3]).astype(np.float32) + elif frame.size == 250 * 160 * 3: + img = np.reshape(frame, [250, 160, 3]).astype(np.float32) + else: + assert False, "Unknown resolution." + img = img[:, :, 0] * 0.299 + img[:, :, 1] * 0.587 + img[:, :, 2] * 0.114 + resized_screen = cv2.resize(img, (84, 110), interpolation=cv2.INTER_AREA) + x_t = resized_screen[18:102, :] + x_t = np.reshape(x_t, [84, 84, 1]) + return x_t.astype(np.uint8) + + +class ClippedRewardsWrapper(gym.RewardWrapper): + def reward(self, reward): + """Change all the positive rewards to 1, negative to -1 and keep zero.""" + return np.sign(reward) + + +class LazyFrames(object): + def __init__(self, frames): + """This object ensures that common frames between the observations are only stored once. + It exists purely to optimize memory usage which can be huge for DQN's 1M frames replay + buffers. + This object should only be converted to numpy array before being passed to the model. + You'd not belive how complex the previous solution was.""" + self._frames = frames + + def __array__(self, dtype=None): + out = np.concatenate(self._frames, axis=0) + if dtype is not None: + out = out.astype(dtype) + return out + + +class FrameStack(gym.Wrapper): + def __init__(self, env, k): + """Stack k last frames. + Returns lazy array, which is much more memory efficient. + See Also + -------- + baselines.common.atari_wrappers.LazyFrames + """ + gym.Wrapper.__init__(self, env) + self.k = k + self.frames = deque([], maxlen=k) + shp = env.observation_space.shape + self.observation_space = spaces.Box(low=0, high=255, shape=(shp[0]*k, shp[1], shp[2]), dtype=np.float32) + + def reset(self): + ob = self.env.reset() + for _ in range(self.k): + self.frames.append(ob) + return self._get_ob() + + def step(self, action): + ob, reward, done, info = self.env.step(action) + self.frames.append(ob) + return self._get_ob(), reward, done, info + + def _get_ob(self): + assert len(self.frames) == self.k + return LazyFrames(list(self.frames)) + + +class ScaledFloatFrame(gym.ObservationWrapper): + def observation(self, obs): + # careful! This undoes the memory optimization, use + # with smaller replay buffers only. + return np.array(obs).astype(np.float32) / 255.0 + + +class ImageToPyTorch(gym.ObservationWrapper): + """ + Change image shape to CWH + """ + def __init__(self, env): + super(ImageToPyTorch, self).__init__(env) + old_shape = self.observation_space.shape + self.observation_space = gym.spaces.Box(low=0.0, high=1.0, shape=(old_shape[-1], old_shape[0], old_shape[1]), + dtype=np.float32) + + def observation(self, observation): + return np.swapaxes(observation, 2, 0) + + +def wrap_dqn(env, stack_frames=4, episodic_life=True, reward_clipping=True): + """Apply a common set of wrappers for Atari games.""" + assert 'NoFrameskip' in env.spec.id + if episodic_life: + env = EpisodicLifeEnv(env) + env = NoopResetEnv(env, noop_max=30) + env = MaxAndSkipEnv(env, skip=4) + if 'FIRE' in env.unwrapped.get_action_meanings(): + env = FireResetEnv(env) + env = ProcessFrame84(env) + env = ImageToPyTorch(env) + env = FrameStack(env, stack_frames) + if reward_clipping: + env = ClippedRewardsWrapper(env) + return env + + +from tensorboardX import SummaryWriter + +import sys +import time +import numpy as np +import torch +import torch.nn as nn + + +HYPERPARAMS = { + 'cartpole': { + 'env_name': "CartPole-v1", + 'stop_reward': 199.0, + 'run_name': 'cartpole', + 'replay_size': 100000, + 'replay_initial': 32, + 'target_net_sync': 300, + 'epsilon_frames': 10 ** 2, + 'epsilon_start': 1.0, + 'epsilon_final': 0.02, + 'learning_rate': 0.0001, + 'gamma': 0.99, + 'batch_size': 32 + }, + 'pong': { + 'env_name': "PongNoFrameskip-v4", + 'stop_reward': 18.0, + 'run_name': 'pong', + 'replay_size': 100000, + 'replay_initial': 10000, + 'target_net_sync': 1000, + 'epsilon_frames': 10**5, + 'epsilon_start': 1.0, + 'epsilon_final': 0.02, + 'learning_rate': 0.0001, + 'gamma': 0.99, + 'batch_size': 32 + }, + 'breakout-small': { + 'env_name': "BreakoutNoFrameskip-v4", + 'stop_reward': 500.0, + 'run_name': 'breakout-small', + 'replay_size': 3*10 ** 5, + 'replay_initial': 20000, + 'target_net_sync': 1000, + 'epsilon_frames': 10 ** 6, + 'epsilon_start': 1.0, + 'epsilon_final': 0.1, + 'learning_rate': 0.0001, + 'gamma': 0.99, + 'batch_size': 64 + }, + 'breakout': { + 'env_name': "BreakoutNoFrameskip-v4", + 'stop_reward': 500.0, + 'run_name': 'breakout', + 'replay_size': 10 ** 6, + 'replay_initial': 50000, + 'target_net_sync': 10000, + 'epsilon_frames': 10 ** 6, + 'epsilon_start': 1.0, + 'epsilon_final': 0.1, + 'learning_rate': 0.00025, + 'gamma': 0.99, + 'batch_size': 32 + }, + 'invaders': { + 'env_name': "SpaceInvadersNoFrameskip-v4", + 'stop_reward': 500.0, + 'run_name': 'breakout', + 'replay_size': 10 ** 6, + 'replay_initial': 50000, + 'target_net_sync': 10000, + 'epsilon_frames': 10 ** 6, + 'epsilon_start': 1.0, + 'epsilon_final': 0.1, + 'learning_rate': 0.00025, + 'gamma': 0.99, + 'batch_size': 32 + }, +} +""" +Agent is something which converts states into actions and has state +""" + + +class BaseAgent: + """ + Abstract Agent interface + """ + def initial_state(self): + """ + Should create initial empty state for the agent. It will be called for the start of the episode + :return: Anything agent want to remember + """ + return None + + def __call__(self, states, agent_states): + """ + Convert observations and states into actions to take + :param states: list of environment states to process + :param agent_states: list of states with the same length as observations + :return: tuple of actions, states + """ + assert isinstance(states, list) + assert isinstance(agent_states, list) + assert len(agent_states) == len(states) + + raise NotImplementedError + + +def default_states_preprocessor(states): + """ + Convert list of states into the form suitable for model. By default we assume Variable + :param states: list of numpy arrays with states + :return: Variable + """ + if len(states) == 1: + np_states = np.expand_dims(states[0], 0) + else: + np_states = np.array([np.array(s, copy=False) for s in states], copy=False) + return torch.tensor(np_states) + + +def float32_preprocessor(states): + np_states = np.array(states, dtype=np.float32) + return torch.tensor(np_states) + + +class DQNAgent(BaseAgent): + """ + DQNAgent is a memoryless DQN agent which calculates Q values + from the observations and converts them into the actions using action_selector + """ + def __init__(self, dqn_model, action_selector, device="cpu", preprocessor=default_states_preprocessor): + self.dqn_model = dqn_model + self.action_selector = action_selector + self.preprocessor = preprocessor + self.device = device + + def __call__(self, states, agent_states=None): + if agent_states is None: + agent_states = [None] * len(states) + if self.preprocessor is not None: + states = self.preprocessor(states) + if torch.is_tensor(states): + states = states.to(self.device) + q_v = self.dqn_model(states) + q = q_v.data.cpu().numpy() + actions = self.action_selector(q) + return actions, agent_states + + +class TargetNet: + """ + Wrapper around model which provides copy of it instead of trained weights + """ + def __init__(self, model): + self.model = model + import copy + self.target_model = copy.deepcopy(model) + + def sync(self): + self.target_model.load_state_dict(self.model.state_dict()) + + def alpha_sync(self, alpha): + """ + Blend params of target net with params from the model + :param alpha: + """ + assert isinstance(alpha, float) + assert 0.0 < alpha <= 1.0 + state = self.model.state_dict() + tgt_state = self.target_model.state_dict() + for k, v in state.items(): + tgt_state[k] = tgt_state[k] * alpha + (1 - alpha) * v + self.target_model.load_state_dict(tgt_state) + + +class PolicyAgent(BaseAgent): + """ + Policy agent gets action probabilities from the model and samples actions from it + """ + # TODO: unify code with DQNAgent, as only action selector is differs. + def __init__(self, model, action_selector=ProbabilityActionSelector(), device="cpu", + apply_softmax=False, preprocessor=default_states_preprocessor): + self.model = model + self.action_selector = action_selector + self.device = device + self.apply_softmax = apply_softmax + self.preprocessor = preprocessor + + def __call__(self, states, agent_states=None): + """ + Return actions from given list of states + :param states: list of states + :return: list of actions + """ + if agent_states is None: + agent_states = [None] * len(states) + if self.preprocessor is not None: + states = self.preprocessor(states) + if torch.is_tensor(states): + states = states.to(self.device) + probs_v = self.model(states) + if self.apply_softmax: + probs_v = F.softmax(probs_v, dim=1) + probs = probs_v.data.cpu().numpy() + actions = self.action_selector(probs) + return np.array(actions), agent_states + + +class ActorCriticAgent(BaseAgent): + """ + Policy agent which returns policy and value tensors from observations. Value are stored in agent's state + and could be reused for rollouts calculations by ExperienceSource. + """ + def __init__(self, model, action_selector=ProbabilityActionSelector(), device="cpu", + apply_softmax=False, preprocessor=default_states_preprocessor): + self.model = model + self.action_selector = action_selector + self.device = device + self.apply_softmax = apply_softmax + self.preprocessor = preprocessor + + def __call__(self, states, agent_states=None): + """ + Return actions from given list of states + :param states: list of states + :return: list of actions + """ + if self.preprocessor is not None: + states = self.preprocessor(states) + if torch.is_tensor(states): + states = states.to(self.device) + probs_v, values_v = self.model(states) + if self.apply_softmax: + probs_v = F.softmax(probs_v, dim=1) + probs = probs_v.data.cpu().numpy() + actions = self.action_selector(probs) + agent_states = values_v.data.squeeze().cpu().numpy().tolist() + return np.array(actions), agent_states + + +def unpack_batch(batch): + states, actions, rewards, dones, last_states = [], [], [], [], [] + for exp in batch: + state = np.array(exp.state, copy=False) + states.append(state) + actions.append(exp.action) + rewards.append(exp.reward) + dones.append(exp.last_state is None) + if exp.last_state is None: + last_states.append(state) # the result will be masked anyway + else: + last_states.append(np.array(exp.last_state, copy=False)) + return np.array(states, copy=False), np.array(actions), np.array(rewards, dtype=np.float32), \ + np.array(dones, dtype=np.uint8), np.array(last_states, copy=False) + + +def calc_loss_dqn(batch, net, tgt_net, gamma, device="cpu"): + states, actions, rewards, dones, next_states = unpack_batch(batch) + + states_v = torch.tensor(states).to(device) + next_states_v = torch.tensor(next_states).to(device) + actions_v = torch.tensor(actions).to(device) + rewards_v = torch.tensor(rewards).to(device) + done_mask = torch.ByteTensor(dones).to(device) + + state_action_values = net(states_v).gather(1, actions_v.unsqueeze(-1)).squeeze(-1) + next_state_values = tgt_net(next_states_v).max(1)[0] + next_state_values[done_mask] = 0.0 + + expected_state_action_values = next_state_values.detach() * gamma + rewards_v + return nn.MSELoss()(state_action_values, expected_state_action_values) + + +class RewardTracker: + def __init__(self, writer, stop_reward): + self.writer = writer + self.stop_reward = stop_reward + + def __enter__(self): + self.ts = time.time() + self.ts_frame = 0 + self.total_rewards = [] + return self + + def __exit__(self, *args): + self.writer.close() + + def reward(self, reward, frame, epsilon=None): + self.total_rewards.append(reward) + speed = (frame - self.ts_frame) / (time.time() - self.ts) + self.ts_frame = frame + self.ts = time.time() + mean_reward = np.mean(self.total_rewards[-100:]) + epsilon_str = "" if epsilon is None else ", eps %.2f" % epsilon + print("%d: done %d games, mean reward %.3f, speed %.2f f/s%s" % ( + frame, len(self.total_rewards), mean_reward, speed, epsilon_str + )) + sys.stdout.flush() + if epsilon is not None: + self.writer.add_scalar("epsilon", epsilon, frame) + self.writer.add_scalar("speed", speed, frame) + self.writer.add_scalar("reward_100", mean_reward, frame) + self.writer.add_scalar("reward", reward, frame) + if mean_reward > self.stop_reward: + print("Solved in %d frames!" % frame) + return True + return False + + +class EpsilonTracker: + def __init__(self, epsilon_greedy_selector, params): + self.epsilon_greedy_selector = epsilon_greedy_selector + self.epsilon_start = params['epsilon_start'] + self.epsilon_final = params['epsilon_final'] + self.epsilon_frames = params['epsilon_frames'] + self.frame(0) + + def frame(self, frame): + self.epsilon_greedy_selector.epsilon = \ + max(self.epsilon_final, self.epsilon_start - frame / self.epsilon_frames) + + +def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): + """ + Perform distribution projection aka Catergorical Algorithm from the + "A Distributional Perspective on RL" paper + """ + batch_size = len(rewards) + proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) + delta_z = (Vmax - Vmin) / (n_atoms - 1) + for atom in range(n_atoms): + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + proj_distr[eq_mask, l[eq_mask]] += next_distr[eq_mask, atom] + ne_mask = u != l + proj_distr[ne_mask, l[ne_mask]] += next_distr[ne_mask, atom] * (u - b_j)[ne_mask] + proj_distr[ne_mask, u[ne_mask]] += next_distr[ne_mask, atom] * (b_j - l)[ne_mask] + if dones.any(): + proj_distr[dones] = 0.0 + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards[dones])) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + eq_dones = dones.copy() + eq_dones[dones] = eq_mask + if eq_dones.any(): + proj_distr[eq_dones, l[eq_mask]] = 1.0 + ne_mask = u != l + ne_dones = dones.copy() + ne_dones[dones] = ne_mask + if ne_dones.any(): + proj_distr[ne_dones, l[ne_mask]] = (u - b_j)[ne_mask] + proj_distr[ne_dones, u[ne_mask]] = (b_j - l)[ne_mask] + return proj_distr + + +Vmax = 10 +Vmin = -10 +N_ATOMS = 51 +DELTA_Z = (Vmax - Vmin) / (N_ATOMS - 1) + + +class DistributionalDQN(nn.Module): + def __init__(self, input_shape, n_actions): + super(DistributionalDQN, self).__init__() + + self.fc = nn.Sequential( + nn.Linear(input_shape[0], 512), + nn.ReLU(), + nn.Linear(512, n_actions * N_ATOMS) + ) + + self.register_buffer("supports", torch.arange(Vmin, Vmax+DELTA_Z, DELTA_Z)) + self.softmax = nn.Softmax(dim=1) + + def forward(self, x): + batch_size = x.size()[0] + fc_out = self.fc(x.float()) + return fc_out.view(batch_size, -1, N_ATOMS) + + def both(self, x): + cat_out = self(x) + probs = self.apply_softmax(cat_out) + weights = probs * self.supports + res = weights.sum(dim=2) + return cat_out, res + + def qvals(self, x): + return self.both(x)[1] + + def apply_softmax(self, t): + return self.softmax(t.view(-1, N_ATOMS)).view(t.size()) + +def calc_loss(batch, net, tgt_net, gamma, device="cpu", save_prefix=None): + states, actions, rewards, dones, next_states = unpack_batch(batch) + batch_size = len(batch) + + states_v = torch.tensor(states).to(device) + actions_v = torch.tensor(actions).to(device) + next_states_v = torch.tensor(next_states).to(device) + + # next state distribution + next_distr_v, next_qvals_v = tgt_net.both(next_states_v) + next_actions = next_qvals_v.max(1)[1].data.cpu().numpy() + next_distr = tgt_net.apply_softmax(next_distr_v).data.cpu().numpy() + + next_best_distr = next_distr[range(batch_size), next_actions] + dones = dones.astype(np.bool) + + # project our distribution using Bellman update + proj_distr = distr_projection(next_best_distr, rewards, dones, Vmin, Vmax, N_ATOMS, gamma) + + # calculate net output + distr_v = net(states_v) + state_action_values = distr_v[range(batch_size), actions_v.data] + state_log_sm_v = F.log_softmax(state_action_values, dim=1) + proj_distr_v = torch.tensor(proj_distr).to(device) + + loss_v = -state_log_sm_v * proj_distr_v + return loss_v.sum(dim=1).mean() + + +if __name__ == "__main__": + params = HYPERPARAMS['cartpole'] +# params['epsilon_frames'] *= 2 + parser = argparse.ArgumentParser() + parser.add_argument("--cuda", default=False, action="store_true", help="Enable cuda") + args = parser.parse_args() + device = torch.device("cuda" if args.cuda or True else "cpu") + + env = gym.make(params['env_name']) + + writer = SummaryWriter(comment="-" + params['run_name'] + "-distrib") + net = DistributionalDQN(env.observation_space.shape, env.action_space.n).to(device) + + tgt_net = TargetNet(net) + selector = EpsilonGreedyActionSelector(epsilon=params['epsilon_start']) + epsilon_tracker = EpsilonTracker(selector, params) + agent = DQNAgent(lambda x: net.qvals(x), selector, device=device) + + exp_source = ExperienceSourceFirstLast(env, agent, gamma=params['gamma'], steps_count=1) + buffer = ExperienceReplayBuffer(exp_source, buffer_size=params['replay_size']) + optimizer = optim.Adam(net.parameters(), lr=params['learning_rate']) + + frame_idx = 0 + eval_states = None + prev_save = 0 + save_prefix = None + + with RewardTracker(writer, params['stop_reward']) as reward_tracker: + while True: + frame_idx += 1 + buffer.populate(1) + epsilon_tracker.frame(frame_idx) + + new_rewards = exp_source.pop_total_rewards() + if new_rewards: + if reward_tracker.reward(new_rewards[0], frame_idx, selector.epsilon): + break + + if len(buffer) < params['replay_initial']: + continue + + optimizer.zero_grad() + batch = buffer.sample(params['batch_size']) + + loss_v = calc_loss(batch, net, tgt_net.target_model, gamma=params['gamma'], + device=device, save_prefix=save_prefix) + loss_v.backward() + # print(str(loss_v.data)) + optimizer.step() + + if frame_idx % params['target_net_sync'] == 0: + tgt_net.sync() diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index 361ef0a..0bd7611 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -154,7 +154,7 @@ def __len__(self): def sample(self, batch, **kwargs): if len(self._memory) Date: Thu, 23 Apr 2020 07:21:00 -0400 Subject: [PATCH 26/29] Added: - RAINBOW dqn. Currently it is one of the worst performing dqns. In the next update (1.2) --- README.md | 2 +- fast_rl/agents/dist_dqn.py | 40 +---- fast_rl/agents/native_dist_dqn.py | 210 ++++++++++++++++++++++++--- fast_rl/agents/rainbow_dqn.py | 203 ++++++++++++++++++++++++++ fast_rl/agents/rainbow_dqn_models.py | 66 +++++++++ fast_rl/core/agent_core.py | 68 +++++++-- fast_rl/core/layers.py | 78 +++++++--- tests/test_dist_dqn.py | 12 ++ tests/test_dqn.py | 10 +- tests/test_rainbow_dqn.py | 27 ++++ 10 files changed, 618 insertions(+), 98 deletions(-) create mode 100644 fast_rl/agents/rainbow_dqn.py create mode 100644 fast_rl/agents/rainbow_dqn_models.py create mode 100644 tests/test_rainbow_dqn.py diff --git a/README.md b/README.md index 1a8bf23..1c7e26b 100644 --- a/README.md +++ b/README.md @@ -113,7 +113,7 @@ OpenAI environments. - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - [X] Add Distributional DQN - - [ ] **Working on** Add RAINBOW DQN + - [X] Add RAINBOW DQN (Note warnings, will require refactor / re-testing) - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO diff --git a/fast_rl/agents/dist_dqn.py b/fast_rl/agents/dist_dqn.py index 1687a19..f8c3a79 100644 --- a/fast_rl/agents/dist_dqn.py +++ b/fast_rl/agents/dist_dqn.py @@ -5,6 +5,7 @@ from fastai.imports import torch, Any from fast_rl.agents.dist_dqn_models import TargetNet +from fast_rl.agents.dqn_models import distr_projection from fast_rl.core.agent_core import ExperienceReplay, NStepExperienceReplay from fast_rl.core.basic_train import AgentLearner, listify, List from fast_rl.core.data_block import MDPDataBunch, MDPStep @@ -29,45 +30,6 @@ -def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): - """ - Perform distribution projection aka Catergorical Algorithm from the - "A Distributional Perspective on RL" paper - """ - batch_size = len(rewards) - proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) - delta_z = (Vmax - Vmin) / (n_atoms - 1) - for atom in range(n_atoms): - tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) - b_j = (tz_j - Vmin) / delta_z - l = np.floor(b_j).astype(np.int64) - u = np.ceil(b_j).astype(np.int64) - eq_mask = u == l - proj_distr[eq_mask, l[eq_mask]] += next_distr[eq_mask, atom] - ne_mask = u != l - proj_distr[ne_mask, l[ne_mask]] += next_distr[ne_mask, atom] * (u - b_j)[ne_mask] - proj_distr[ne_mask, u[ne_mask]] += next_distr[ne_mask, atom] * (b_j - l)[ne_mask] - if dones.any(): - proj_distr[dones] = 0.0 - tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards[dones])) - b_j = (tz_j - Vmin) / delta_z - l = np.floor(b_j).astype(np.int64) - u = np.ceil(b_j).astype(np.int64) - eq_mask = u == l - eq_dones = dones.copy() - eq_dones[dones] = eq_mask - if eq_dones.any(): - proj_distr[eq_dones, l[eq_mask]] = 1.0 - ne_mask = u != l - ne_dones = dones.copy() - ne_dones[dones] = ne_mask - if ne_dones.any(): - proj_distr[ne_dones, l[ne_mask]] = (u - b_j)[ne_mask] - proj_distr[ne_dones, u[ne_mask]] = (b_j - l)[ne_mask] - return proj_distr - - - def unpack_batch(batch): states, actions, rewards, dones, last_states = [], [], [], [], [] for exp in batch: diff --git a/fast_rl/agents/native_dist_dqn.py b/fast_rl/agents/native_dist_dqn.py index eab0cc4..13cd77c 100644 --- a/fast_rl/agents/native_dist_dqn.py +++ b/fast_rl/agents/native_dist_dqn.py @@ -1,4 +1,6 @@ #!/usr/bin/env python3 +import math + import gym import numpy as np @@ -1668,42 +1670,213 @@ def calc_loss(batch, net, tgt_net, gamma, device="cpu", save_prefix=None): return loss_v.sum(dim=1).mean() +# if __name__ == "__main__": +# params = HYPERPARAMS['cartpole'] +# # params['epsilon_frames'] *= 2 +# parser = argparse.ArgumentParser() +# parser.add_argument("--cuda", default=False, action="store_true", help="Enable cuda") +# args = parser.parse_args() +# device = torch.device("cuda" if args.cuda or True else "cpu") +# +# env = gym.make(params['env_name']) +# +# writer = SummaryWriter(comment="-" + params['run_name'] + "-distrib") +# net = DistributionalDQN(env.observation_space.shape, env.action_space.n).to(device) +# +# tgt_net = TargetNet(net) +# selector = EpsilonGreedyActionSelector(epsilon=params['epsilon_start']) +# epsilon_tracker = EpsilonTracker(selector, params) +# agent = DQNAgent(lambda x: net.qvals(x), selector, device=device) +# +# exp_source = ExperienceSourceFirstLast(env, agent, gamma=params['gamma'], steps_count=1) +# buffer = ExperienceReplayBuffer(exp_source, buffer_size=params['replay_size']) +# optimizer = optim.Adam(net.parameters(), lr=params['learning_rate']) +# +# frame_idx = 0 +# eval_states = None +# prev_save = 0 +# save_prefix = None +# +# with RewardTracker(writer, params['stop_reward']) as reward_tracker: +# while True: +# frame_idx += 1 +# buffer.populate(1) +# epsilon_tracker.frame(frame_idx) +# +# new_rewards = exp_source.pop_total_rewards() +# if new_rewards: +# if reward_tracker.reward(new_rewards[0], frame_idx, selector.epsilon): +# break +# +# if len(buffer) < params['replay_initial']: +# continue +# +# optimizer.zero_grad() +# batch = buffer.sample(params['batch_size']) +# +# loss_v = calc_loss(batch, net, tgt_net.target_model, gamma=params['gamma'], +# device=device, save_prefix=save_prefix) +# loss_v.backward() +# # print(str(loss_v.data)) +# optimizer.step() +# +# if frame_idx % params['target_net_sync'] == 0: +# tgt_net.sync() + + +class NoisyLinear(nn.Linear): + def __init__(self, in_features, out_features, sigma_init=0.017, bias=True): + super(NoisyLinear, self).__init__(in_features, out_features, bias=bias) + self.sigma_weight = nn.Parameter(torch.full((out_features, in_features), sigma_init)) + self.register_buffer("epsilon_weight", torch.zeros(out_features, in_features)) + if bias: + self.sigma_bias = nn.Parameter(torch.full((out_features,), sigma_init)) + self.register_buffer("epsilon_bias", torch.zeros(out_features)) + self.reset_parameters() + + def reset_parameters(self): + std = math.sqrt(3 / self.in_features) + self.weight.data.uniform_(-std, std) + self.bias.data.uniform_(-std, std) + + def forward(self, input): + self.epsilon_weight.normal_() + bias = self.bias + if bias is not None: + self.epsilon_bias.normal_() + bias = bias + self.sigma_bias * self.epsilon_bias.data + return F.linear(input, self.weight + self.sigma_weight * self.epsilon_weight.data, bias) + + +class NoisyFactorizedLinear(nn.Linear): + """ + NoisyNet layer with factorized gaussian noise + + N.B. nn.Linear already initializes weight and bias to + """ + def __init__(self, in_features, out_features, sigma_zero=0.4, bias=True): + super(NoisyFactorizedLinear, self).__init__(in_features, out_features, bias=bias) + sigma_init = sigma_zero / math.sqrt(in_features) + self.sigma_weight = nn.Parameter(torch.full((out_features, in_features), sigma_init)) + self.register_buffer("epsilon_input", torch.zeros(1, in_features)) + self.register_buffer("epsilon_output", torch.zeros(out_features, 1)) + if bias: + self.sigma_bias = nn.Parameter(torch.full((out_features,), sigma_init)) + + def forward(self, input): + self.epsilon_input.normal_() + self.epsilon_output.normal_() + + func = lambda x: torch.sign(x) * torch.sqrt(torch.abs(x)) + eps_in = func(self.epsilon_input.data) + eps_out = func(self.epsilon_output.data) + + bias = self.bias + if bias is not None: + bias = bias + self.sigma_bias * eps_out.t() + noise_v = torch.mul(eps_in, eps_out) + return F.linear(input, self.weight + self.sigma_weight * noise_v, bias) + + +class DQN(nn.Module): + def __init__(self, input_shape, n_actions): + super(DQN, self).__init__() + + # self.conv = nn.Sequential( + # nn.Conv2d(input_shape[0], 32, kernel_size=8, stride=4), + # nn.ReLU(), + # nn.Conv2d(32, 64, kernel_size=4, stride=2), + # nn.ReLU(), + # nn.Conv2d(64, 64, kernel_size=3, stride=1), + # nn.ReLU() + # ) + # + # conv_out_size = self._get_conv_out(input_shape) + self.fc = nn.Sequential( + nn.Linear(input_shape[0], 512), + nn.ReLU(), + nn.Linear(512, n_actions) + ) + + def _get_conv_out(self, shape): + o = self.conv(torch.zeros(1, *shape)) + return int(np.prod(o.size())) + + def forward(self, x): + fx = x.float()# / 256 + # conv_out = self.conv(fx).view(fx.size()[0], -1) + return self.fc(fx) + + +class NoisyDQN(nn.Module): + def __init__(self, input_shape, n_actions): + super(NoisyDQN, self).__init__() + + # self.conv = nn.Sequential( + # nn.Conv2d(input_shape[0], 32, kernel_size=8, stride=4), + # nn.ReLU(), + # nn.Conv2d(32, 64, kernel_size=4, stride=2), + # nn.ReLU(), + # nn.Conv2d(64, 64, kernel_size=3, stride=1), + # nn.ReLU() + # ) + # + # conv_out_size = self._get_conv_out(input_shape) + self.noisy_layers = [ + NoisyLinear(input_shape[0], 512), + NoisyLinear(512, n_actions) + ] + self.fc = nn.Sequential( + self.noisy_layers[0], + nn.ReLU(), + self.noisy_layers[1] + ) + + def _get_conv_out(self, shape): + o = self.conv(torch.zeros(1, *shape)) + return int(np.prod(o.size())) + + def forward(self, x): + fx = x.float() #/ 256 + # conv_out = self.conv(fx).view(fx.size()[0], -1) + return self.fc(fx) + + def noisy_layers_sigma_snr(self): + return [ + ((layer.weight ** 2).mean().sqrt() / (layer.sigma_weight ** 2).mean().sqrt()).item() + for layer in self.noisy_layers + ] + + if __name__ == "__main__": params = HYPERPARAMS['cartpole'] -# params['epsilon_frames'] *= 2 parser = argparse.ArgumentParser() parser.add_argument("--cuda", default=False, action="store_true", help="Enable cuda") args = parser.parse_args() - device = torch.device("cuda" if args.cuda or True else "cpu") + device = torch.device("cuda" if args.cuda else "cpu") env = gym.make(params['env_name']) + # env = wrap_dqn(env) - writer = SummaryWriter(comment="-" + params['run_name'] + "-distrib") - net = DistributionalDQN(env.observation_space.shape, env.action_space.n).to(device) - + writer = SummaryWriter(comment="-" + params['run_name'] + "-noisy-net") + net = NoisyDQN(env.observation_space.shape, env.action_space.n).to(device) tgt_net = TargetNet(net) - selector = EpsilonGreedyActionSelector(epsilon=params['epsilon_start']) - epsilon_tracker = EpsilonTracker(selector, params) - agent = DQNAgent(lambda x: net.qvals(x), selector, device=device) + agent = DQNAgent(net, ArgmaxActionSelector(), device=device) exp_source = ExperienceSourceFirstLast(env, agent, gamma=params['gamma'], steps_count=1) buffer = ExperienceReplayBuffer(exp_source, buffer_size=params['replay_size']) optimizer = optim.Adam(net.parameters(), lr=params['learning_rate']) frame_idx = 0 - eval_states = None - prev_save = 0 - save_prefix = None with RewardTracker(writer, params['stop_reward']) as reward_tracker: while True: frame_idx += 1 buffer.populate(1) - epsilon_tracker.frame(frame_idx) new_rewards = exp_source.pop_total_rewards() if new_rewards: - if reward_tracker.reward(new_rewards[0], frame_idx, selector.epsilon): + if reward_tracker.reward(new_rewards[0], frame_idx): break if len(buffer) < params['replay_initial']: @@ -1711,12 +1884,15 @@ def calc_loss(batch, net, tgt_net, gamma, device="cpu", save_prefix=None): optimizer.zero_grad() batch = buffer.sample(params['batch_size']) - - loss_v = calc_loss(batch, net, tgt_net.target_model, gamma=params['gamma'], - device=device, save_prefix=save_prefix) + loss_v = calc_loss_dqn(batch, net, tgt_net.target_model, gamma=params['gamma'], device=device) loss_v.backward() - # print(str(loss_v.data)) + print(loss_v) optimizer.step() if frame_idx % params['target_net_sync'] == 0: tgt_net.sync() + + if frame_idx % 500 == 0: + for layer_idx, sigma_l2 in enumerate(net.noisy_layers_sigma_snr()): + writer.add_scalar("sigma_snr_layer_%d" % (layer_idx+1), + sigma_l2, frame_idx) \ No newline at end of file diff --git a/fast_rl/agents/rainbow_dqn.py b/fast_rl/agents/rainbow_dqn.py new file mode 100644 index 0000000..fc7c4f7 --- /dev/null +++ b/fast_rl/agents/rainbow_dqn.py @@ -0,0 +1,203 @@ +import collections +from copy import deepcopy +from warnings import warn + +from fastai.basic_train import LearnerCallback +from fastai.imports import torch, Any + +from fast_rl.agents.dist_dqn_models import TargetNet +from fast_rl.agents.dqn_models import distr_projection +from fast_rl.core.agent_core import ExperienceReplay, NStepExperienceReplay, NStepPriorityExperienceReplay +from fast_rl.core.basic_train import AgentLearner, listify, List +from fast_rl.core.data_block import MDPDataBunch, MDPStep +from fastai.imports import torch + +import gym +import numpy as np +import argparse + +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.optim as optim + +Vmax = 10 +Vmin = -10 +N_ATOMS = 51 +# Vmax = 5 +# Vmin = -5 +# N_ATOMS = 8 +DELTA_Z = (Vmax - Vmin) / (N_ATOMS - 1) + +ExperienceFirstLast = collections.namedtuple('ExperienceFirstLast', ('state', 'action', 'reward', 'last_state','done')) + + + + +def unpack_batch(batch): + states, actions, rewards, dones, last_states = [], [], [], [], [] + for exp in batch: + state = np.array(exp.state, copy=False) + states.append(state) + actions.append(exp.action) + rewards.append(exp.reward) + dones.append(exp.done) + # if exp.last_state is None: + # last_states.append(state) # the result will be masked anyway + # else: + last_states.append(np.array(exp.last_state, copy=False)) + return np.array(states, copy=False), np.array(actions), np.array(rewards, dtype=np.float32), \ + np.array(dones, dtype=np.uint8), np.array(last_states, copy=False) + + +def calc_loss(batch, batch_weights, net, tgt_net, gamma, device="cpu"): + states, actions, rewards, dones, next_states = unpack_batch(batch) + batch_size = len(batch) + + states_v = torch.tensor(states).to(device) + actions_v = torch.tensor(actions).to(device) + next_states_v = torch.tensor(next_states).to(device) + if batch_weights is not None: batch_weights_v = torch.tensor(batch_weights).to(device) + + # next state distribution + # dueling arch -- actions from main net, distr from tgt_net + + # calc at once both next and cur states + distr_v, qvals_v = net.both(torch.cat((states_v, next_states_v))) + next_qvals_v = qvals_v[batch_size:] + distr_v = distr_v[:batch_size] + + next_actions_v = next_qvals_v.max(1)[1] + next_distr_v = tgt_net(next_states_v) + next_best_distr_v = next_distr_v[range(batch_size), next_actions_v.data] + next_best_distr_v = tgt_net.apply_softmax(next_best_distr_v) + next_best_distr = next_best_distr_v.data.cpu().numpy() + + dones = dones.astype(np.bool) + + # project our distribution using Bellman update + proj_distr = distr_projection(next_best_distr, rewards, dones, Vmin, Vmax, N_ATOMS, gamma) + + # calculate net output + state_action_values = distr_v[range(batch_size), actions_v.data] + state_log_sm_v = F.log_softmax(state_action_values, dim=1) + proj_distr_v = torch.tensor(proj_distr).to(device) + + loss_v = -state_log_sm_v * proj_distr_v + if batch_weights is not None: loss_v = batch_weights_v * loss_v.sum(dim=1) + return loss_v.mean(), loss_v + 1e-5 + + +class BaseRainbowDQNTrainer(LearnerCallback): + def __init__(self, learn: 'DistDQNLearner', max_episodes=None): + r"""Handles basic DQN end of step model optimization.""" + super().__init__(learn) + self.n_skipped = 0 + self._persist = max_episodes is not None + self.max_episodes = max_episodes + self.episode = -1 + self.iteration = 0 + # For the callback handler + self._order = 0 + self.previous_item = None + + @property + def learn(self)->'RainbowDQNLearner': + return self._learn() + + def on_train_begin(self, n_epochs, **kwargs: Any): + self.max_episodes = n_epochs if not self._persist else self.max_episodes + + def on_epoch_begin(self, epoch, **kwargs: Any): + pass + + def on_backward_begin(self, **kwargs: Any):return {'skip_bwd': self.learn.warming_up} + def on_backward_end(self, **kwargs:Any): return {'skip_step':False} + def on_step_end(self, **kwargs: Any):return {'skip_zero': False} + + def on_loss_begin(self, **kwargs: Any): + r"""Performs tree updates, exploration updates, and model optimization.""" + if self.learn.model.training: + self.learn.memory.update(item=self.learn.data.x.items[-1]) + self.iteration+=1 + self.learn.epsilon_tracker.frame(self.iteration) + + if not self.learn.warming_up: + samples: List[MDPStep]=self.memory.sample(self.learn.data.bs) + batch=[ExperienceFirstLast(state=deepcopy(s.s[0]),action=deepcopy(s.action.taken_action), + reward=deepcopy(s.reward),last_state=deepcopy(s.s_prime[0]),done=deepcopy(s.done)) for s in samples] + # model_func=lambda x: self.learn.model.qvals(x) + loss,weight_loss=calc_loss(batch,self.memory.weights(),self.learn.model,self.learn.target_net.target_model,gamma=0.99,device=self.learn.data.device) + self.learn.memory.refresh({'td_error':weight_loss}) + return {'last_output':loss} + else: return None + + def on_batch_end(self, **kwargs:Any) ->None: + if self.iteration % 300 == 0: + self.learn.target_net.sync() + + +class ArgmaxActionSelector(object): + """ + Selects actions using argmax + """ + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + return np.argmax(scores, axis=1) + + +class EpsilonGreedyActionSelector(object): + def __init__(self, epsilon=0.05, selector=None): + self.epsilon = epsilon + self.selector = selector if selector is not None else ArgmaxActionSelector() + + def __call__(self, scores): + assert isinstance(scores, np.ndarray) + batch_size, n_actions = scores.shape + actions = self.selector(scores) + mask = np.random.random(size=batch_size) < self.epsilon + rand_actions = np.random.choice(n_actions, sum(mask)) + actions[mask] = rand_actions + return actions + +class EpsilonTracker: + def __init__(self, epsilon_greedy_selector, params): + self.epsilon_greedy_selector = epsilon_greedy_selector + self.epsilon_start = params['epsilon_start'] + self.epsilon_final = params['epsilon_final'] + self.epsilon_frames = params['epsilon_frames'] + self.frame(0) + + def frame(self, frame): + self.epsilon_greedy_selector.epsilon = \ + max(self.epsilon_final, self.epsilon_start - frame / self.epsilon_frames) + + + +class RainbowDQNLearner(AgentLearner): + def __init__(self, data: MDPDataBunch, model, trainers,use_per=True, loss_func=None,opt=torch.optim.Adam,**learn_kwargs): + super().__init__(data=data, model=model, opt=opt,loss_func=loss_func, **learn_kwargs) + self._loss_func=loss_func + self.memory=NStepPriorityExperienceReplay(100000,n_step=2) if use_per else NStepExperienceReplay(100000,step_sz=2) + if use_per: warn('Using per on simpler evs such as cartpole has not been solved at least before 2000 epochs. ' + 'We will see if there is a way to configure per to handling these simpler environments') + warn('RAINBOW for envs like cartpole is extremely slow on convergence requiring more than 600 epochs. ' + 'Due to a memory issue, we cannot test beyond this number of epochs to get detailed convergence.') + self.target_net=TargetNet(self.model) + self.exploration_method=EpsilonGreedyActionSelector(1.0) + self.epsilon_tracker=EpsilonTracker(self.exploration_method, {'epsilon_frames': 100, 'epsilon_start': 1.0, + 'epsilon_final': 0.02}) + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + + def init(self, init):pass + # def init_loss_func(self):pass + + def predict(self, element, **kwargs): + model_func=lambda x: self.model.qvals(x) + q_v=model_func(element) + q=q_v.data.cpu().numpy() + actions=self.exploration_method(q) + return actions + + diff --git a/fast_rl/agents/rainbow_dqn_models.py b/fast_rl/agents/rainbow_dqn_models.py new file mode 100644 index 0000000..abbb66d --- /dev/null +++ b/fast_rl/agents/rainbow_dqn_models.py @@ -0,0 +1,66 @@ +# n-step +from fast_rl.core.layers import * + +REWARD_STEPS = 2 + +# priority replay +PRIO_REPLAY_ALPHA = 0.6 +BETA_START = 0.4 +BETA_FRAMES = 100000 + +# C51 +Vmax = 10 +Vmin = -10 +N_ATOMS = 51 +DELTA_Z = (Vmax - Vmin) / (N_ATOMS - 1) + + +class RainbowDQN(nn.Module): + def __init__(self, input_shape, n_actions): + super(RainbowDQN, self).__init__() + + hd_sz=512 + + self.fc_val = nn.Sequential( + GaussianNoisyLinear(input_shape[0], hd_sz), + nn.ReLU(), + GaussianNoisyLinear(hd_sz, N_ATOMS) + ) + + self.fc_adv = nn.Sequential( + GaussianNoisyLinear(input_shape[0], hd_sz), + nn.ReLU(), + GaussianNoisyLinear(hd_sz, n_actions * N_ATOMS) + ) + + self.register_buffer("supports", torch.arange(Vmin, Vmax+DELTA_Z, DELTA_Z)) + self.softmax = nn.Softmax(dim=1) + + self.loss_func=None + + def _get_conv_out(self, shape): + o = self.conv(torch.zeros(1, *shape)) + return int(np.prod(o.size())) + + def forward(self, x): + batch_size = x.size()[0] + fx = x.float() + val_out = self.fc_val(fx).view(batch_size, 1, N_ATOMS) + adv_out = self.fc_adv(fx).view(batch_size, -1, N_ATOMS) + adv_mean = adv_out.mean(dim=1, keepdim=True) + return val_out + (adv_out - adv_mean) + + def set_opt(self, _): pass + + def both(self, x): + cat_out = self(x) + probs = self.apply_softmax(cat_out) + weights = probs * self.supports + res = weights.sum(dim=2) + return cat_out, res + + def qvals(self, x): + return self.both(x)[1] + + def apply_softmax(self, t): + return self.softmax(t.view(-1, N_ATOMS)).view(t.size()) diff --git a/fast_rl/core/agent_core.py b/fast_rl/core/agent_core.py index 0bd7611..75b61fe 100644 --- a/fast_rl/core/agent_core.py +++ b/fast_rl/core/agent_core.py @@ -5,6 +5,7 @@ from fastai.basic_train import * from fastai.torch_core import * +from fast_rl.core.data_block import MDPStep from fast_rl.core.data_structures import SumTree @@ -87,11 +88,17 @@ def __init__(self, memory_size, reduce_ram=False): def __len__(self): raise NotImplementedError('Experience needs a concept of size') + def weights(self): return None + @property def memory(self): return None def sample(self, **kwargs): pass - def update(self, item, **kwargs): item.to(device=defaults.device) - def refresh(self, **kwargs): pass + def update(self, item, **kwargs): + if isinstance(item,list): + for o in item: o.to(device=defaults.device) + else: + item.to(device=defaults.device) + def refresh(self, *args,**kwargs): pass class ExperienceReplay(Experience): @@ -215,11 +222,11 @@ def refresh(self, post_optimize, **kwargs): self.tree.update(self._indices.astype(int), np.abs(post_optimize['td_error'])+self.epsilon) def sample(self, batch, **kwargs): - self.beta=np.min([1., self.beta+self.b_inc]) ranges=np.linspace(0, ceil(self.tree.total()/batch), num=batch+1) uniform_ranges=[np.random.uniform(ranges[i], ranges[i+1]) for i in range(len(ranges)-1)] try: self._indices, weights, samples=self.tree.batch_get(uniform_ranges) + self.beta=np.min([1., self.beta+self.b_inc]) except ValueError: warn('Too few values to unpack. Your batch size is too small, when PER queries tree, all 0 values get' ' ignored. We will retry until we can return at least one sample.') @@ -248,15 +255,46 @@ def update(self, item, **kwargs): self.tree.add(np.abs(maximal_priority)+self.epsilon, item) -# class HindsightExperienceReplay(Experience): -# def __init__(self, memory_size): -# """ -# -# References: -# [1] Andrychowicz, Marcin, et al. "Hindsight experience replay." -# Advances in Neural Information Processing Systems. 2017. -# -# Args: -# memory_size: -# """ -# super().__init__(memory_size) + +class NStepPriorityExperienceReplay(PriorityExperienceReplay): + + def __init__(self, memory_size, n_step=1, **kwargs): + super().__init__(memory_size//n_step, **kwargs) + self.n_step=n_step + self._memory=[] + self._temp_samples=[] + + def refresh(self, post_optimize, **kwargs): + pre_td_error=[] + idx=0 + for item in self._temp_samples: + temp_td_error=[] + for _ in item: + temp_td_error.append(post_optimize['td_error'][idx]) + idx+=1 + pre_td_error.append(np.average(temp_td_error)) + post_optimize['td_error']=pre_td_error + super(NStepPriorityExperienceReplay, self).refresh(post_optimize) + + def weights(self): + individual_item_weights=[] + idx=0 + for item in self._temp_samples: + for _ in item: + individual_item_weights.append(self.p_weights[idx]) + idx+=1 + return individual_item_weights + + + def update(self, item:MDPStep, **kwargs): + item=deepcopy(item) + if len(self._memory)=self.n_step or item.done: + super(NStepPriorityExperienceReplay,self).update(deepcopy(self._memory)) + self._memory.clear() + + def sample(self, batch, **kwargs): + samples=super(NStepPriorityExperienceReplay, self).sample(batch//self.n_step) + self._temp_samples=samples + return [o for ll in samples for o in ll] \ No newline at end of file diff --git a/fast_rl/core/layers.py b/fast_rl/core/layers.py index f8ac2f4..eb20bbd 100644 --- a/fast_rl/core/layers.py +++ b/fast_rl/core/layers.py @@ -6,6 +6,45 @@ from torch.distributions import Normal +def distr_projection(next_distr, rewards, dones, Vmin, Vmax, n_atoms, gamma): + """ + Perform distribution projection aka Catergorical Algorithm from the + "A Distributional Perspective on RL" paper + """ + batch_size = len(rewards) + proj_distr = np.zeros((batch_size, n_atoms), dtype=np.float32) + delta_z = (Vmax - Vmin) / (n_atoms - 1) + for atom in range(n_atoms): + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards + (Vmin + atom * delta_z) * gamma)) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + proj_distr[eq_mask, l[eq_mask]] += next_distr[eq_mask, atom] + ne_mask = u != l + proj_distr[ne_mask, l[ne_mask]] += next_distr[ne_mask, atom] * (u - b_j)[ne_mask] + proj_distr[ne_mask, u[ne_mask]] += next_distr[ne_mask, atom] * (b_j - l)[ne_mask] + if dones.any(): + proj_distr[dones] = 0.0 + tz_j = np.minimum(Vmax, np.maximum(Vmin, rewards[dones])) + b_j = (tz_j - Vmin) / delta_z + l = np.floor(b_j).astype(np.int64) + u = np.ceil(b_j).astype(np.int64) + eq_mask = u == l + eq_dones = dones.copy() + eq_dones[dones] = eq_mask + if eq_dones.any(): + proj_distr[eq_dones, l[eq_mask]] = 1.0 + ne_mask = u != l + ne_dones = dones.copy() + ne_dones[dones] = ne_mask + if ne_dones.any(): + proj_distr[ne_dones, l[ne_mask]] = (u - b_j)[ne_mask] + proj_distr[ne_dones, u[ne_mask]] = (b_j - l)[ne_mask] + return proj_distr + + + def bn_drop_lin(n_in:int, n_out:int, bn:bool=True, p:float=0., actn:Optional[nn.Module]=None,lin_cls=nn.Linear): "Sequence of batchnorm (if `bn`), dropout (with `p`) and linear (`n_in`,`n_out`) layers followed by `actn`." layers = [nn.BatchNorm1d(n_in)] if bn else [] @@ -81,31 +120,28 @@ def forward(self, xi: Tensor, *args): return xi class GaussianNoisyLinear(nn.Linear): - def __init__(self, in_features, out_features, sigma_init=0.017, bias=True): - super().__init__(in_features, out_features, bias=bias) - self.sigma_weight=nn.Parameter(torch.full((out_features, in_features), sigma_init)) - self.register_buffer("epsilon_weight",torch.zeros(out_features,in_features)) - self.normal=Normal(0,1) + def __init__(self, in_features, out_features, sigma_zero=0.4, bias=True): + super(GaussianNoisyLinear, self).__init__(in_features, out_features, bias=bias) + sigma_init = sigma_zero / math.sqrt(in_features) + self.sigma_weight = nn.Parameter(torch.full((out_features, in_features), sigma_init)) + self.register_buffer("epsilon_input", torch.zeros(1, in_features)) + self.register_buffer("epsilon_output", torch.zeros(out_features, 1)) if bias: - self.sigma_bias=nn.Parameter(torch.full((out_features,),sigma_init)) - self.register_buffer("epsilon_bias", torch.zeros(out_features)) - self.reset_parameters() + self.sigma_bias = nn.Parameter(torch.full((out_features,), sigma_init)) + + def forward(self, input): + self.epsilon_input.normal_() + self.epsilon_output.normal_() - def reset_parameters(self): - std=math.sqrt(3/self.in_features) - self.weight.data.uniform_(-std,std) - self.bias.data.uniform_(-std,std) + func = lambda x: torch.sign(x) * torch.sqrt(torch.abs(x)) + eps_in = func(self.epsilon_input.data) + eps_out = func(self.epsilon_output.data) - def forward(self, xi): - # self.normal=Normal(0,1) - self.epsilon_weight.data.copy_(self.normal.sample(self.epsilon_weight.shape)) - bias=self.bias + bias = self.bias if bias is not None: - # self.epsilon_bias.normal_() - self.epsilon_bias.data.copy_(self.normal.sample(self.epsilon_bias.shape)) - bias=bias+self.sigma_bias*self.epsilon_bias - return F.linear(xi,self.weight+self.sigma_weight*self.epsilon_weight,bias) - + bias = bias + self.sigma_bias * eps_out.t() + noise_v = torch.mul(eps_in, eps_out) + return F.linear(input, self.weight + self.sigma_weight * noise_v, bias) class GaussianNoisyFactorizedLinear(nn.Linear): def __init__(self, in_features, out_features,sigma_zero=0.4,bias=True): diff --git a/tests/test_dist_dqn.py b/tests/test_dist_dqn.py index a212106..7ac826f 100644 --- a/tests/test_dist_dqn.py +++ b/tests/test_dist_dqn.py @@ -1,3 +1,5 @@ +import pytest + from fast_rl.agents.dist_dqn import DistDQNLearner, BaseDistDQNTrainer from fast_rl.agents.dist_dqn_models import DistributionalDQN from fast_rl.core.data_block import MDPDataBunch, partial, ResolutionWrapper @@ -5,6 +7,16 @@ def test_dist_dqn(): + data=MDPDataBunch.from_env('CartPole-v0', render='rgb_array', bs=4, add_valid=False, keep_env_open=False, + res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) + model=DistributionalDQN((4,),2) + metrics=[RewardMetric, RollingRewardMetric,EpsilonMetric] + learner=DistDQNLearner(data=data,model=model,trainers=BaseDistDQNTrainer,callback_fns=metrics,loss_func=lambda x,y:x) + learner.fit(3,wd=0,lr=0.0001) + + +@pytest.mark.usefixtures('skip_performance_check') +def test_dist_dqn_perf(): data=MDPDataBunch.from_env('CartPole-v0', render='human', bs=32, add_valid=False, keep_env_open=False, res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) model=DistributionalDQN((4,),2) diff --git a/tests/test_dqn.py b/tests/test_dqn.py index 8464c5d..26db85e 100644 --- a/tests/test_dqn.py +++ b/tests/test_dqn.py @@ -47,8 +47,8 @@ def trained_learner(model_cls, env, s_format, experience, bs, layers, memory_siz explore = ifnone(explore,GreedyEpsilon(epsilon_start=1, epsilon_end=0.02, decay=decay)) if type(lr) == list: lr = lr[0] if model_cls == DQNModule else lr[1] data = MDPDataBunch.from_env(env, render='human', bs=bs, add_valid=False, keep_env_open=False, feed_type=s_format, - memory_management_strategy='k_partitions_top', k=3,**kwargs) - if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.RMSprop,lin_cls=ifnone(lin_cls,nn.Linear),**model_kwargs) + memory_management_strategy='k_partitions_top', k=1,**kwargs) + if model_cls == DQNModule: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers, opt=optim.Adam,lin_cls=ifnone(lin_cls,nn.Linear),**model_kwargs) else: model = create_dqn_model(data=data, base_arch=model_cls, lr=lr, layers=layers,lin_cls=ifnone(lin_cls,nn.Linear),**model_kwargs) learn = dqn_learner(data, model, memory=memory, exploration_method=explore, copy_over_frequency=copy_over_frequency, callback_fns=metrics) @@ -175,13 +175,13 @@ def test_dqn_models_distributional_cartpole(s_format): @pytest.mark.parametrize(["model_cls", "s_format",'layer_cls'], list(product(p_model, p_format,layer_clss))) def test_dqn_models_noisy_layers_cartpole(model_cls, s_format,layer_cls): - experience=NStepExperienceReplay + experience=ExperienceReplay group_interp = GroupAgentInterpretation() extra_s=f'{experience.__name__}_{model_cls.__name__}_{s_format}_{layer_cls.__name__}' for i in range(1): # Since we are using noisy layers, just use default exploration strategy (no exploration) - learn = trained_learner(model_cls, 'CartPole-v1', s_format, experience, bs=32, layers=[64, 64], - memory_size=1000000, decay=0.001,lin_cls=layer_cls,explore=ExplorationStrategy(),epochs=450) + learn = trained_learner(model_cls, 'CartPole-v1', s_format, experience, bs=32, layers=[512],lr=0.0001, + memory_size=100000, decay=0.01,lin_cls=layer_cls,explore=ExplorationStrategy(),epochs=800) learner2gif(learn,s_format,group_interp,'cartpole_layer_exp',extra_s) diff --git a/tests/test_rainbow_dqn.py b/tests/test_rainbow_dqn.py new file mode 100644 index 0000000..1cb10cf --- /dev/null +++ b/tests/test_rainbow_dqn.py @@ -0,0 +1,27 @@ +from time import sleep + +import pytest + +from fast_rl.agents.rainbow_dqn import * +from fast_rl.agents.rainbow_dqn_models import RainbowDQN +from fast_rl.core.data_block import MDPDataBunch, partial, ResolutionWrapper +from fast_rl.core.metrics import * + + +def test_rainbow_dqn(): + data=MDPDataBunch.from_env('CartPole-v0', render='rgb_array', bs=4, add_valid=False, keep_env_open=False, + res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) + model=RainbowDQN((4,),2) + metrics=[RewardMetric, RollingRewardMetric,EpsilonMetric] + learner=RainbowDQNLearner(data=data,model=model,trainers=BaseRainbowDQNTrainer,callback_fns=metrics,loss_func=lambda x,y:x) + learner.fit(3,wd=0,lr=0.0001) + + +@pytest.mark.usefixtures('skip_performance_check') +def test_rainbow_dqn_perf(): + data=MDPDataBunch.from_env('CartPole-v0', render='human', bs=32, add_valid=False, keep_env_open=False, + res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) + model=RainbowDQN((4,),2) + metrics=[RewardMetric, RollingRewardMetric,EpsilonMetric] + learner=RainbowDQNLearner(data=data,model=model,trainers=BaseRainbowDQNTrainer,callback_fns=metrics,use_per=False,loss_func=lambda x,y:x) + learner.fit(1600,wd=0,lr=0.0001) From 2c09b4480ef79ef96c22c8f2566cd2faef05ba58 Mon Sep 17 00:00:00 2001 From: josiah Date: Thu, 23 Apr 2020 07:37:40 -0400 Subject: [PATCH 27/29] Updated: - roadmap --- README.md | 44 ++++++++--- ROADMAP.md | 46 ++++++++--- fast_rl/agents/reinforce.py | 123 ----------------------------- fast_rl/agents/reinforce_models.py | 54 ------------- 4 files changed, 65 insertions(+), 202 deletions(-) diff --git a/README.md b/README.md index 1c7e26b..a0e30cf 100644 --- a/README.md +++ b/README.md @@ -121,42 +121,62 @@ OpenAI environments. - [ ] Add A2C - [ ] Add A3C - [ ] Add SAC -- [ ] 1.2.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* +- [ ] 2.0.0 Mass refactor / performance update + - [ ] Environments needs to be faster. Beat openai baseline 350 frames per second + - Comparing against https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On performance + - [ ] fastrl needs to handle ram better + - [ ] Use Pong as "expensive computation" benchmark for all compatible models (discrete). + - [ ] 2 Runs image space + - [ ] Use Cartpole as "cheap computation" benchmark for all compatible models (discrete). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Mountain car as "far distance goal" benchmark all compatible models (discrete) + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Ant as "expensive computation" benchmark for all compatible models (continuous). + - [ ] 2 Runs image space + - [ ] Use Pendulum as "cheap computation" benchmark for all compatible models (continuous). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Mountain car continuous as "cheap computation" "far distance goal" benchmark all compatible models (continuous). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use yield instead of return for the MDPDataset object + - [ ] Unify common code pieces shared in all models + - [ ] Transition entire project to [nbdev](https://github.com/fastai/nbdev) + - Make documentation easier / more expansive. Current method is tedious. +- [ ] 2.1.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* - [ ] Add SMDP - [ ] Add Goal oriented MDPs. Will Require a new "Step" - [ ] Add FeUdal Network - [ ] Add storage based DataBunch memory management. This can prevent RAM from being used up by episode image frames that may or may not serve any use to the agent, but only for logging. -- [ ] 1.3.0 +- [ ] 2.2.0 - [ ] Add HAC - [ ] Add MAXQ - [ ] Add HIRO -- [ ] 1.4.0 +- [ ] 2.3.0 - [ ] Add h-DQN - [ ] Add Modulated Policy Hierarchies - [ ] Add Meta Learning Shared Hierarchies -- [ ] 1.5.0 +- [ ] 2.4.0 - [ ] Add STRategic Attentive Writer (STRAW) - [ ] Add H-DRLN - [ ] Add Abstract Markov Decision Process (AMDP) - [ ] Add conda integration so that installation can be truly one step. -- [ ] 1.6.0 HRL Options models *Possibly will already be implemented in a previous model* +- [ ] 2.5.0 HRL Options models *Possibly will already be implemented in a previous model* - [ ] Options augmentation to DQN based models - [ ] Options augmentation to actor critic models - [ ] Options augmentation to async actor critic models -- [ ] 1.8.0 HRL Skills +- [ ] 2.6.0 HRL Skills - [ ] Skills augmentation to DQN based models - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models -- [ ] 1.9.0 Add PyBullet Fetch Environments +- [ ] 2.7.0 Add PyBullet Fetch Environments - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` - [ ] Add HER -- [ ] 2.0.0 Breaking refactor of all methods +- [ ] 3.0.0 Breaking refactor of all methods - [ ] Move to fastai 2.0 - - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second - - [ ] fastrl needs to handle ram better - - [ ] Use yield instead of return for the MDPDataset object - - [ ] Unify common code pieces shared in all models ## Contribution diff --git a/ROADMAP.md b/ROADMAP.md index 611e1a3..a12ec1e 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -8,7 +8,7 @@ this point, all models should have guaranteed environments they should succeed i - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - [X] Add Distributional DQN - - [ ] **Working on** Add RAINBOW DQN + - [X] Add RAINBOW DQN - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO @@ -16,39 +16,59 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Add A2C - [ ] Add A3C - [ ] Add SAC -- [ ] 1.2.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* +- [ ] 2.0.0 Mass refactor / performance update + - [ ] Environments needs to be faster. Beat openai baseline 350 frames per second + - Comparing against https://github.com/PacktPublishing/Deep-Reinforcement-Learning-Hands-On performance + - [ ] fastrl needs to handle ram better + - [ ] Use Pong as "expensive computation" benchmark for all compatible models (discrete). + - [ ] 2 Runs image space + - [ ] Use Cartpole as "cheap computation" benchmark for all compatible models (discrete). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Mountain car as "far distance goal" benchmark all compatible models (discrete) + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Ant as "expensive computation" benchmark for all compatible models (continuous). + - [ ] 2 Runs image space + - [ ] Use Pendulum as "cheap computation" benchmark for all compatible models (continuous). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use Mountain car continuous as "cheap computation" "far distance goal" benchmark all compatible models (continuous). + - [ ] 5 Runs state space + - [ ] 2 Runs image space + - [ ] Use yield instead of return for the MDPDataset object + - [ ] Unify common code pieces shared in all models + - [ ] Transition entire project to [nbdev](https://github.com/fastai/nbdev) + - Make documentation easier / more expansive. Current method is tedious. +- [ ] 2.1.0 HRL models *Possibly might change version to 2.0 depending on SMDP issues* - [ ] Add SMDP - [ ] Add Goal oriented MDPs. Will Require a new "Step" - [ ] Add FeUdal Network - [ ] Add storage based DataBunch memory management. This can prevent RAM from being used up by episode image frames that may or may not serve any use to the agent, but only for logging. -- [ ] 1.3.0 +- [ ] 2.2.0 - [ ] Add HAC - [ ] Add MAXQ - [ ] Add HIRO -- [ ] 1.4.0 +- [ ] 2.3.0 - [ ] Add h-DQN - [ ] Add Modulated Policy Hierarchies - [ ] Add Meta Learning Shared Hierarchies -- [ ] 1.5.0 +- [ ] 2.4.0 - [ ] Add STRategic Attentive Writer (STRAW) - [ ] Add H-DRLN - [ ] Add Abstract Markov Decision Process (AMDP) - [ ] Add conda integration so that installation can be truly one step. -- [ ] 1.6.0 HRL Options models *Possibly will already be implemented in a previous model* +- [ ] 2.5.0 HRL Options models *Possibly will already be implemented in a previous model* - [ ] Options augmentation to DQN based models - [ ] Options augmentation to actor critic models - [ ] Options augmentation to async actor critic models -- [ ] 1.8.0 HRL Skills +- [ ] 2.6.0 HRL Skills - [ ] Skills augmentation to DQN based models - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models -- [ ] 1.9.0 Add PyBullet Fetch Environments +- [ ] 2.7.0 Add PyBullet Fetch Environments - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` - [ ] Add HER -- [ ] 2.0.0 Breaking refactor of all methods +- [ ] 3.0.0 Breaking refactor of all methods - [ ] Move to fastai 2.0 - - [ ] Environment needs to be faster. Beat openai baseline 350 frames per second - - [ ] fastrl needs to handle ram better - - [ ] Use yield instead of return for the MDPDataset object - - [ ] Unify common code pieces shared in all models \ No newline at end of file diff --git a/fast_rl/agents/reinforce.py b/fast_rl/agents/reinforce.py index a76569d..e69de29 100644 --- a/fast_rl/agents/reinforce.py +++ b/fast_rl/agents/reinforce.py @@ -1,123 +0,0 @@ -from typing import * -from fastai.basic_train import LearnerCallback, Module, torch, ifnone, Tensor, listify, OptimWrapper - -import numpy as np -from fastai.tabular import TabularModel -from torch.distributions import Categorical -from torch.nn import Sequential - -from fast_rl.core.agent_core import ExplorationStrategy -from fast_rl.core.basic_train import AgentLearner -from fast_rl.core.data_block import MDPStep -from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper - - -class GaussianBasedExploration(ExplorationStrategy): - r""" Exploration via gaussian distribution of action outputs. - - This is per the usefulness noted in [1] pg 15. - - References: - [1] .. (Williams, 1992) [REINFORCE] Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning - """ - def perturb(self, action, action_space) -> np.ndarray: - m=Categorical(action) - a=m.sample() - return a - - -class LogBasedExploration(ExplorationStrategy): - def __init__(self): - super().__init__() - self.log_prob_a=0 - - r""" Exploration via log based probability distribution of action outputs. """ - def perturb(self, action, action_space) -> np.ndarray: - m=Categorical(action) - a=m.sample() - self.log_prob_a=m.log_prob(a) - return a - - -class REINFORCEStepWiseTrainer(LearnerCallback): - def __init__(self, learn): - super().__init__(learn) - self._order=1 - - def on_backward_begin(self, **kwargs:Any): return {'skip_bwd': False} - - def on_loss_begin(self, last_output,**kwargs): - r""" Loss will require the reward also. """ - return {'last_output':{'last_output':last_output, - 'reward':self.learn.data.x.items[-1].reward.float().to(device=self.learn.data.device), - 'log_prob':self.learn.exploration_strategy.log_prob_a}} - - -def discount_reward(r:List,discount): - discounts=discount**torch.arange(len(r)) - if discounts.shape[0]==1: discounts=discounts.unsqueeze(0) - discount_r=torch.cat(r).view(-1).dot(discounts.squeeze(0).float()) - if len(discount_r.shape)==0: discount_r=discount_r.unsqueeze(0).unsqueeze(0) - elif len(discount_r.shape)==1: discount_r=discount_r.unsqueeze(0) - return discount_r - -class REINFORCEEpisodicTrainer(LearnerCallback): - def __init__(self, learn): - super().__init__(learn) - self._order=1 - self.reward_buffer=[] - self.log_prob_buffer=[] - - def on_backward_begin(self, **kwargs: Any): - return {'skip_bwd': not bool(self.learn.data.x.items[-1].done)} - - def on_loss_begin(self, last_output,**kwargs): - r""" Loss will require the reward also. """ - self.reward_buffer.append(self.learn.data.x.items[-1].reward.float()) - self.log_prob_buffer.append(self.learn.exploration_strategy.log_prob_a) - return {'last_output':{'last_output':last_output, - 'reward':discount_reward(self.reward_buffer,self.learn.discount).to(device=self.learn.data.device), - 'log_prob':self.log_prob_buffer}} - - def on_epoch_end(self, **kwargs:Any) ->None: - self.reward_buffer=[] - self.log_prob_buffer=[] - - -def log_wise_loss(out, *args): - if len(out['log_prob'])<2: - return (-1*torch.cat(out['log_prob'])*out['reward']).squeeze(0).squeeze(0) - else: - return (-1*torch.cat(out['log_prob'],-1)*out['reward'].squeeze(0)).sum() - - -class REINFORCELearner(AgentLearner): - def __init__(self, data,model,trainers=None, lr=0.005,exploration_strategy=None,discount=None,**kwargs): - self.discount=ifnone(discount,0.99) - trainers=ifnone(trainers,REINFORCEStepWiseTrainer) - super().__init__(data=data, model=model,**kwargs) - self.opt=OptimWrapper.create(self.opt_func, lr=lr,layer_groups=[self.model.action_model]) - self.loss_func=log_wise_loss - self.exploration_strategy=ifnone(exploration_strategy,LogBasedExploration()) - self.trainers=listify(trainers) - for t in self.trainers: self.callbacks.append(t(self)) - - def predict(self, element, **kwargs): - training=self.model.training - if element.shape[0]==1: self.model.eval() - pred=self.model(element) - if training: self.model.train() - return self.exploration_strategy.perturb(pred, self.data.action.action_space) - - -def lazy_conv_out(m:Module,w,h,nc,switched)->int: - r""" A Lazier way to determining the conv block output. """ - is_training=m.training - m.eval() - ni=int(m(torch.zeros((1, w, h, nc) if switched else (1, nc, w, h))).view(-1, ).shape[0]) - if is_training: m.train(True) - return ni - - - - diff --git a/fast_rl/agents/reinforce_models.py b/fast_rl/agents/reinforce_models.py index 08a7bd4..e69de29 100644 --- a/fast_rl/agents/reinforce_models.py +++ b/fast_rl/agents/reinforce_models.py @@ -1,54 +0,0 @@ -from typing import * - -from fastai.basic_train import Module, ifnone, Tensor -from fastai.tabular import TabularModel -from torch.nn import Sequential - -from fast_rl.agents.reinforce import lazy_conv_out -from fast_rl.core.layers import conv_bn_lrelu, ChannelTranspose, Flatten, FakeBatchNorm, TabularEmbedWrapper - - -class REINFORCEModel(Module): - def __init__(self, ni: int, na: int, layers: Optional[List[int]] = None, conv_layers: Optional[List[int]] = None, - stride: Optional[List[int]] = None, padding: Optional[List[int]] = None, use_bn=False, - nc: Optional[int] = None, model_base_line=0, - w: Optional[int] = None, h: Optional[int] = None, embed_szs: Optional[List[int]] = None): - super().__init__() - self.model_base_line=model_base_line - self.switched=False - self.action_model=Sequential() - if self.setup_convolutional_layers(ni, nc, conv_layers, stride, padding, use_bn): - ni=lazy_conv_out(self.action_model, w, h, nc, self.switched) - self.setup_linear_layers(ni, ifnone(embed_szs, []), ifnone(layers, [32, 32]), na, use_bn) - - def set_opt(self, opt): - None - - def fix_switched_channels(self, current_channels, expected_channels, layers: list): - if current_channels==expected_channels: return layers - self.switched=True - return [ChannelTranspose()]+layers - - def setup_convolutional_layers(self, ni, nc, cv_l, stride, padding, use_bn) -> bool: - if cv_l is None or len(cv_l)==0: return False - # gen a list of conv blocks based on the input size and the list of filter sizes - conv_blocks=[conv_bn_lrelu(_ni, nf, s, p, bn=use_bn) for _ni, nf, s, p in - zip([ni]+cv_l[:-1], cv_l[1:], stride, padding)] - fixed_conv_blocks=self.fix_switched_channels(ni, nc, conv_blocks) - self.action_model.add_module('conv_block', Sequential(fixed_conv_blocks+[Flatten()])) - return True - - def setup_linear_layers(self, ni, emb_szs, layers, ao, use_bn): - tabular_model=TabularModel(emb_szs=emb_szs, n_cont=ni if not emb_szs else 0, layers=layers, out_sz=ao, - use_bn=use_bn) - if not emb_szs: tabular_model.embeds=None - if not use_bn: tabular_model.bn_cont=FakeBatchNorm() - self.action_model.add_module('lin_block', TabularEmbedWrapper(tabular_model)) - - def forward(self, xi: Tensor): - training=self.training - if xi.shape[0]==1: self.eval() - pred=self.action_model(xi) - if training: self.train() - pred[pred<0]=self.model_base_line+0.0001 # TODO sometimes this fails due to a de-synchronization error - return pred \ No newline at end of file From 2b624553126bb214a0d9cc511164386c2df6fcf1 Mon Sep 17 00:00:00 2001 From: josiah Date: Thu, 23 Apr 2020 11:56:41 -0400 Subject: [PATCH 28/29] Added: - REINFORCE model for Cartpole --- README.md | 2 +- ROADMAP.md | 4 +- fast_rl/agents/reinforce.py | 171 +++++++++++++++++++++++++++++ fast_rl/agents/reinforce_models.py | 18 +++ tests/test_reinforce.py | 26 +++++ 5 files changed, 218 insertions(+), 3 deletions(-) create mode 100644 tests/test_reinforce.py diff --git a/README.md b/README.md index a0e30cf..7527bf6 100644 --- a/README.md +++ b/README.md @@ -173,7 +173,7 @@ OpenAI environments. - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models - [ ] 2.7.0 Add PyBullet Fetch Environments - - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` + - [ ] Envs need to subclass OpenAI `gym.GoalEnv` - [ ] Add HER - [ ] 3.0.0 Breaking refactor of all methods - [ ] Move to fastai 2.0 diff --git a/ROADMAP.md b/ROADMAP.md index a12ec1e..67995cc 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -8,7 +8,7 @@ this point, all models should have guaranteed environments they should succeed i - [X] NStep Experience replay - [X] Gaussian and Factored Gaussian Noise exploration replacement - [X] Add Distributional DQN - - [X] Add RAINBOW DQN + - [X] Add RAINBOW DQN (Note warnings, will require refactor / re-testing) - [ ] **Working on** Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO @@ -68,7 +68,7 @@ this point, all models should have guaranteed environments they should succeed i - [ ] Skills augmentation to actor critic models - [ ] Skills augmentation to async actor critic models - [ ] 2.7.0 Add PyBullet Fetch Environments - - [ ] Envs need to subclaNot part of this repo, however the ess the OpenAI `gym.GoalEnv` + - [ ] Envs need to subclass OpenAI `gym.GoalEnv` - [ ] Add HER - [ ] 3.0.0 Breaking refactor of all methods - [ ] Move to fastai 2.0 diff --git a/fast_rl/agents/reinforce.py b/fast_rl/agents/reinforce.py index e69de29..cc2c5cc 100644 --- a/fast_rl/agents/reinforce.py +++ b/fast_rl/agents/reinforce.py @@ -0,0 +1,171 @@ +import collections +from copy import deepcopy +from functools import partial +from warnings import warn + +from fastai.basic_train import LearnerCallback +from fastai.imports import torch, Any + +from fast_rl.agents.dist_dqn_models import TargetNet +from fast_rl.agents.dqn_models import distr_projection +from fast_rl.core.agent_core import ExperienceReplay, NStepExperienceReplay, NStepPriorityExperienceReplay, \ + ExplorationStrategy +from fast_rl.core.basic_train import AgentLearner, listify, List +from fast_rl.core.data_block import MDPDataBunch, MDPStep +from fastai.imports import torch + +import gym +import numpy as np +import argparse + +import torch +import torch.nn as nn +import torch.nn.functional as F +import torch.optim as optim + +from itertools import groupby + + +class PolicyExploration(ExplorationStrategy): + def __init__(self,apply_softmax=False): + super().__init__() + self.apply_softmax=apply_softmax + self.epsilon=0 + + def perturb(self, action, action_space) -> np.ndarray: + if self.apply_softmax: + action=F.softmax(action.double(), dim=1) # cast to double so the precision is greater (otherwise sum!= 1 err) + action/=action.sum() + action_list = [np.random.choice(len(prob), p=prob) for prob in action] + return np.array(action_list) + +def calc_qvals(rewards,gamma): + res = [] + sum_r = 0.0 + for r in reversed(rewards): + sum_r *= gamma + sum_r += r + res.append(sum_r) + res = list(reversed(res)) + mean_q = np.mean(res) + return [q - mean_q for q in res] + +def calc_loss(states,actions,logits,q_vals): + log_prob_v=F.log_softmax(logits, dim=1) + log_prob_actions_v=q_vals*log_prob_v[range(len(states)), actions] + loss_v=-log_prob_actions_v.mean() + return loss_v + +class BaseReinforceTrainer(LearnerCallback): + def __init__(self, learn: 'ReinforceLearner', max_episodes=None): + r"""Handles basic DQN end of step model optimization.""" + super().__init__(learn) + + self.n_skipped = 0 + self._persist = max_episodes is not None + self.max_episodes = max_episodes + self.episode = -1 + self.iteration = 0 + # For the callback handler + self._order = 0 + self.previous_item = None + self.loss=None + + @property + def learn(self)->'ReinforceLearner': + return self._learn() + + def on_train_begin(self, n_epochs, **kwargs: Any): + self.max_episodes = n_epochs if not self._persist else self.max_episodes + + def on_epoch_begin(self, epoch, **kwargs: Any): + pass + + def on_backward_begin(self, **kwargs: Any): + return {'skip_bwd':self.learn.current_n_episodes_to_train=self.learn.n_episodes_to_train: + return {'skip_step': False} + return {'skip_step':True} + def on_step_end(self, **kwargs: Any): + if self.learn.current_n_episodes_to_train>=self.learn.n_episodes_to_train: + self.learn.current_n_episodes_to_train=0 + return {'skip_zero': False} + return {'skip_zero': True} + + def on_batch_begin(self, **kwargs:Any) ->None: + if self.learn.model.training: + if self.learn.data.x.items[-1].done: self.learn.current_n_episodes_to_train+=1 + if not self.learn.warming_up and self.learn.loss_func is None: self.learn.init_loss_func() + + def on_loss_begin(self, **kwargs: Any): + r"""Performs tree updates, exploration updates, and model optimization.""" + if self.learn.model.training: + # if self.learn.data.x.items[-1].done: self.learn.current_n_episodes_to_train+=1 + self.learn.memory.update(item=self.learn.data.x.items[-1]) + if len(self.learn.data.x.items)>10:self.learn.data.x.items=np.delete(self.learn.data.x.items,0) + self.iteration+=1 + self.learn.exploration_method.update(self.episode, max_episodes=self.max_episodes, explore=self.learn.model.training) + + if self.learn.current_n_episodes_to_train>=self.learn.n_episodes_to_train and not self.learn.warming_up: + samples=list(self.memory.memory) + assert int(sum([s.done for s in samples]))==self.learn.current_n_episodes_to_train + + _episode_counter=[0] + q_vals=[] + def paint_episodes(x,counter): + if not bool(x.done): return counter[0] + else: + counter[0]+=1 + return counter[0] + for g_n,o in groupby([s for s in samples],partial(paint_episodes,counter=_episode_counter)): + q_vals.extend(calc_qvals([float(s.reward) for s in o],self.learn.discount)) + + loss=calc_loss( + states=torch.cat([s.s for s in samples]), + actions=torch.cat([s.a for s in samples]), + logits=self.learn.model(torch.cat([s.s for s in samples])), + q_vals=torch.Tensor(q_vals).to(self.learn.data.device) + ) + self.learn.memory.memory.clear() + self.loss=loss.detach().cpu() + return {'last_output': loss} + return {'last_output':self.loss} + + def on_batch_end(self, **kwargs:Any) ->None: + if self.iteration % 300 == 0: + self.learn.target_net.sync() + + +class ReinforceLearner(AgentLearner): + def __init__(self, data: MDPDataBunch, model, trainers,loss_func=None,episodes_to_train=4,discount=0.99,opt=torch.optim.Adam,**learn_kwargs): + super().__init__(data=data, model=model, opt=opt,loss_func=loss_func, **learn_kwargs) + self._loss_func=loss_func + self.memory=ExperienceReplay(100000) + self.discount=discount + + self.target_net=TargetNet(self.model) + self.exploration_method=PolicyExploration(apply_softmax=True) + self.trainers=listify(trainers) + for t in self.trainers: self.callbacks.append(t(self)) + self.n_episodes_to_train=episodes_to_train + self.current_n_episodes_to_train=0 + self.stay_warmed_up_toggle=True + + def init(self, init):pass + # def init_loss_func(self):pass + def remove_loss_func(self): + self.loss_func=None + + @property + def warming_up(self): + if self.n_episodes_to_train<=self.current_n_episodes_to_train: + self.stay_warmed_up_toggle=False + return self.stay_warmed_up_toggle + + def predict(self, element, **kwargs): + q_v=self.model(element) + actions=self.exploration_method.perturb(q_v,self.data.action.action_space) + return actions + + diff --git a/fast_rl/agents/reinforce_models.py b/fast_rl/agents/reinforce_models.py index e69de29..b9cc141 100644 --- a/fast_rl/agents/reinforce_models.py +++ b/fast_rl/agents/reinforce_models.py @@ -0,0 +1,18 @@ +from torch import nn + + +class PGN(nn.Module): + def __init__(self, input_size, n_actions): + super(PGN, self).__init__() + + self.net = nn.Sequential( + nn.Linear(input_size[0], 128), + nn.ReLU(), + nn.Linear(128, n_actions) + ) + self.loss_func=None + + def set_opt(self, _): pass + + def forward(self, x): + return self.net(x) \ No newline at end of file diff --git a/tests/test_reinforce.py b/tests/test_reinforce.py new file mode 100644 index 0000000..26892ef --- /dev/null +++ b/tests/test_reinforce.py @@ -0,0 +1,26 @@ +import pytest + +from fast_rl.agents.reinforce import BaseReinforceTrainer, ReinforceLearner +from fast_rl.agents.reinforce_models import PGN +from fast_rl.core.data_block import MDPDataBunch, partial, ResolutionWrapper +from fast_rl.core.metrics import * + + +def test_reinforce(): + data=MDPDataBunch.from_env('CartPole-v0', render='rgb_array', bs=1, add_valid=False, keep_env_open=False, + res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) + model=PGN((4,),2) + metrics=[RewardMetric, RollingRewardMetric,EpsilonMetric] + learner=ReinforceLearner(data=data,model=model,trainers=BaseReinforceTrainer,episodes_to_train=4, + callback_fns=metrics,loss_func=lambda x,y:x) + learner.fit(3,wd=0,lr=0.0001) + + +@pytest.mark.usefixtures('skip_performance_check') +def test_reinforce_perf(): + data=MDPDataBunch.from_env('CartPole-v0', render='rgb_array', bs=1, add_valid=False, keep_env_open=False, + res_wrap=partial(ResolutionWrapper, w_step=4, h_step=4)) + model=PGN((4,),2) + metrics=[RewardMetric, RollingRewardMetric,EpsilonMetric] + learner=ReinforceLearner(data=data,model=model,trainers=BaseReinforceTrainer,episodes_to_train=4,callback_fns=metrics,loss_func=lambda x,y:x) + learner.fit(500,wd=0,lr=0.01) From fc6765cb645df518e2803dbba58c51830c913f45 Mon Sep 17 00:00:00 2001 From: josiah Date: Thu, 23 Apr 2020 11:58:57 -0400 Subject: [PATCH 29/29] Updated: - REINFORCE roadmap --- ROADMAP.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/ROADMAP.md b/ROADMAP.md index 67995cc..a983a9a 100644 --- a/ROADMAP.md +++ b/ROADMAP.md @@ -9,7 +9,7 @@ this point, all models should have guaranteed environments they should succeed i - [X] Gaussian and Factored Gaussian Noise exploration replacement - [X] Add Distributional DQN - [X] Add RAINBOW DQN (Note warnings, will require refactor / re-testing) - - [ ] **Working on** Add REINFORCE + - [X] Add REINFORCE - [ ] **Working on** Add PPO - [ ] **Working on** Add TRPO - [ ] Add D4PG