Update version to 0.25.0

Author: deliahu

build/build-image.sh

@@ -19,7 +19,7 @@ set -euo pipefail
 
 ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")"/.. >/dev/null && pwd)"
 
-CORTEX_VERSION=master
+CORTEX_VERSION=0.25.0
 
 image=$1
 dir="${ROOT}/images/${image/-slim}"

build/cli.sh

@@ -19,7 +19,7 @@ set -euo pipefail
 
 ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")"/.. >/dev/null && pwd)"
 
-CORTEX_VERSION=master
+CORTEX_VERSION=0.25.0
 
 arg1=${1:-""}
 upload="false"

build/push-image.sh

@@ -17,7 +17,7 @@
 
 set -euo pipefail
 
-CORTEX_VERSION=master
+CORTEX_VERSION=0.25.0
 
 image=$1
 

docs/clients/install.md

@@ -9,10 +9,10 @@ pip install cortex
 ```
 
 <!-- CORTEX_VERSION_README x2 -->
-To install or upgrade to a specific version (e.g. v0.24.1):
+To install or upgrade to a specific version (e.g. v0.25.0):
 
 ```bash
-pip install cortex==0.24.1
+pip install cortex==0.25.0
 ```
 
 To upgrade to the latest version:
@@ -25,8 +25,8 @@ pip install --upgrade cortex
 
 <!-- CORTEX_VERSION_README x2 -->
 ```bash
-# For example to download CLI version 0.24.1 (Note the "v"):
-$ bash -c "$(curl -sS https://raw.githubusercontent.com/cortexlabs/cortex/v0.24.1/get-cli.sh)"
+# For example to download CLI version 0.25.0 (Note the "v"):
+$ bash -c "$(curl -sS https://raw.githubusercontent.com/cortexlabs/cortex/v0.25.0/get-cli.sh)"
 ```
 
 By default, the Cortex CLI is installed at `/usr/local/bin/cortex`. To install the executable elsewhere, export the `CORTEX_INSTALL_PATH` environment variable to your desired location before running the command above.

docs/clients/python.md

@@ -114,7 +114,7 @@ Deploy an API.
 
 **Arguments**:
 
-- `api_spec` - A dictionary defining a single Cortex API. See https://docs.cortex.dev/v/master/ for schema.
+- `api_spec` - A dictionary defining a single Cortex API. See https://docs.cortex.dev/v/0.25/ for schema.
 - `predictor` - A Cortex Predictor class implementation. Not required when deploying a traffic splitter.
 - `requirements` - A list of PyPI dependencies that will be installed before the predictor class implementation is invoked.
 - `conda_packages` - A list of Conda dependencies that will be installed before the predictor class implementation is invoked.

docs/clusters/aws/install.md

@@ -81,17 +81,17 @@ The docker images used by the Cortex cluster can also be overridden, although th
 
 <!-- CORTEX_VERSION_BRANCH_STABLE -->
 ```yaml
-image_operator: quay.io/cortexlabs/operator:master
-image_manager: quay.io/cortexlabs/manager:master
-image_downloader: quay.io/cortexlabs/downloader:master
-image_request_monitor: quay.io/cortexlabs/request-monitor:master
-image_cluster_autoscaler: quay.io/cortexlabs/cluster-autoscaler:master
-image_metrics_server: quay.io/cortexlabs/metrics-server:master
-image_inferentia: quay.io/cortexlabs/inferentia:master
-image_neuron_rtd: quay.io/cortexlabs/neuron-rtd:master
-image_nvidia: quay.io/cortexlabs/nvidia:master
-image_fluentd: quay.io/cortexlabs/fluentd:master
-image_statsd: quay.io/cortexlabs/statsd:master
-image_istio_proxy: quay.io/cortexlabs/istio-proxy:master
-image_istio_pilot: quay.io/cortexlabs/istio-pilot:master
+image_operator: quay.io/cortexlabs/operator:0.25.0
+image_manager: quay.io/cortexlabs/manager:0.25.0
+image_downloader: quay.io/cortexlabs/downloader:0.25.0
+image_request_monitor: quay.io/cortexlabs/request-monitor:0.25.0
+image_cluster_autoscaler: quay.io/cortexlabs/cluster-autoscaler:0.25.0
+image_metrics_server: quay.io/cortexlabs/metrics-server:0.25.0
+image_inferentia: quay.io/cortexlabs/inferentia:0.25.0
+image_neuron_rtd: quay.io/cortexlabs/neuron-rtd:0.25.0
+image_nvidia: quay.io/cortexlabs/nvidia:0.25.0
+image_fluentd: quay.io/cortexlabs/fluentd:0.25.0
+image_statsd: quay.io/cortexlabs/statsd:0.25.0
+image_istio_proxy: quay.io/cortexlabs/istio-proxy:0.25.0
+image_istio_pilot: quay.io/cortexlabs/istio-pilot:0.25.0
 ```

docs/clusters/aws/update.md

@@ -8,8 +8,6 @@ cortex cluster configure  # or: cortex cluster configure --config cluster.yaml
 
 ## Upgrade to a newer version of Cortex
 
-<!-- CORTEX_VERSION_MINOR -->
-
 ```bash
 # spin down your cluster
 cortex cluster down

docs/clusters/gcp/install.md

@@ -45,11 +45,11 @@ The docker images used by the Cortex cluster can also be overridden, although th
 
 <!-- CORTEX_VERSION_BRANCH_STABLE -->
 ```yaml
-image_operator: quay.io/cortexlabs/operator:master
-image_manager: quay.io/cortexlabs/manager:master
-image_downloader: quay.io/cortexlabs/downloader:master
-image_statsd: quay.io/cortexlabs/statsd:master
-image_istio_proxy: quay.io/cortexlabs/istio-proxy:master
-image_istio_pilot: quay.io/cortexlabs/istio-pilot:master
-image_pause: quay.io/cortexlabs/pause:master
+image_operator: quay.io/cortexlabs/operator:0.25.0
+image_manager: quay.io/cortexlabs/manager:0.25.0
+image_downloader: quay.io/cortexlabs/downloader:0.25.0
+image_statsd: quay.io/cortexlabs/statsd:0.25.0
+image_istio_proxy: quay.io/cortexlabs/istio-proxy:0.25.0
+image_istio_pilot: quay.io/cortexlabs/istio-pilot:0.25.0
+image_pause: quay.io/cortexlabs/pause:0.25.0
 ```

docs/workloads/batch/configuration.md

@@ -11,7 +11,7 @@
     path: <string>  # path to a python file with a PythonPredictor class definition, relative to the Cortex root (required)
     config: <string: value>  # arbitrary dictionary passed to the constructor of the Predictor (can be overridden by config passed in job submission) (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
-    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/python-predictor-cpu:master or quay.io/cortexlabs/python-predictor-gpu:master based on compute)
+    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/python-predictor-cpu:0.25.0 or quay.io/cortexlabs/python-predictor-gpu:0.25.0 based on compute)
     env: <string: string>  # dictionary of environment variables
   networking:
     endpoint: <string>  # the endpoint for the API (default: <api_name>)
@@ -45,8 +45,8 @@
       batch_interval: <duration>  # the maximum amount of time to spend waiting for additional requests before running inference on the batch of requests
     config: <string: value>  # arbitrary dictionary passed to the constructor of the Predictor (can be overridden by config passed in job submission) (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
-    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/tensorflow-predictor:master)
-    tensorflow_serving_image: <string> # docker image to use for the TensorFlow Serving container (default: quay.io/cortexlabs/tensorflow-serving-gpu:master or quay.io/cortexlabs/tensorflow-serving-cpu:master based on compute)
+    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/tensorflow-predictor:0.25.0)
+    tensorflow_serving_image: <string> # docker image to use for the TensorFlow Serving container (default: quay.io/cortexlabs/tensorflow-serving-gpu:0.25.0 or quay.io/cortexlabs/tensorflow-serving-cpu:0.25.0 based on compute)
     env: <string: string>  # dictionary of environment variables
   networking:
     endpoint: <string>  # the endpoint for the API (default: <api_name>)
@@ -75,7 +75,7 @@
         ...
     config: <string: value>  # arbitrary dictionary passed to the constructor of the Predictor (can be overridden by config passed in job submission) (optional)
     python_path: <string>  # path to the root of your Python folder that will be appended to PYTHONPATH (default: folder containing cortex.yaml)
-    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/onnx-predictor-gpu:master or quay.io/cortexlabs/onnx-predictor-cpu:master based on compute)
+    image: <string> # docker image to use for the Predictor (default: quay.io/cortexlabs/onnx-predictor-gpu:0.25.0 or quay.io/cortexlabs/onnx-predictor-cpu:0.25.0 based on compute)
     env: <string: string>  # dictionary of environment variables
   networking:
     endpoint: <string>  # the endpoint for the API (default: <api_name>)

docs/workloads/batch/predictors.md

@@ -161,7 +161,7 @@ torchvision==0.6.1
 ```
 
 <!-- CORTEX_VERSION_MINOR x3 -->
-The pre-installed system packages are listed in [images/python-predictor-cpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/python-predictor-cpu/Dockerfile) (for CPU), [images/python-predictor-gpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/python-predictor-gpu/Dockerfile) (for GPU), or [images/python-predictor-inf/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/python-predictor-inf/Dockerfile) (for Inferentia).
+The pre-installed system packages are listed in [images/python-predictor-cpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/python-predictor-cpu/Dockerfile) (for CPU), [images/python-predictor-gpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/python-predictor-gpu/Dockerfile) (for GPU), or [images/python-predictor-inf/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/python-predictor-inf/Dockerfile) (for Inferentia).
 
 ## TensorFlow Predictor
 
@@ -216,7 +216,7 @@ class TensorFlowPredictor:
 ```
 
 <!-- CORTEX_VERSION_MINOR -->
-Cortex provides a `tensorflow_client` to your Predictor's constructor. `tensorflow_client` is an instance of [TensorFlowClient](https://github.com/cortexlabs/cortex/tree/master/pkg/cortex/serve/cortex_internal/lib/client/tensorflow.py) that manages a connection to a TensorFlow Serving container to make predictions using your model. It should be saved as an instance variable in your Predictor, and your `predict()` function should call `tensorflow_client.predict()` to make an inference with your exported TensorFlow model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your `predict()` function as well.
+Cortex provides a `tensorflow_client` to your Predictor's constructor. `tensorflow_client` is an instance of [TensorFlowClient](https://github.com/cortexlabs/cortex/tree/0.25/pkg/cortex/serve/cortex_internal/lib/client/tensorflow.py) that manages a connection to a TensorFlow Serving container to make predictions using your model. It should be saved as an instance variable in your Predictor, and your `predict()` function should call `tensorflow_client.predict()` to make an inference with your exported TensorFlow model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your `predict()` function as well.
 
 When multiple models are defined using the Predictor's `models` field, the `tensorflow_client.predict()` method expects a second argument `model_name` which must hold the name of the model that you want to use for inference (for example: `self.client.predict(payload, "text-generator")`).
 
@@ -242,7 +242,7 @@ tensorflow==2.3.0
 ```
 
 <!-- CORTEX_VERSION_MINOR -->
-The pre-installed system packages are listed in [images/tensorflow-predictor/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/tensorflow-predictor/Dockerfile).
+The pre-installed system packages are listed in [images/tensorflow-predictor/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/tensorflow-predictor/Dockerfile).
 
 ## ONNX Predictor
 
@@ -297,7 +297,7 @@ class ONNXPredictor:
 ```
 
 <!-- CORTEX_VERSION_MINOR -->
-Cortex provides an `onnx_client` to your Predictor's constructor. `onnx_client` is an instance of [ONNXClient](https://github.com/cortexlabs/cortex/tree/master/pkg/cortex/serve/cortex_internal/lib/client/onnx.py) that manages an ONNX Runtime session to make predictions using your model. It should be saved as an instance variable in your Predictor, and your `predict()` function should call `onnx_client.predict()` to make an inference with your exported ONNX model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your `predict()` function as well.
+Cortex provides an `onnx_client` to your Predictor's constructor. `onnx_client` is an instance of [ONNXClient](https://github.com/cortexlabs/cortex/tree/0.25/pkg/cortex/serve/cortex_internal/lib/client/onnx.py) that manages an ONNX Runtime session to make predictions using your model. It should be saved as an instance variable in your Predictor, and your `predict()` function should call `onnx_client.predict()` to make an inference with your exported ONNX model. Preprocessing of the JSON payload and postprocessing of predictions can be implemented in your `predict()` function as well.
 
 When multiple models are defined using the Predictor's `models` field, the `onnx_client.predict()` method expects a second argument `model_name` which must hold the name of the model that you want to use for inference (for example: `self.client.predict(model_input, "text-generator")`).
 
@@ -320,4 +320,4 @@ requests==2.24.0
 ```
 
 <!-- CORTEX_VERSION_MINOR x2 -->
-The pre-installed system packages are listed in [images/onnx-predictor-cpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/onnx-predictor-cpu/Dockerfile) (for CPU) or [images/onnx-predictor-gpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/master/images/onnx-predictor-gpu/Dockerfile) (for GPU).
+The pre-installed system packages are listed in [images/onnx-predictor-cpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/onnx-predictor-cpu/Dockerfile) (for CPU) or [images/onnx-predictor-gpu/Dockerfile](https://github.com/cortexlabs/cortex/tree/0.25/images/onnx-predictor-gpu/Dockerfile) (for GPU).