Merge pull request #299 from mit-han-lab/upgrade-qiskit1

Upgrade to qiskit-1.4

Author: zkysfls

.github/workflows/functional_tests.yaml

@@ -14,7 +14,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.8", "3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.9", "3.10", "3.11", "3.12"]
 
     steps:
     - uses: actions/checkout@v3

.gitignore

@@ -336,3 +336,15 @@ es_runs/
 .vscode-upload.json
 
 mnist_data/
+
+configs.yml
+debug_qiskit.txt
+fix_note.txt
+h2_new.txt
+max-acc-valid.pt
+model.pt
+.cursor/rules/*.mdc
+
+.cursorignore
+.cursor/
+.github/copilot-instructions.md

examples/QuantumNAS/quantumnas.ipynb

@@ -4056,7 +4056,8 @@
       "toc_visible": true
     },
     "kernelspec": {
-      "display_name": "Python 3",
+      "display_name": "torchquantum",
+      "language": "python",
       "name": "python3"
     },
     "language_info": {
@@ -4069,7 +4070,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.8.16"
+      "version": "3.9.20"
     },
     "widgets": {
       "application/vnd.jupyter.widget-state+json": {

examples/gradient_pruning/callbacks.py

@@ -37,7 +37,7 @@
 from torchpack.utils.logging import logger
 from torchpack.utils.typing import Trainer
 from torchpack import distributed as dist
-from torchquantum.super_utils import get_named_sample_arch
+from torchquantum.algorithm.quantumnas.super_utils import get_named_sample_arch
 from torchquantum.util import legalize_unitary
 
 

examples/regression/new_run_regression.py

@@ -46,13 +46,13 @@
 
 
 def gen_data(L, N):
-    omega_0 = np.zeros([2**L], dtype="complex_")
+    omega_0 = np.zeros([2**L], dtype=complex)
     omega_0[0] = 1 + 0j
 
-    omega_1 = np.zeros([2**L], dtype="complex_")
+    omega_1 = np.zeros([2**L], dtype=complex)
     omega_1[-1] = 1 + 0j
 
-    states = np.zeros([N, 2**L], dtype="complex_")
+    states = np.zeros([N, 2**L], dtype=complex)
 
     thetas = 2 * np.pi * np.random.rand(N)
     phis = 2 * np.pi * np.random.rand(N)

examples/regression/run_regression.py

@@ -40,13 +40,13 @@
 
 
 def gen_data(L, N):
-    omega_0 = np.zeros([2**L], dtype="complex_")
+    omega_0 = np.zeros([2**L], dtype=complex)
     omega_0[0] = 1 + 0j
 
-    omega_1 = np.zeros([2**L], dtype="complex_")
+    omega_1 = np.zeros([2**L], dtype=complex)
     omega_1[-1] = 1 + 0j
 
-    states = np.zeros([N, 2**L], dtype="complex_")
+    states = np.zeros([N, 2**L], dtype=complex)
 
     thetas = 2 * np.pi * np.random.rand(N)
     phis = 2 * np.pi * np.random.rand(N)

examples/save_load_example/save_load.py

@@ -119,7 +119,7 @@ def save_load2():
 
     torch.save(model, "model_whole.pt")
 
-    model2 = torch.load("model_whole.pt")
+    model2 = torch.load("model_whole.pt", weights_only=False)
     y2 = model2(x)
     print(y2)
     assert torch.equal(y, y2)

requirement_update.txt

@@ -0,0 +1,24 @@
+
+dill
+matplotlib
+nbsphinx
+numpy
+
+opt_einsum
+pathos
+pylatexenc
+pyscf
+qiskit
+recommonmark
+qiskit_ibm_runtime
+qiskit-aer
+
+scipy
+setuptools
+tensorflow
+torch
+torchdiffeq
+torchpack
+torchquantum
+torchvision
+tqdm

requirements.txt

@@ -8,10 +8,10 @@ opt_einsum
 pathos>=0.2.7
 pylatexenc>=2.10
 pyscf>=2.0.1
-qiskit>=0.39.0,<1.0.0
+qiskit==1.4.3
 recommonmark
-qiskit_ibm_runtime==0.20.0
-qiskit-aer==0.13.3
+qiskit_ibm_runtime
+qiskit-aer
 
 scipy>=1.5.2
 setuptools>=52.0.0
@@ -21,4 +21,4 @@ torchdiffeq>=0.2.3
 torchpack>=0.3.0
 torchquantum>=0.1
 torchvision>=0.9.0.dev20210130
-tqdm>=4.56.0
+tqdm>=4.56.0