Merge branch 'main' into add-infer-accelerate-tutorial

Author: ericspod

.github/workflows/test-modified.yml

@@ -9,39 +9,39 @@ on:
 
 concurrency:
   # automatically cancel the previously triggered workflows when there's a newer version
-  group: build-gpu-${{ github.event.pull_request.number || github.ref }}
+  group: build-${{ github.event.pull_request.number || github.ref }}
   cancel-in-progress: true
 
 jobs:
   build:
-    if: github.repository == 'Project-MONAI/tutorials'
-    container:
-      image: nvcr.io/nvidia/pytorch:24.02-py3
-      options: --gpus all --ipc host
-    runs-on: [self-hosted, linux, x64]
+    runs-on: ubuntu-latest
     steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python 3.10
+      uses: actions/setup-python@v3
+      with:
+        python-version: '3.10'
     - name: Install MONAI
       id: monai-install
       run: |
         which python
-        nvidia-smi
-        rm -rf ../../MONAI/MONAI
-        python -m pip install --upgrade pip wheel
-        pip uninstall -y monai
-        pip uninstall -y monai
-        pip uninstall -y monai-weekly
-        pip uninstall -y monai-weekly # make sure there's no existing installation
-        BUILD_MONAI=0 python -m pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI
+        python -m pip install -U pip wheel
+        python -m pip install torch torchvision torchaudio
+
         python -m pip install -r https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/requirements-dev.txt
-        python -m pip install -U torch torchvision torchaudio
-    - uses: actions/checkout@v3
+        python -m pip install -r requirements.txt
+
+        BUILD_MONAI=0 python -m pip install git+https://github.com/Project-MONAI/MONAI#egg=MONAI
+        python -m pip list
     - name: Notebook quick check
       shell: bash
       run: |
-        git config --global --add safe.directory /__w/tutorials/tutorials
-        git fetch origin main
-        python -m pip install -r requirements.txt; python -m pip list
         python -c "import monai; monai.config.print_debug_info()"
-        export CUDA_VISIBLE_DEVICES=0
-        git diff --name-only origin/main | while read line; do if [[ $line == *.ipynb ]]; then ./runner.sh -p " -and -wholename './${line}'"; fi; done;
-          # [[ $line == *.ipynb ]] && ./runner.sh --file "$line"
+        git fetch origin main
+        git diff --name-only origin/main | while read line
+        do
+          if [[ $line == *.ipynb ]]
+          then
+            ./runner.sh -p " -and -wholename './${line}'"
+          fi
+        done

.pre-commit-config.yaml

@@ -23,7 +23,7 @@ repos:
       - id: detect-private-key
 
   - repo: https://github.com/psf/black
-    rev: "24.10.0"
+    rev: "25.1.0"
     hooks:
       - id: black
       - id: black-jupyter

2d_classification/monai_101.ipynb

@@ -141,15 +141,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "/workspace/data\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "directory = os.environ.get(\"MONAI_DATA_DIRECTORY\")\n",
     "if directory is not None:\n",
@@ -250,11 +242,12 @@
    "outputs": [],
    "source": [
     "max_epochs = 5\n",
-    "model = densenet121(spatial_dims=2, in_channels=1, out_channels=6).to(\"cuda:0\")\n",
+    "device = torch.device(\"cuda:0\" if torch.cuda.device_count() > 0 else \"cpu\")\n",
+    "model = densenet121(spatial_dims=2, in_channels=1, out_channels=6).to(device)\n",
     "\n",
     "logging.basicConfig(stream=sys.stdout, level=logging.INFO)\n",
     "trainer = SupervisedTrainer(\n",
-    "    device=torch.device(\"cuda:0\"),\n",
+    "    device=device,\n",
     "    max_epochs=max_epochs,\n",
     "    train_data_loader=DataLoader(dataset, batch_size=512, shuffle=True, num_workers=4),\n",
     "    network=model,\n",
@@ -320,7 +313,7 @@
     "max_items_to_print = 10\n",
     "with eval_mode(model):\n",
     "    for item in DataLoader(testdata, batch_size=1, num_workers=0):\n",
-    "        prob = np.array(model(item[\"image\"].to(\"cuda:0\")).detach().to(\"cpu\"))[0]\n",
+    "        prob = np.array(model(item[\"image\"].to(device)).detach().to(\"cpu\"))[0]\n",
     "        pred = class_names[prob.argmax()]\n",
     "        gt = item[\"class_name\"][0]\n",
     "        print(f\"Class prediction is {pred}. Ground-truth: {gt}\")\n",