Merge branch 'main' into 2015-improve-explanation-of-datalist-format

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

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",

3d_segmentation/spleen_segmentation_3d_visualization_basic.ipynb

@@ -484,7 +484,7 @@
     "# standard PyTorch program style: create UNet, DiceLoss and Adam optimizer\n",
     "device = torch.device(\"cuda:0\")\n",
     "\n",
-    "UNet_meatdata = {\n",
+    "UNet_metadata = {\n",
     "    \"spatial_dims\": 3,\n",
     "    \"in_channels\": 1,\n",
     "    \"out_channels\": 2,\n",
@@ -494,7 +494,7 @@
     "    \"norm\": Norm.BATCH,\n",
     "}\n",
     "\n",
-    "model = UNet(**UNet_meatdata).to(device)\n",
+    "model = UNet(**UNet_metadata).to(device)\n",
     "loss_function = DiceLoss(to_onehot_y=True, softmax=True)\n",
     "loss_type = \"DiceLoss\"\n",
     "optimizer = torch.optim.Adam(model.parameters(), 1e-4)\n",
@@ -539,7 +539,7 @@
     "# initialize a new Aim Run\n",
     "aim_run = aim.Run()\n",
     "# log model metadata\n",
-    "aim_run[\"UNet_meatdata\"] = UNet_meatdata\n",
+    "aim_run[\"UNet_metadata\"] = UNet_metadata\n",
     "# log optimizer metadata\n",
     "aim_run[\"Optimizer_metadata\"] = Optimizer_metadata\n",
     "\n",

README.md

@@ -41,6 +41,50 @@ Running:
 
 in a cell will verify this has worked and show you what kind of hardware you have access to.
 
+#### Google Colab Setup (CUDA 12.x, PyTorch 2.6, MONAI 1.5)
+
+In Google Colab, the default environment may cause version conflicts with MONAI.
+To ensure compatibility, install PyTorch and MONAI explicitly as follows:
+
+# Install PyTorch 2.6.0 with CUDA 12.4
+pip install --index-url https://download.pytorch.org/whl/cu124 \
+  torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0
+
+# Install MONAI and common dependencies
+pip install "monai[all]" nibabel pydicom ipywidgets==8.1.2
+
+
+### Known issues and fixes
+
+- Torchaudio mismatch
+  Colab may come with torchaudio 2.8.0, which is incompatible with torch 2.6.0.
+  Installing the versions above resolves this issue.
+
+- filelock conflicts with nni
+  Some preinstalled packages (such as pytensor with newer filelock) may conflict.
+  Use the following commands to fix:
+
+  pip uninstall -y pytensor
+  pip install -U filelock
+
+- Too many workers warning
+  Colab has limited CPU resources, and high num_workers settings may freeze execution.
+  It is recommended to use --num_workers=2 when running tutorials and adjust the `num_workers` parameters where it is used in notebooks (eg. for data loaders).
+
+
+### Quick smoke test
+
+After installation, verify the environment by running:
+
+git clone https://github.com/Project-MONAI/tutorials.git
+cd tutorials/3d_segmentation/torch
+python -u unet_training_array.py --max_epochs 2 --batch_size 1 --num_workers 2
+
+If the logs show decreasing training loss and a Dice score, the setup is correct.
+
+**Note:** In most cases, users can run MONAI tutorials directly in Colab notebooks without additional installation.
+The steps above are mainly for resolving dependency conflicts when installing extra packages.
+
 #### Data
 
 Some notebooks will require additional data.

generation/maisi/README.md

@@ -20,6 +20,10 @@ We are excited to announce the new MAISI Version `maisi3d-rflow`. Compared with
 - For the released model weights, `maisi3d-rflow` can generate images with better quality for head region and small output volumes than `maisi3d-ddpm`; they have comparable quality for other cases.
 - `maisi3d-rflow` added a diffusion model input `modality`, which gives it flexibility to extend to other modalities. Currently it is set as always equal to 1 since this version only supports CT generation. We predefined some modalities in [./configs/modality_mapping.json](./configs/modality_mapping.json).
 
+More details can be found in our 2025 report:
+
+[Zhao, C., Guo, P., Yang, D., Tang, Y., ... & Xu, D. (2025). MAISI-v2: Accelerated 3D High-Resolution Medical Image Synthesis with Rectified Flow and Region-specific Contrastive Loss](https://arxiv.org/pdf/2508.05772)
+
 **GUI demo:** Welcome to try our GUI demo at [https://build.nvidia.com/nvidia/maisi](https://build.nvidia.com/nvidia/maisi).
 The GUI is only a demo for toy examples. This Github repo is the full version.
 

generation/maisi/maisi_train_vae_tutorial.ipynb

@@ -692,7 +692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "id": "4c251a32-390f-46dd-a613-75b12a7884c1",
    "metadata": {
     "scrolled": true
@@ -850,7 +850,7 @@
     "            with torch.no_grad():\n",
     "                with autocast(\"cuda\", enabled=args.amp):\n",
     "                    images = batch[\"image\"]\n",
-    "                    reconstruction, _, _ = dynamic_infer(val_inferer, autoencoder, images)\n",
+    "                    reconstruction, z_mu, z_sigma = dynamic_infer(val_inferer, autoencoder, images)\n",
     "                    reconstruction = reconstruction.to(device)\n",
     "                    val_epoch_losses[\"recons_loss\"] += intensity_loss(reconstruction, images.to(device)).item()\n",
     "                    val_epoch_losses[\"kl_loss\"] += KL_loss(z_mu, z_sigma).item()\n",

requirements.txt

@@ -4,4 +4,5 @@ autopep8
 jupytext<=1.16.3
 autoflake
 ipywidgets
+ipykernel
 tensorboard>=2.4.0

runner.sh

@@ -131,6 +131,7 @@ skip_run_papermill=("${skip_run_papermill[@]}" .*unet_segmentation_3d_ignite_cle
 skip_run_papermill=("${skip_run_papermill[@]}" .*vista_2d_tutorial_monai.ipynb*)
 skip_run_papermill=("${skip_run_papermill[@]}" .*learn2reg_oasis_unpaired_brain_mr.ipynb*)
 skip_run_papermill=("${skip_run_papermill[@]}" .*finetune_vista3d_for_hugging_face_pipeline.ipynb*)
+skip_run_papermill=("${skip_run_papermill[@]}" .*TCIA_PROSTATEx_Prostate_MRI_Anatomy_Model.ipynb*)  # https://github.com/Project-MONAI/tutorials/issues/2029
 
 # output formatting
 separator=""
@@ -466,6 +467,15 @@ trap finish EXIT
 # After setup, don't want to exit immediately after error
 set +e
 
+# FIXME: https://github.com/Project-MONAI/MONAI/issues/4354
+protobuf_major_version=$(${PY_EXE} -m pip list | grep '^protobuf ' | tr -s ' ' | cut -d' ' -f2 | cut -d'.' -f1)
+if [ "$protobuf_major_version" -ge "4" ]
+then
+    export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
+else
+    unset PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION
+fi
+
 ########################################################################
 #                                                                      #
 #  loop over files                                                     #
@@ -559,15 +569,6 @@ for file in "${files[@]}"; do
 
         python -c 'import monai; monai.config.print_config()'
 
-        # FIXME: https://github.com/Project-MONAI/MONAI/issues/4354
-        protobuf_major_version=$(${PY_EXE} -m pip list | grep '^protobuf ' | tr -s ' ' | cut -d' ' -f2 | cut -d'.' -f1)
-        if [ "$protobuf_major_version" -ge "4" ]
-        then
-            export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
-        else
-            unset PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION
-        fi
-
         cmd=$(echo "papermill ${papermill_opt} --progress-bar --log-output -k ${kernelspec}")
         echo "$cmd"
         time out=$(echo "$notebook" | eval "$cmd")