3921 - test with torch 1.11

.github/workflows/integration.yml

@@ -37,7 +37,7 @@ jobs:
         which python
         python -m pip install --upgrade pip wheel
         python -m pip uninstall -y torch torchvision
-        python -m pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.11+cu111 torchvision==0.12+cu111 -f https://download.pytorch.org/whl/torch_stable.html
         python -m pip install -r requirements-dev.txt
     - name: Run integration tests
       run: |

.github/workflows/pythonapp-gpu.yml

@@ -25,6 +25,7 @@ jobs:
           - "PT19+CUDA114"
           - "PT110+CUDA116"
           - "PT110+CUDA102"
+          - "PT111+CUDA102"
         include:
           # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
           - environment: PT17+CUDA102
@@ -51,6 +52,9 @@ jobs:
           - environment: PT110+CUDA102
             pytorch: "torch==1.10.1 torchvision==0.11.2"
             base: "nvcr.io/nvidia/cuda:10.2-devel-ubuntu18.04"
+          - environment: PT111+CUDA102
+            pytorch: "torch==1.11.0 torchvision==0.12.0"
+            base: "nvcr.io/nvidia/cuda:10.2-devel-ubuntu18.04"
     container:
       image: ${{ matrix.base }}
       options: --gpus all
@@ -61,7 +65,8 @@ jobs:
       run: |
         if [ ${{ matrix.environment }} = "PT17+CUDA102" ] || \
           [ ${{ matrix.environment }} = "PT18+CUDA102" ] || \
-          [ ${{ matrix.environment }} = "PT110+CUDA102" ]
+          [ ${{ matrix.environment }} = "PT110+CUDA102" ] || \
+          [ ${{ matrix.environment }} = "PT111+CUDA102" ]
         then
         PYVER=3.7 PYSFX=3 DISTUTILS=python3-distutils && \
         apt-get update && apt-get install -y --no-install-recommends \

.github/workflows/pythonapp-min.yml

@@ -51,11 +51,11 @@ jobs:
     - if: runner.os == 'windows'
       name: Install torch cpu from pytorch.org (Windows only)
       run: |
-        python -m pip install torch==1.10.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.11.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
     - name: Install the dependencies
       run: |
         # min. requirements
-        python -m pip install torch==1.10.1
+        python -m pip install torch==1.11.0
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions
@@ -101,7 +101,7 @@ jobs:
     - name: Install the dependencies
       run: |
         # min. requirements
-        python -m pip install torch==1.10.1
+        python -m pip install torch==1.11.0
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions
@@ -119,7 +119,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        pytorch-version: [1.6.0, 1.7.1, 1.8.1, 1.9.1, latest]
+        pytorch-version: [1.6.0, 1.7.1, 1.8.1, 1.9.1, 1.10.1, latest]
     timeout-minutes: 40
     steps:
     - uses: actions/checkout@v2
@@ -156,6 +156,8 @@ jobs:
           python -m pip install torch==1.8.1
         elif [ ${{ matrix.pytorch-version }} == "1.9.1" ]; then
           python -m pip install torch==1.9.1
+        elif [ ${{ matrix.pytorch-version }} == "1.10.1" ]; then
+          python -m pip install torch==1.10.1
         fi
         python -m pip install -r requirements-min.txt
         python -m pip list

.github/workflows/pythonapp.yml

@@ -87,10 +87,10 @@ jobs:
     - if: runner.os == 'windows'
       name: Install torch cpu from pytorch.org (Windows only)
       run: |
-        python -m pip install torch==1.10.1+cpu torchvision==0.11.2+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.11.0+cpu torchvision==0.12.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
     - name: Install the dependencies
       run: |
-        python -m pip install torch==1.10.1 torchvision==0.11.2
+        python -m pip install torch==1.11.0 torchvision==0.12.0
         cat "requirements-dev.txt"
         python -m pip install -r requirements-dev.txt
         python -m pip list

.github/workflows/setupapp.yml

@@ -44,7 +44,7 @@ jobs:
         python -m pip install --upgrade pip wheel
         python -m pip uninstall -y torch torchvision
         rm -rf $(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")/ruamel*
-        python -m pip install torch==1.10.1 torchvision==0.11.2
+        python -m pip install torch==1.11.0+cu113 torchvision==0.12.0+cu113 -f https://download.pytorch.org/whl/torch_stable.html
         python -m pip install -r requirements-dev.txt
     - name: Run unit tests report coverage
       run: |
@@ -98,7 +98,7 @@ jobs:
     - name: Install the dependencies
       run: |
         python -m pip install --upgrade pip wheel
-        python -m pip install torch==1.10.1 torchvision==0.11.2
+        python -m pip install torch==1.11.0 torchvision==0.12.0
         python -m pip install -r requirements-dev.txt
     - name: Run quick tests CPU ubuntu
       run: |

monai/apps/pathology/transforms/spatial/array.py

@@ -203,7 +203,7 @@ def __call__(self, image: NdarrayOrTensor) -> NdarrayOrTensor:
             c, h, w = img_np.shape
             pad_h = (self.tile_size - h % self.tile_size) % self.tile_size
             pad_w = (self.tile_size - w % self.tile_size) % self.tile_size
-            img_np = np.pad(
+            img_np = np.pad(  # type: ignore
                 img_np,
                 [[0, 0], [pad_h // 2, pad_h - pad_h // 2], [pad_w // 2, pad_w - pad_w // 2]],
                 constant_values=self.background_val,
@@ -220,7 +220,7 @@ def __call__(self, image: NdarrayOrTensor) -> NdarrayOrTensor:
             strides=(x_stride * x_step, y_stride * y_step, c_stride, x_stride, y_stride),
             writeable=False,
         )
-        img_np = llw.reshape(-1, c_image, h_tile, w_tile)
+        img_np = llw.reshape(-1, c_image, h_tile, w_tile)  # type: ignore
 
         # if keeping all patches
         if self.tile_count is None:
@@ -251,7 +251,7 @@ def __call__(self, image: NdarrayOrTensor) -> NdarrayOrTensor:
                         img_np = img_np[self.random_idxs]
 
             elif len(img_np) < self.tile_count:
-                img_np = np.pad(
+                img_np = np.pad(  # type: ignore
                     img_np,
                     [[0, self.tile_count - len(img_np)], [0, 0], [0, 0], [0, 0]],
                     constant_values=self.background_val,

monai/transforms/intensity/array.py

@@ -1405,7 +1405,7 @@ def __call__(self, img: NdarrayOrTensor, randomize: bool = True) -> NdarrayOrTen
         img_min, img_max = img_np.min(), img_np.max()
         reference_control_points_scaled = self.reference_control_points * (img_max - img_min) + img_min
         floating_control_points_scaled = self.floating_control_points * (img_max - img_min) + img_min
-        img_np = np.asarray(
+        img_np = np.asarray(  # type: ignore
             np.interp(img_np, reference_control_points_scaled, floating_control_points_scaled), dtype=img_np.dtype
         )
         img, *_ = convert_to_dst_type(img_np, dst=img)

monai/visualize/utils.py

@@ -107,7 +107,7 @@ def matshow3d(
         vol = np.concatenate([pad(v) for v in vol], axis=0)
     else:  # ndarray
         while len(vol.shape) < 3:
-            vol = np.expand_dims(vol, 0)  # so that we display 2d as well
+            vol = np.expand_dims(vol, 0)  # type: ignore  # so that we display 2d as well
 
     if channel_dim is not None:  # move the expected dim to construct frames with `B` dim
         vol = np.moveaxis(vol, frame_dim, -4)  # type: ignore