[CI] fix timm related bug

.circleci/test.yml

@@ -64,6 +64,16 @@ jobs:
           command: |
             python -V
             python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
+      - when:
+          condition:
+            equal: [ "1.9.0", << parameters.torch >> ]
+          steps:
+            - run: docker exec mmaction pip install timm
+      - when:
+          condition:
+            equal: [ "1.6.0", << parameters.torch >> ]
+          steps:
+            - run: docker exec mmaction pip install timm==0.6.7
       - run:
           name: Install mmaction dependencies
           command: |
@@ -124,6 +134,16 @@ jobs:
             docker exec mmaction pip install git+https://github.com/open-mmlab/mmdetection/
             docker exec mmaction pip install git+https://github.com/open-mmlab/mmclassification/
             docker exec mmaction pip install -r requirements.txt
+      - when:
+          condition:
+            equal: [ "1.8.1", << parameters.torch >> ]
+          steps:
+            - run: docker exec mmaction pip install timm
+      - when:
+          condition:
+            equal: [ "1.6.0", << parameters.torch >> ]
+          steps:
+            - run: docker exec mmaction pip install timm==0.6.7
       - when:
           condition:
             equal: [ "10.2", << parameters.cuda >> ]

.github/workflows/build.yml

@@ -81,7 +81,7 @@ jobs:
         run: rm -rf .eggs && pip install -e .
       - name: Run unittests and generate coverage report
         run: |
-          coverage run --branch --source mmaction -m pytest tests/
+          coverage run --branch --source mmaction -m pytest tests/ -k 'not timm'
           coverage xml
           coverage report -m
   build_cu101:
@@ -138,7 +138,7 @@ jobs:
         run: rm -rf .eggs && pip install -e .
       - name: Run unittests and generate coverage report
         run: |
-          coverage run --branch --source mmaction -m pytest tests/
+          coverage run --branch --source mmaction -m pytest tests/ -k 'not timm'
           coverage xml
           coverage report -m
       # Only upload coverage report for python3.7 && pytorch1.5
@@ -188,6 +188,8 @@ jobs:
         run: python -m pip install lmdb
       - name: Install PyTorch
         run: python -m pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install timm
+        run: python -m pip install timm
       - name: Install mmaction dependencies
         run: |
           python -V
@@ -229,6 +231,8 @@ jobs:
       - name: Install PyTorch
         # As a complement to Linux CI, we test on PyTorch LTS version
         run: pip install torch==1.8.2+${{ matrix.platform }} torchvision==0.9.2+${{ matrix.platform }} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
+      - name: Install timm
+        run: python -m pip install timm
       - name: Install MMCV
         run: pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cpu/torch1.8/index.html --only-binary mmcv-full
       - name: Install mmaction dependencies

requirements/optional.txt

@@ -9,4 +9,3 @@ onnxruntime
 packaging
 pims
 PyTurboJPEG
-timm

setup.cfg

@@ -4,9 +4,6 @@ universal=1
 [aliases]
 test=pytest
 
-[tool:pytest]
-addopts=tests/
-
 [yapf]
 based_on_style = pep8
 blank_line_before_nested_class_or_def = true

tests/test_models/test_recognizers/test_recognizer2d.py

@@ -98,28 +98,6 @@ def test_tsn():
         for one_img in img_list:
             recognizer(one_img, None, return_loss=False)
 
-    # test timm backbones
-    timm_backbone = dict(type='timm.efficientnet_b0', pretrained=False)
-    config.model['backbone'] = timm_backbone
-    config.model['cls_head']['in_channels'] = 1280
-
-    recognizer = build_recognizer(config.model)
-
-    input_shape = (1, 3, 3, 32, 32)
-    demo_inputs = generate_recognizer_demo_inputs(input_shape)
-
-    imgs = demo_inputs['imgs']
-    gt_labels = demo_inputs['gt_labels']
-
-    losses = recognizer(imgs, gt_labels)
-    assert isinstance(losses, dict)
-
-    # Test forward test
-    with torch.no_grad():
-        img_list = [img[None, :] for img in imgs]
-        for one_img in img_list:
-            recognizer(one_img, None, return_loss=False)
-
 
 def test_tsm():
     config = get_recognizer_cfg('tsm/tsm_r50_1x1x8_50e_kinetics400_rgb.py')
@@ -280,3 +258,29 @@ def test_tanet():
     recognizer(imgs, gradcam=True)
     for one_img in img_list:
         recognizer(one_img, gradcam=True)
+
+
+def test_timm_backbone():
+    # test tsn from timm
+    config = get_recognizer_cfg('tsn/tsn_r50_1x1x3_100e_kinetics400_rgb.py')
+    config.model['backbone']['pretrained'] = None
+    timm_backbone = dict(type='timm.efficientnet_b0', pretrained=False)
+    config.model['backbone'] = timm_backbone
+    config.model['cls_head']['in_channels'] = 1280
+
+    recognizer = build_recognizer(config.model)
+
+    input_shape = (1, 3, 3, 32, 32)
+    demo_inputs = generate_recognizer_demo_inputs(input_shape)
+
+    imgs = demo_inputs['imgs']
+    gt_labels = demo_inputs['gt_labels']
+
+    losses = recognizer(imgs, gt_labels)
+    assert isinstance(losses, dict)
+
+    # Test forward test
+    with torch.no_grad():
+        img_list = [img[None, :] for img in imgs]
+        for one_img in img_list:
+            recognizer(one_img, None, return_loss=False)