[Enhance] Enhance get_torchvision_models

mmcv/model_zoo/torchvision_0.12.json

@@ -0,0 +1,57 @@
+{
+    "alexnet": "https://download.pytorch.org/models/alexnet-owt-7be5be79.pth",
+    "densenet121": "https://download.pytorch.org/models/densenet121-a639ec97.pth",
+    "densenet169": "https://download.pytorch.org/models/densenet169-b2777c0a.pth",
+    "densenet201": "https://download.pytorch.org/models/densenet201-c1103571.pth",
+    "densenet161": "https://download.pytorch.org/models/densenet161-8d451a50.pth",
+    "efficientnet_b0": "https://download.pytorch.org/models/efficientnet_b0_rwightman-3dd342df.pth",
+    "efficientnet_b1": "https://download.pytorch.org/models/efficientnet_b1_rwightman-533bc792.pth",
+    "efficientnet_b2": "https://download.pytorch.org/models/efficientnet_b2_rwightman-bcdf34b7.pth",
+    "efficientnet_b3": "https://download.pytorch.org/models/efficientnet_b3_rwightman-cf984f9c.pth",
+    "efficientnet_b4": "https://download.pytorch.org/models/efficientnet_b4_rwightman-7eb33cd5.pth",
+    "efficientnet_b5": "https://download.pytorch.org/models/efficientnet_b5_lukemelas-b6417697.pth",
+    "efficientnet_b6": "https://download.pytorch.org/models/efficientnet_b6_lukemelas-c76e70fd.pth",
+    "efficientnet_b7": "https://download.pytorch.org/models/efficientnet_b7_lukemelas-dcc49843.pth",
+    "googlenet": "https://download.pytorch.org/models/googlenet-1378be20.pth",
+    "inception_v3_google": "https://download.pytorch.org/models/inception_v3_google-0cc3c7bd.pth",
+    "mobilenet_v2": "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth",
+    "mobilenet_v3_large": "https://download.pytorch.org/models/mobilenet_v3_large-8738ca79.pth",
+    "mobilenet_v3_small": "https://download.pytorch.org/models/mobilenet_v3_small-047dcff4.pth",
+    "regnet_y_400mf": "https://download.pytorch.org/models/regnet_y_400mf-c65dace8.pth",
+    "regnet_y_800mf": "https://download.pytorch.org/models/regnet_y_800mf-1b27b58c.pth",
+    "regnet_y_1_6gf": "https://download.pytorch.org/models/regnet_y_1_6gf-b11a554e.pth",
+    "regnet_y_3_2gf": "https://download.pytorch.org/models/regnet_y_3_2gf-b5a9779c.pth",
+    "regnet_y_8gf": "https://download.pytorch.org/models/regnet_y_8gf-d0d0e4a8.pth",
+    "regnet_y_16gf": "https://download.pytorch.org/models/regnet_y_16gf-9e6ed7dd.pth",
+    "regnet_y_32gf": "https://download.pytorch.org/models/regnet_y_32gf-4dee3f7a.pth",
+    "regnet_x_400mf": "https://download.pytorch.org/models/regnet_x_400mf-adf1edd5.pth",
+    "regnet_x_800mf": "https://download.pytorch.org/models/regnet_x_800mf-ad17e45c.pth",
+    "regnet_x_1_6gf": "https://download.pytorch.org/models/regnet_x_1_6gf-e3633e7f.pth",
+    "regnet_x_3_2gf": "https://download.pytorch.org/models/regnet_x_3_2gf-f342aeae.pth",
+    "regnet_x_8gf": "https://download.pytorch.org/models/regnet_x_8gf-03ceed89.pth",
+    "regnet_x_16gf": "https://download.pytorch.org/models/regnet_x_16gf-2007eb11.pth",
+    "regnet_x_32gf": "https://download.pytorch.org/models/regnet_x_32gf-9d47f8d0.pth",
+    "resnet18": "https://download.pytorch.org/models/resnet18-f37072fd.pth",
+    "resnet34": "https://download.pytorch.org/models/resnet34-b627a593.pth",
+    "resnet50": "https://download.pytorch.org/models/resnet50-0676ba61.pth",
+    "resnet101": "https://download.pytorch.org/models/resnet101-63fe2227.pth",
+    "resnet152": "https://download.pytorch.org/models/resnet152-394f9c45.pth",
+    "resnext50_32x4d": "https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth",
+    "resnext101_32x8d": "https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth",
+    "wide_resnet50_2": "https://download.pytorch.org/models/wide_resnet50_2-95faca4d.pth",
+    "wide_resnet101_2": "https://download.pytorch.org/models/wide_resnet101_2-32ee1156.pth",
+    "shufflenetv2_x0.5": "https://download.pytorch.org/models/shufflenetv2_x0.5-f707e7126e.pth",
+    "shufflenetv2_x1.0": "https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth",
+    "shufflenetv2_x1.5": null,
+    "shufflenetv2_x2.0": null,
+    "squeezenet1_0": "https://download.pytorch.org/models/squeezenet1_0-b66bff10.pth",
+    "squeezenet1_1": "https://download.pytorch.org/models/squeezenet1_1-b8a52dc0.pth",
+    "vgg11": "https://download.pytorch.org/models/vgg11-8a719046.pth",
+    "vgg13": "https://download.pytorch.org/models/vgg13-19584684.pth",
+    "vgg16": "https://download.pytorch.org/models/vgg16-397923af.pth",
+    "vgg19": "https://download.pytorch.org/models/vgg19-dcbb9e9d.pth",
+    "vgg11_bn": "https://download.pytorch.org/models/vgg11_bn-6002323d.pth",
+    "vgg13_bn": "https://download.pytorch.org/models/vgg13_bn-abd245e5.pth",
+    "vgg16_bn": "https://download.pytorch.org/models/vgg16_bn-6c64b313.pth",
+    "vgg19_bn": "https://download.pytorch.org/models/vgg19_bn-c79401a0.pth"
+}

mmcv/runner/checkpoint.py

@@ -18,7 +18,7 @@
 from ..fileio import FileClient
 from ..fileio import load as load_file
 from ..parallel import is_module_wrapper
-from ..utils import load_url, mkdir_or_exist
+from ..utils import digit_version, load_url, mkdir_or_exist
 from .dist_utils import get_dist_info
 
 ENV_MMCV_HOME = 'MMCV_HOME'
@@ -106,14 +106,48 @@ def load(module, prefix=''):
 
 
 def get_torchvision_models():
-    model_urls = dict()
-    for _, name, ispkg in pkgutil.walk_packages(torchvision.models.__path__):
-        if ispkg:
-            continue
-        _zoo = import_module(f'torchvision.models.{name}')
-        if hasattr(_zoo, 'model_urls'):
-            _urls = getattr(_zoo, 'model_urls')
-            model_urls.update(_urls)
+    if digit_version(torchvision.__version__) < digit_version('0.13.0a0'):
+        model_urls = dict()
+        # When the version of torchvision is lower than 0.13, the model url is
+        # not declared in `torchvision.model.__init__.py`, so we need to
+        # iterate through `torchvision.models.__path__` to get the url for each
+        # model.
+        for _, name, ispkg in pkgutil.walk_packages(
+                torchvision.models.__path__):
+            if ispkg:
+                continue
+            _zoo = import_module(f'torchvision.models.{name}')
+            if hasattr(_zoo, 'model_urls'):
+                _urls = getattr(_zoo, 'model_urls')
+                model_urls.update(_urls)
+    else:
+        # Since torchvision bumps to v0.13, the weight loading logic,
+        # model keys and model urls have been changed. Here the URLs of old
+        # version is loaded to avoid breaking back compatibility. If the
+        # torchvision version>=0.13.0, new URLs will be added. Users can get
+        # the resnet50 checkpoint by setting 'resnet50.imagent1k_v1',
+        # 'resnet50' or 'ResNet50_Weights.IMAGENET1K_V1' in the config.
+        json_path = osp.join(mmcv.__path__[0],
+                             'model_zoo/torchvision_0.12.json')
+        model_urls = mmcv.load(json_path)
+        for cls_name, cls in torchvision.models.__dict__.items():
+            # The name of torchvision model weights classes ends with
+            # `_Weights` such as `ResNet18_Weights`. However, some model weight
+            # classes, such as `MNASNet0_75_Weights` does not have any urls in
+            # torchvision 0.13.0 and cannot be iterated. Here we simply check
+            # `DEFAULT` attribute to ensure the class is not empty.
+            if (not cls_name.endswith('_Weights')
+                    or not hasattr(cls, 'DEFAULT')):
+                continue
+            # Since `cls.DEFAULT` can not be accessed by iterating cls, we set
+            # default urls explicitly.
+            cls_key = cls_name.replace('_Weights', '').lower()
+            model_urls[f'{cls_key}.default'] = cls.DEFAULT.url
+            for weight_enum in cls:
+                cls_key = cls_name.replace('_Weights', '').lower()
+                cls_key = f'{cls_key}.{weight_enum.name.lower()}'
+                model_urls[cls_key] = weight_enum.url
+
     return model_urls
 
 
@@ -396,6 +430,11 @@ def load_from_torchvision(filename, map_location=None):
         model_name = filename[11:]
     else:
         model_name = filename[14:]
+
+    # Support getting model urls in the same way as torchvision
+    # `ResNet50_Weights.IMAGENET1K_V1` will be mapped to
+    # resnet50.imagenet1k_v1.
+    model_name = model_name.lower().replace('_weights', '')
     return load_from_http(model_urls[model_name], map_location=map_location)
 
 

tests/test_load_model_zoo.py

@@ -4,14 +4,15 @@
 from unittest.mock import patch
 
 import pytest
+import torchvision
 
 import mmcv
 from mmcv.runner.checkpoint import (DEFAULT_CACHE_DIR, ENV_MMCV_HOME,
                                     ENV_XDG_CACHE_HOME, _get_mmcv_home,
                                     _load_checkpoint,
                                     get_deprecated_model_names,
                                     get_external_models)
-from mmcv.utils import TORCH_VERSION
+from mmcv.utils import digit_version
 
 
 @patch('mmcv.__path__', [osp.join(osp.dirname(__file__), 'data/')])
@@ -77,24 +78,33 @@ def load(filepath, map_location=None):
 @patch('torch.load', load)
 def test_load_external_url():
     # test modelzoo://
-    url = _load_checkpoint('modelzoo://resnet50')
-    if TORCH_VERSION < '1.9.0':
-        assert url == ('url:https://download.pytorch.org/models/resnet50-19c8e'
-                       '357.pth')
+    torchvision_version = torchvision.__version__
+    if digit_version(torchvision_version) < digit_version('0.10.0a0'):
+        assert (_load_checkpoint('modelzoo://resnet50') ==
+                'url:https://download.pytorch.org/models/resnet50-19c8e'
+                '357.pth')
+        assert (_load_checkpoint('torchvision://resnet50') ==
+                'url:https://download.pytorch.org/models/resnet50-19c8e'
+                '357.pth')
     else:
-        # filename of checkpoint is renamed in torch1.9.0
-        assert url == ('url:https://download.pytorch.org/models/resnet50-0676b'
-                       'a61.pth')
-
-    # test torchvision://
-    url = _load_checkpoint('torchvision://resnet50')
-    if TORCH_VERSION < '1.9.0':
-        assert url == ('url:https://download.pytorch.org/models/resnet50-19c8e'
-                       '357.pth')
-    else:
-        # filename of checkpoint is renamed in torch1.9.0
-        assert url == ('url:https://download.pytorch.org/models/resnet50-0676b'
-                       'a61.pth')
+        assert (_load_checkpoint('modelzoo://resnet50') ==
+                'url:https://download.pytorch.org/models/resnet50-0676b'
+                'a61.pth')
+        assert (_load_checkpoint('torchvision://resnet50') ==
+                'url:https://download.pytorch.org/models/resnet50-0676b'
+                'a61.pth')
+
+    if digit_version(torchvision_version) >= digit_version('0.13.0a0'):
+        # Test load new format torchvision models.
+        assert (
+            _load_checkpoint('torchvision://resnet50.imagenet1k_v1') ==
+            'url:https://download.pytorch.org/models/resnet50-0676ba61.pth')
+
+        assert (
+            _load_checkpoint('torchvision://ResNet50_Weights.IMAGENET1K_V1') ==
+            'url:https://download.pytorch.org/models/resnet50-0676ba61.pth')
+
+        _load_checkpoint('torchvision://resnet50.default')
 
     # test open-mmlab:// with default MMCV_HOME
     os.environ.pop(ENV_MMCV_HOME, None)