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fix test_model_default_cfgs

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This commit is contained in:
Yusuke Uchida 2020-08-11 23:23:57 +09:00
parent 078a51dbac
commit f6b56602f9
9 changed files with 56 additions and 31 deletions
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5
tests/test_models.py
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@ -69,6 +69,7 @@ def test_model_backward(model_name, batch_size):
@pytest.mark.timeout(120)
@pytest.mark.parametrize('model_name', list_models())
#@pytest.mark.parametrize('model_name', ["xception41"])
@pytest.mark.parametrize('batch_size', [1])
def test_model_default_cfgs(model_name, batch_size):
"""Run a single forward pass with each model"""
@ -106,8 +107,8 @@ def test_model_default_cfgs(model_name, batch_size):
assert outputs.shape[-1] == pool_size[-1] and outputs.shape[-2] == pool_size[-2]
# check classifier and first convolution names match those in default_cfg
assert any([k.startswith(classifier) for k in state_dict.keys()]), f'{classifier} not in model params'
assert any([k.startswith(first_conv) for k in state_dict.keys()]), f'{first_conv} not in model params'
assert classifier + ".weight" in state_dict.keys(), f'{classifier} not in model params'
assert first_conv + ".weight" in state_dict.keys(), f'{first_conv} not in model params'
if 'GITHUB_ACTIONS' not in os.environ:

30
timm/models/gluon_resnet.py
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@ -28,22 +28,32 @@ default_cfgs = {
'gluon_resnet50_v1b': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1b-0ebe02e2.pth'),
'gluon_resnet101_v1b': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1b-3b017079.pth'),
'gluon_resnet152_v1b': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1b-c1edb0dd.pth'),
'gluon_resnet50_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1c-48092f55.pth'),
'gluon_resnet101_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1c-1f26822a.pth'),
'gluon_resnet152_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1c-a3bb0b98.pth'),
'gluon_resnet50_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1d-818a1b1b.pth'),
'gluon_resnet101_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1d-0f9c8644.pth'),
'gluon_resnet152_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1d-bd354e12.pth'),
'gluon_resnet50_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1s-1762acc0.pth'),
'gluon_resnet101_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1s-60fe0cc1.pth'),
'gluon_resnet152_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1s-dcc41b81.pth'),
'gluon_resnet50_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1c-48092f55.pth',
first_conv='conv1.0'),
'gluon_resnet101_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1c-1f26822a.pth',
first_conv='conv1.0'),
'gluon_resnet152_v1c': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1c-a3bb0b98.pth',
first_conv='conv1.0'),
'gluon_resnet50_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1d-818a1b1b.pth',
first_conv='conv1.0'),
'gluon_resnet101_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1d-0f9c8644.pth',
first_conv='conv1.0'),
'gluon_resnet152_v1d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1d-bd354e12.pth',
first_conv='conv1.0'),
'gluon_resnet50_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet50_v1s-1762acc0.pth',
first_conv='conv1.0'),
'gluon_resnet101_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet101_v1s-60fe0cc1.pth',
first_conv='conv1.0'),
'gluon_resnet152_v1s': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnet152_v1s-dcc41b81.pth',
first_conv='conv1.0'),
'gluon_resnext50_32x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnext50_32x4d-e6a097c1.pth'),
'gluon_resnext101_32x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnext101_32x4d-b253c8c4.pth'),
'gluon_resnext101_64x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_resnext101_64x4d-f9a8e184.pth'),
'gluon_seresnext50_32x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_seresnext50_32x4d-90cf2d6e.pth'),
'gluon_seresnext101_32x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_seresnext101_32x4d-cf52900d.pth'),
'gluon_seresnext101_64x4d': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_seresnext101_64x4d-f9926f93.pth'),
'gluon_senet154': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_senet154-70a1a3c0.pth'),
'gluon_senet154': _cfg(url='https://github.com/rwightman/pytorch-pretrained-gluonresnet/releases/download/v0.1/gluon_senet154-70a1a3c0.pth',
first_conv='conv1.0'),
}

2
timm/models/inception_v3.py
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@ -19,7 +19,7 @@ def _cfg(url='', **kwargs):
'num_classes': 1000, 'input_size': (3, 299, 299), 'pool_size': (8, 8),
'crop_pct': 0.875, 'interpolation': 'bicubic',
'mean': IMAGENET_INCEPTION_MEAN, 'std': IMAGENET_INCEPTION_STD,
'first_conv': 'Conv2d_1a_3x3', 'classifier': 'fc',
'first_conv': 'Conv2d_1a_3x3.conv', 'classifier': 'fc',
**kwargs
}

2
timm/models/resnest.py
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@ -22,7 +22,7 @@ def _cfg(url='', **kwargs):
'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
'crop_pct': 0.875, 'interpolation': 'bilinear',
'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
'first_conv': 'conv1', 'classifier': 'fc',
'first_conv': 'conv1.0', 'classifier': 'fc',
**kwargs
}

39
timm/models/resnet.py
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@ -42,13 +42,15 @@ default_cfgs = {
interpolation='bicubic'),
'resnet26d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet26d-69e92c46.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'resnet50': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet50_ram-a26f946b.pth',
interpolation='bicubic'),
'resnet50d': _cfg(
url='',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'resnet101': _cfg(url='https://download.pytorch.org/models/resnet101-5d3b4d8f.pth'),
'resnet152': _cfg(url='https://download.pytorch.org/models/resnet152-b121ed2d.pth'),
'tv_resnet34': _cfg(url='https://download.pytorch.org/models/resnet34-333f7ec4.pth'),
@ -62,7 +64,8 @@ default_cfgs = {
interpolation='bicubic'),
'resnext50d_32x4d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnext50d_32x4d-103e99f8.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'resnext101_32x4d': _cfg(url=''),
'resnext101_32x8d': _cfg(url='https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth'),
'resnext101_64x4d': _cfg(url=''),
@ -118,7 +121,8 @@ default_cfgs = {
interpolation='bicubic'),
'seresnet50tn': _cfg(
url='',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'seresnet101': _cfg(
url='',
interpolation='bicubic'),
@ -132,13 +136,16 @@ default_cfgs = {
interpolation='bicubic'),
'seresnext26d_32x4d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26d_32x4d-80fa48a3.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'seresnext26t_32x4d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26t_32x4d-361bc1c4.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'seresnext26tn_32x4d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/seresnext26tn_32x4d-569cb627.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'seresnext50_32x4d': _cfg(
interpolation='bicubic'),
'seresnext101_32x4d': _cfg(
@ -149,7 +156,8 @@ default_cfgs = {
interpolation='bicubic'),
'senet154': _cfg(
url='',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
# Efficient Channel Attention ResNets
'ecaresnet18': _cfg(),
@ -159,21 +167,26 @@ default_cfgs = {
interpolation='bicubic'),
'ecaresnet50d': _cfg(
url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNet50D_833caf58.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'ecaresnet50d_pruned': _cfg(
url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45899/outputs/ECAResNet50D_P_9c67f710.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'ecaresnet101d': _cfg(
url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45402/outputs/ECAResNet101D_281c5844.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'ecaresnet101d_pruned': _cfg(
url='https://imvl-automl-sh.oss-cn-shanghai.aliyuncs.com/darts/hyperml/hyperml/job_45610/outputs/ECAResNet101D_P_75a3370e.pth',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
# Efficient Channel Attention ResNeXts
'ecaresnext26tn_32x4d': _cfg(
url='',
interpolation='bicubic'),
interpolation='bicubic',
first_conv='conv1.0'),
'ecaresnext50_32x4d': _cfg(
url='',
interpolation='bicubic'),

2
timm/models/selecsls.py
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@ -29,7 +29,7 @@ def _cfg(url='', **kwargs):
'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (4, 4),
'crop_pct': 0.875, 'interpolation': 'bilinear',
'mean': IMAGENET_DEFAULT_MEAN, 'std': IMAGENET_DEFAULT_STD,
'first_conv': 'stem', 'classifier': 'fc',
'first_conv': 'stem.0', 'classifier': 'fc',
**kwargs
}

3
timm/models/sknet.py
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@ -36,7 +36,8 @@ default_cfgs = {
'skresnet34': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/skresnet34_ra-bdc0ccde.pth'),
'skresnet50': _cfg(),
'skresnet50d': _cfg(),
'skresnet50d': _cfg(
first_conv='conv1.0'),
'skresnext50_32x4d': _cfg(
url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/skresnext50_ra-f40e40bf.pth'),
}

2
timm/models/tresnet.py
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@ -25,7 +25,7 @@ def _cfg(url='', **kwargs):
'url': url, 'num_classes': 1000, 'input_size': (3, 224, 224), 'pool_size': (7, 7),
'crop_pct': 0.875, 'interpolation': 'bilinear',
'mean': (0, 0, 0), 'std': (1, 1, 1),
'first_conv': 'body.conv1', 'classifier': 'head.fc',
'first_conv': 'body.conv1.0', 'classifier': 'head.fc',
**kwargs
}

2
timm/models/xception_aligned.py
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@ -25,7 +25,7 @@ def _cfg(url='', **kwargs):
'num_classes': 1000, 'input_size': (3, 299, 299), 'pool_size': (10, 10),
'crop_pct': 0.903, 'interpolation': 'bicubic',
'mean': IMAGENET_INCEPTION_MEAN, 'std': IMAGENET_INCEPTION_STD,
'first_conv': 'stem.0', 'classifier': 'head.fc',
'first_conv': 'stem.0.conv', 'classifier': 'head.fc',
**kwargs
}