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fix: Fixed load_pretrained_params in PyTorch when ignoring keys #902

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merged 11 commits into from
Apr 28, 2022
Merged

fix: Fixed load_pretrained_params in PyTorch when ignoring keys #902

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43814e3
fix: Fixed load_pretrained_params
Apr 27, 2022
f1f63a9
fix: Fixed ignore_keys for models in PyTorch
Apr 27, 2022
b51b217
test: Updated unittest accordingly
Apr 27, 2022
1bdedd2
refactor: Improved checks
Apr 27, 2022
2d28bf1
test: Added unittest for ignore_keys
Apr 27, 2022
b2a21dc
fix: Added missing import
Apr 28, 2022
79173f4
style: Fixed typing
Apr 28, 2022
de0652b
refactor: Refactored recognition ignore_keys
Apr 28, 2022
f8202ee
fix: Fixed typo
Apr 28, 2022
7de2ddc
fix: Fixed ResNet
Apr 28, 2022
5165d30
fix: Fixed load conditions
Apr 28, 2022
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refactor: Refactored recognition ignore_keys
  • Loading branch information
FG Fernandez committed Apr 28, 2022
commit de0652bd3931d062f61c1235fca5d5ddf9eaee47
29 changes: 20 additions & 9 deletions doctr/models/recognition/crnn/pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -221,6 +221,7 @@ def _crnn(
pretrained: bool,
backbone_fn: Callable[[Any], nn.Module],
pretrained_backbone: bool = True,
ignore_keys: Optional[List[str]] = None,
**kwargs: Any,
) -> CRNN:

Expand All @@ -240,12 +241,10 @@ def _crnn(
model = CRNN(feat_extractor, cfg=_cfg, **kwargs) # type: ignore[arg-type]
# Load pretrained parameters
if pretrained:
if _cfg['vocab'] != default_cfgs[arch]['vocab']:
# The number of classes is not the same as the number of classes in the pretrained model =>
# remove the last layer weights
load_pretrained_params(model, _cfg['url'], pop_entrys=['linear.weight', 'linear.bias'])
else:
load_pretrained_params(model, _cfg['url'])
# The number of classes is not the same as the number of classes in the pretrained model =>
# remove the last layer weights
_ignore_keys = ignore_keys if kwargs['num_classes'] == len(default_cfgs[arch]['classes']) else None
load_pretrained_params(model, _cfg['url'], ignore_keys=_ignore_keys)

return model

Expand All @@ -267,7 +266,7 @@ def crnn_vgg16_bn(pretrained: bool = False, **kwargs: Any) -> CRNN:
text recognition architecture
"""

return _crnn('crnn_vgg16_bn', pretrained, vgg16_bn_r, **kwargs)
return _crnn('crnn_vgg16_bn', pretrained, vgg16_bn_r, ignore_keys=['linear.weight', 'linear.bias'], **kwargs)


def crnn_mobilenet_v3_small(pretrained: bool = False, **kwargs: Any) -> CRNN:
Expand All @@ -287,7 +286,13 @@ def crnn_mobilenet_v3_small(pretrained: bool = False, **kwargs: Any) -> CRNN:
text recognition architecture
"""

return _crnn('crnn_mobilenet_v3_small', pretrained, mobilenet_v3_small_r, **kwargs)
return _crnn(
'crnn_mobilenet_v3_small',
pretrained,
mobilenet_v3_small_r,
ignore_keys=['linear.weight', 'linear.bias'],
**kwargs,
)


def crnn_mobilenet_v3_large(pretrained: bool = False, **kwargs: Any) -> CRNN:
Expand All @@ -307,4 +312,10 @@ def crnn_mobilenet_v3_large(pretrained: bool = False, **kwargs: Any) -> CRNN:
text recognition architecture
"""

return _crnn('crnn_mobilenet_v3_large', pretrained, mobilenet_v3_large_r, **kwargs)
return _crnn(
'crnn_mobilenet_v3_large',
pretrained,
mobilenet_v3_large_r,
ignore_keys=['linear.weight', 'linear.bias'],
**kwargs,
)
2 changes: 1 addition & 1 deletion doctr/models/utils/pytorch.py
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Expand Up @@ -28,7 +28,7 @@ def load_pretrained_params(
>>> load_pretrained_params(model, "https://yoursource.com/yourcheckpoint-yourhash.zip")

Args:
model: the keras model to be loaded
model: the PyTorch model to be loaded
url: URL of the zipped set of parameters
hash_prefix: first characters of SHA256 expected hash
overwrite: should the zip extraction be enforced if the archive has already been extracted
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