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allow to load pretrained weights when the include_top variable is False #290

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2 changes: 1 addition & 1 deletion efficientnet_pytorch/model.py
Original file line number Diff line number Diff line change
Expand Up @@ -376,7 +376,7 @@ def from_pretrained(cls, model_name, weights_path=None, advprop=False,
"""
model = cls.from_name(model_name, num_classes=num_classes, **override_params)
load_pretrained_weights(model, model_name, weights_path=weights_path,
load_fc=(num_classes == 1000), advprop=advprop)
load_fc=(num_classes == 1000) and model._global_params.include_top, advprop=advprop)
model._change_in_channels(in_channels)
return model

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2 changes: 1 addition & 1 deletion efficientnet_pytorch/utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -608,7 +608,7 @@ def load_pretrained_weights(model, model_name, weights_path=None, load_fc=True,
state_dict.pop('_fc.weight')
state_dict.pop('_fc.bias')
ret = model.load_state_dict(state_dict, strict=False)
assert set(ret.missing_keys) == set(
assert not ret.missing_keys or set(ret.missing_keys) == set(
['_fc.weight', '_fc.bias']), 'Missing keys when loading pretrained weights: {}'.format(ret.missing_keys)
assert not ret.unexpected_keys, 'Missing keys when loading pretrained weights: {}'.format(ret.unexpected_keys)

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