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Enable ONNX export when PyTorch and TensorFlow installed in the same env #15625

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merged 1 commit into from Feb 11, 2022
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Enable ONNX export when PyTorch and TensorFlow installed in the same env #15625

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10 changes: 9 additions & 1 deletion src/transformers/onnx/features.py
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Expand Up @@ -303,8 +303,16 @@ def get_model_from_feature(feature: str, model: str) -> Union[PreTrainedModel, T
The instance of the model.

"""
# If PyTorch and TensorFlow are installed in the same environment, we
# load an AutoModel class by default
model_class = FeaturesManager.get_model_class_for_feature(feature)
return model_class.from_pretrained(model)
try:
model = model_class.from_pretrained(model)
# Load TensorFlow weights in an AutoModel instance if PyTorch and
# TensorFlow are installed in the same environment
except OSError:
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Are you sure it's the only possible exception that can be raised?
It seems like EnvironmentError and ValueError can be raised too according to here and here.

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The second Value error is complete legacy code for when people pass the name of filename, you won't reach it with an auto model call :-)

model = model_class.from_pretrained(model, from_tf=True)
return model

@staticmethod
def check_supported_model_or_raise(
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