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Ignore unexpected weights from PT conversion (#10397)

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Lysandre Debut
2021-02-25 16:42:27 +01:00
committed by GitHub
parent 63645b3b11
commit 88cc26dcd1
1 changed files with 5 additions and 1 deletions
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src/transformers/models/bert/modeling_tf_bert.py
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@@ -919,7 +919,11 @@ Bert Model with two heads on top as done during the pretraining:
) )
class TFBertForPreTraining(TFBertPreTrainedModel, TFBertPreTrainingLoss): class TFBertForPreTraining(TFBertPreTrainedModel, TFBertPreTrainingLoss):
# names with a '.' represents the authorized unexpected/missing layers when a TF model is loaded from a PT model # names with a '.' represents the authorized unexpected/missing layers when a TF model is loaded from a PT model
_keys_to_ignore_on_load_unexpected = [r"cls.predictions.decoder.weight"] _keys_to_ignore_on_load_unexpected = [
r"position_ids",
r"cls.predictions.decoder.weight",
r"cls.predictions.decoder.bias",
]
def __init__(self, config: BertConfig, *inputs, **kwargs): def __init__(self, config: BertConfig, *inputs, **kwargs):
super().__init__(config, *inputs, **kwargs) super().__init__(config, *inputs, **kwargs)