01e2ad83afd612d5ebbb5ef93d0004a4d6dfd9a1,allennlp/data/token_indexers/pretrained_transformer_indexer.py,PretrainedTransformerIndexer,as_padded_tensor_dict,#PretrainedTransformerIndexer#Any#Any#,193

Before Change

                    pad_sequence_to_length(val, padding_lengths[key], default_value=lambda: False)
                )
            else:
                tensor = torch.LongTensor(
                    pad_sequence_to_length(
                        val,
                        padding_lengths[key],
                        default_value=lambda: 0
                        if key == "type_ids"
                        else self._tokenizer.pad_token_id,
                    ),
                )
            tensor_dict[key] = tensor
        return tensor_dict

    def __eq__(self, other):

After Change

    ) -> Dict[str, torch.Tensor]:
        tensor_dict = {}
        for key, val in tokens.items():
            if key == "type_ids":
                padding_value = 0
                mktensor = torch.LongTensor
            elif key == "mask":
                padding_value = False
                mktensor = torch.BoolTensor
            elif len(val) > 0 and isinstance(val[0], bool):
                padding_value = False
                mktensor = torch.BoolTensor
            else:
                padding_value = self._tokenizer.pad_token_id
                mktensor = torch.LongTensor

            tensor = mktensor(
                pad_sequence_to_length(
                    val, padding_lengths[key], default_value=lambda: padding_value
                )

Instances