f5278f68882ebf89a013611c86eb20345e723df2,pytext/models/seq_models/seq2seq_model.py,Seq2SeqModel,forward,#Seq2SeqModel#Any#Any#Any#Any#,164

Before Change

        if dict_feats:
            additional_features.append(list(dict_feats))

        logits, output_dict = self.model(
            src_tokens, additional_features, src_lengths, trg_tokens
        )

        if dict_feats:
            (
                output_dict["dict_tokens"],

After Change

                create_module(config.dict_embedding, tensorizer=gazetteer_tensorizer)
            )
        contextual_token_tensorizer = tensorizers.get("contextual_token_embedding")
        if contextual_token_tensorizer:
            src_embedding_list.append(
                create_module(
                    config.contextual_token_embedding,
                    tensorizer=contextual_token_tensorizer,

Instances