f255b7f90185f4bb38f23ad2499361443177fdd6,test/test_models.py,TestModel,embeddings_forward,#TestModel#Any#Any#Any#,41

Before Change

        """
        vocab = self.get_vocab()
        feats_padding_idx = []
        emb = make_embeddings(opt, vocab.stoi[onmt.IO.PAD_WORD],
                              feats_padding_idx, len(vocab),
                              for_encoder=True)
        test_src, _, __ = self.get_batch(sourceL=sourceL,
                                         bsize=bsize)
        if opt.decoder_type == "transformer":
            input = torch.cat([test_src, test_src], 0)

After Change

        """
        word_dict = self.get_vocab()
        feature_dicts = []
        emb = make_embeddings(opt, word_dict, feature_dicts)
        test_src, _, __ = self.get_batch(sourceL=sourceL,
                                         bsize=bsize)
        if opt.decoder_type == "transformer":
            input = torch.cat([test_src, test_src], 0)

Instances