4fa9abb648cebe9425250181bdce2bbf805aa7fe,onmt/decoders/transformer.py,TransformerDecoder,forward,#TransformerDecoder#,218

Before Change

        src_memory_bank = memory_bank.transpose(0, 1).contiguous()

        padding_idx = self.embeddings.word_padding_idx
        src_pad_mask = src_words.data.eq(padding_idx).unsqueeze(1) \
            .expand(src_batch, tgt_len, src_len)
        tgt_pad_mask = tgt_words.data.eq(padding_idx).unsqueeze(1) \
            .expand(tgt_batch, tgt_len, tgt_len)

        if self.state["cache"] is None:

After Change

        src_memory_bank = memory_bank.transpose(0, 1).contiguous()

        padding_idx = self.embeddings.word_padding_idx
        src_pad_mask = src_words.data.eq(padding_idx).unsqueeze(1)
        tgt_pad_mask = tgt_words.data.eq(padding_idx).unsqueeze(1)

        if self.state["cache"] is None:
            saved_inputs = []

Instances