27568a7ebed1a35f08ac0390f35b3de9b8dad0dd,fairseq/models/levenshtein_transformer.py,LevenshteinTransformerModel,initialize_output_tokens,#LevenshteinTransformerModel#Any#Any#,491

Before Change

        return [output_tokens, output_scores, attn, 0, 0]

    def initialize_output_tokens(self, encoder_out, src_tokens):
        initial_output_tokens = torch.cat(
            [
                torch.zeros(src_tokens.size(0), 1).fill_(self.bos),
                torch.zeros(src_tokens.size(0), 1).fill_(self.eos),
            ],
            1,
        )

        initial_output_scores = torch.zeros_like(initial_output_tokens).to(
            encoder_out[0]
        )

        initial_attn = torch.empty([0])
        if getattr(self.decoder.layers[-1], "need_attn", True):
            initial_attn = torch.zeros([src_tokens.size(0), 2, src_tokens.size(1)]).to(
                initial_output_tokens
            )

        return [initial_output_tokens, initial_output_scores, initial_attn, 0, 0]


class LevenshteinTransformerDecoder(TracingTransformerDecoder):
    def __init__(self, args, dictionary, embed_tokens, no_encoder_attn=False):

After Change

        initial_output_tokens[:, 0] = self.bos
        initial_output_tokens[:, 1] = self.eos

        initial_output_scores = initial_output_tokens.new_zeros(
            *initial_output_tokens.size()
        ).type_as(encoder_out.encoder_out)
        return DecoderOut(
            output_tokens=initial_output_tokens,
            output_scores=initial_output_scores,
            attn=None,
            step=0,
            max_step=0,
        )


class LevenshteinTransformerDecoder(TransformerDecoder):
    def __init__(self, args, dictionary, embed_tokens, no_encoder_attn=False):

Instances