e2799c64b7b8248de872ca7fb741080079839710,onmt/translate/translator.py,Translator,_translate_batch,#Translator#Any#Any#Any#Any#Any#Any#,532

Before Change

        src, enc_states, memory_bank, src_lengths = self._run_encoder(batch)
        self.model.decoder.init_state(src, memory_bank, enc_states)

        results = {}
        results["predictions"] = None
        results["scores"] = None
        results["attention"] = None
        results["batch"] = batch
        if "tgt" in batch.__dict__:
            results["gold_score"] = self._score_target(
                batch,
                memory_bank,
                src_lengths,
                src_vocabs,
                batch.src_map if use_src_map else None
            )
            self.model.decoder.init_state(src, memory_bank, enc_states)
        else:
            results["gold_score"] = [0] * batch_size

        // (2) Repeat src objects `beam_size` times.
        // We use batch_size x beam_size
        src_map = (tile(batch.src_map, beam_size, dim=1)
                   if use_src_map else None)
        self.model.decoder.map_state(
            lambda state, dim: tile(state, beam_size, dim=dim))

After Change

        src, enc_states, memory_bank, src_lengths = self._run_encoder(batch)
        self.model.decoder.init_state(src, memory_bank, enc_states)

        results = {
            "predictions": None,
            "scores": None,
            "attention": None,
            "batch": batch,
            "gold_score": self._gold_score(
                batch, memory_bank, src_lengths, src_vocabs, use_src_map,
                enc_states, batch_size, src)}

        // (2) Repeat src objects `beam_size` times.
        // We use batch_size x beam_size
        src_map = (tile(batch.src_map, beam_size, dim=1)

Instances