[fix] Move _adjust_logits above postprocess to fix Marian.generate (#5126)
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@@ -792,7 +792,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin):
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def prepare_inputs_for_generation(self, input_ids, **kwargs):
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return {"input_ids": input_ids}
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def prepare_logits_for_generation(self, logits, **kwargs):
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def adjust_logits_during_generation(self, logits, **kwargs):
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return logits
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def _use_cache(self, outputs, use_cache):
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@@ -1396,6 +1396,11 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin):
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# if model has past, then set the past variable to speed up decoding
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if self._use_cache(outputs, use_cache):
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past = outputs[1]
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if self.config.is_encoder_decoder and do_sample is False:
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# TODO (PVP) still a bit hacky here - there might be a better solution
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next_token_logits = self.adjust_logits_during_generation(
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next_token_logits, cur_len=cur_len, max_length=max_length
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)
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scores = F.log_softmax(next_token_logits, dim=-1) # (batch_size * num_beams, vocab_size)
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@@ -1413,10 +1418,6 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin):
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num_beams=num_beams,
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)
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if self.config.is_encoder_decoder and do_sample is False:
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# TODO (PVP) still a bit hacky here - there might be a better solution
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scores = self.prepare_logits_for_generation(scores, cur_len=cur_len, max_length=max_length)
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assert scores.shape == (batch_size * num_beams, vocab_size), "Shapes of scores: {} != {}".format(
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scores.shape, (batch_size * num_beams, vocab_size)
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)
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