update modeling_baichuan.py for torchscript mode with past_kv

#30
Files changed (1) hide show
  1. modeling_baichuan.py +4 -2
modeling_baichuan.py CHANGED
@@ -365,7 +365,7 @@ class BaichuanModel(BaichuanPreTrainedModel):
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  use_cache: Optional[bool] = False,
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  output_attentions: Optional[bool] = False,
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  output_hidden_states: Optional[bool] = False,
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- return_dict: Optional[bool] = True,
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  ) -> Union[Tuple, BaseModelOutputWithPast]:
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  if input_ids is not None and inputs_embeds is not None:
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  raise ValueError(
@@ -378,6 +378,8 @@ class BaichuanModel(BaichuanPreTrainedModel):
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  else:
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  raise ValueError("You need to provide input_ids or inputs_embeds")
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  return_dict = (
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  return_dict if return_dict is not None else self.config.use_return_dict
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  )
@@ -682,7 +684,7 @@ class BaichuanForCausalLM(BaichuanPreTrainedModel):
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  use_cache: Optional[bool] = None,
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  output_attentions: Optional[bool] = False,
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  output_hidden_states: Optional[bool] = False,
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- return_dict: Optional[bool] = True,
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  **kwargs,
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  ) -> Union[Tuple, CausalLMOutputWithPast]:
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  return_dict = (
 
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  use_cache: Optional[bool] = False,
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  output_attentions: Optional[bool] = False,
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  output_hidden_states: Optional[bool] = False,
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+ return_dict: Optional[bool] = None,
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  ) -> Union[Tuple, BaseModelOutputWithPast]:
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  if input_ids is not None and inputs_embeds is not None:
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  raise ValueError(
 
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  else:
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  raise ValueError("You need to provide input_ids or inputs_embeds")
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+ use_cache = use_cache if use_cache is not None else self.config.use_cache
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+
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  return_dict = (
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  return_dict if return_dict is not None else self.config.use_return_dict
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  )
 
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  use_cache: Optional[bool] = None,
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  output_attentions: Optional[bool] = False,
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  output_hidden_states: Optional[bool] = False,
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+ return_dict: Optional[bool] = None,
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  **kwargs,
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  ) -> Union[Tuple, CausalLMOutputWithPast]:
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  return_dict = (