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https://github.com/hiyouga/LLaMA-Factory.git
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parent
2e0342dc54
commit
1a23cb2578
@ -36,31 +36,44 @@ class Seq2SeqPeftTrainer(PeftTrainer):
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inputs["labels"] = self._pad_tensors_to_target_len(inputs["labels"], inputs["input_ids"])
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if label_len > prompt_len:
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inputs["input_ids"] = self._pad_tensors_to_target_len(inputs["input_ids"], inputs["labels"])
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if "attention_mask" in inputs:
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inputs["attention_mask"] = self._pad_tensors_to_target_len(
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inputs["attention_mask"], inputs["labels"], pad_token_id=0
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)
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if "position_ids" in inputs:
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inputs["position_ids"] = self._pad_tensors_to_target_len(
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inputs["position_ids"], inputs["labels"], pad_token_id=0
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)
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loss, generated_tokens, labels = super().prediction_step(
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model, inputs, prediction_loss_only=prediction_loss_only, ignore_keys=ignore_keys
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)
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generated_tokens = generated_tokens[:, max(prompt_len, label_len):] if generated_tokens is not None else None
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generated_tokens = (
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generated_tokens[:, max(prompt_len, label_len):] if generated_tokens is not None else None
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)
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return (loss, generated_tokens, labels)
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def _pad_tensors_to_target_len(self, src_tensor: torch.Tensor, tgt_tensor: torch.Tensor) -> torch.Tensor:
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def _pad_tensors_to_target_len(
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self,
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src_tensor: torch.Tensor,
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tgt_tensor: torch.Tensor,
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pad_token_id: Optional[int] = None
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) -> torch.Tensor:
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r"""
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Pads the tensor to the same length as the target tensor.
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Should only be called when predict_with_generate=True.
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"""
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if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"):
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assert self.tokenizer.padding_side == "left", "This method only accepts left-padded tensor."
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# If PAD token is not defined at least EOS token has to be defined
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pad_token_id = (
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self.tokenizer.pad_token_id if self.tokenizer.pad_token_id is not None else self.tokenizer.eos_token_id
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)
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else:
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if self.model.config.pad_token_id is not None:
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pad_token_id = self.model.config.pad_token_id
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if pad_token_id is None:
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if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"):
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assert self.tokenizer.padding_side == "left", "This method only accepts left-padded tensor."
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pad_token_id = self.tokenizer.pad_token_id
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else:
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raise ValueError("Pad_token_id must be set in the configuration of the model, in order to pad tensors")
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if self.model.config.pad_token_id is not None:
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pad_token_id = self.model.config.pad_token_id
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else:
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raise ValueError("Pad_token_id must be set in the configuration of the model.")
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padded_tensor = pad_token_id * torch.ones_like(tgt_tensor)
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padded_tensor[:, -src_tensor.shape[-1]:] = src_tensor # adopt left-padding
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