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fix #196

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Former-commit-id: 925a790bc9507c4d23af275a5abfb149959dbdcb
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hiyouga 2023-07-19 17:35:38 +08:00
parent 2e0342dc54
commit 1a23cb2578
1 changed files with 25 additions and 12 deletions
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37
src/llmtuner/tuner/sft/trainer.py
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@ -36,31 +36,44 @@ class Seq2SeqPeftTrainer(PeftTrainer):
inputs["labels"] = self._pad_tensors_to_target_len(inputs["labels"], inputs["input_ids"]) inputs["labels"] = self._pad_tensors_to_target_len(inputs["labels"], inputs["input_ids"])
if label_len > prompt_len: if label_len > prompt_len:
inputs["input_ids"] = self._pad_tensors_to_target_len(inputs["input_ids"], inputs["labels"]) inputs["input_ids"] = self._pad_tensors_to_target_len(inputs["input_ids"], inputs["labels"])
if "attention_mask" in inputs:
inputs["attention_mask"] = self._pad_tensors_to_target_len(
inputs["attention_mask"], inputs["labels"], pad_token_id=0
)
if "position_ids" in inputs:
inputs["position_ids"] = self._pad_tensors_to_target_len(
inputs["position_ids"], inputs["labels"], pad_token_id=0
)
loss, generated_tokens, labels = super().prediction_step( loss, generated_tokens, labels = super().prediction_step(
model, inputs, prediction_loss_only=prediction_loss_only, ignore_keys=ignore_keys model, inputs, prediction_loss_only=prediction_loss_only, ignore_keys=ignore_keys
) )
generated_tokens = generated_tokens[:, max(prompt_len, label_len):] if generated_tokens is not None else None generated_tokens = (
generated_tokens[:, max(prompt_len, label_len):] if generated_tokens is not None else None
)
return (loss, generated_tokens, labels) return (loss, generated_tokens, labels)
def _pad_tensors_to_target_len(self, src_tensor: torch.Tensor, tgt_tensor: torch.Tensor) -> torch.Tensor: def _pad_tensors_to_target_len(
self,
src_tensor: torch.Tensor,
tgt_tensor: torch.Tensor,
pad_token_id: Optional[int] = None
) -> torch.Tensor:
r""" r"""
Pads the tensor to the same length as the target tensor. Pads the tensor to the same length as the target tensor.
Should only be called when predict_with_generate=True. Should only be called when predict_with_generate=True.
""" """
if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"): if pad_token_id is None:
assert self.tokenizer.padding_side == "left", "This method only accepts left-padded tensor." if self.tokenizer is not None and hasattr(self.tokenizer, "pad_token_id"):
# If PAD token is not defined at least EOS token has to be defined assert self.tokenizer.padding_side == "left", "This method only accepts left-padded tensor."
pad_token_id = ( pad_token_id = self.tokenizer.pad_token_id
self.tokenizer.pad_token_id if self.tokenizer.pad_token_id is not None else self.tokenizer.eos_token_id
)
else:
if self.model.config.pad_token_id is not None:
pad_token_id = self.model.config.pad_token_id
else: else:
raise ValueError("Pad_token_id must be set in the configuration of the model, in order to pad tensors") if self.model.config.pad_token_id is not None:
pad_token_id = self.model.config.pad_token_id
else:
raise ValueError("Pad_token_id must be set in the configuration of the model.")
padded_tensor = pad_token_id * torch.ones_like(tgt_tensor) padded_tensor = pad_token_id * torch.ones_like(tgt_tensor)
padded_tensor[:, -src_tensor.shape[-1]:] = src_tensor # adopt left-padding padded_tensor[:, -src_tensor.shape[-1]:] = src_tensor # adopt left-padding