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fix loading valuehead

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hiyouga
2023-06-13 11:13:06 +08:00
parent 531a3764d9
commit 875e8e2349
2 changed files with 18 additions and 11 deletions
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14
src/utils/other.py
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@@ -126,21 +126,27 @@ def get_state_dict(model: torch.nn.Module) -> Dict[str, torch.Tensor]: # get sta
return filtered_state_dict
def load_trainable_params(model: torch.nn.Module, checkpoint_dir: os.PathLike) -> None:
def load_trainable_params(model: torch.nn.Module, checkpoint_dir: os.PathLike) -> bool:
weights_file = os.path.join(checkpoint_dir, WEIGHTS_NAME)
assert os.path.exists(weights_file), f"Provided path ({checkpoint_dir}) does not contain the pretrained weights."
if not os.path.exists(weights_file):
logger.warning("Provided path ({}) does not contain pre-trained weights.".format(checkpoint_dir))
return False
model_state_dict = torch.load(weights_file, map_location="cpu")
model.load_state_dict(model_state_dict, strict=False) # skip missing keys
return True
def load_valuehead_params(model: torch.nn.Module, checkpoint_dir: os.PathLike) -> None:
def load_valuehead_params(model: torch.nn.Module, checkpoint_dir: os.PathLike) -> bool:
valuehead_file = os.path.join(checkpoint_dir, VALUE_HEAD_FILE_NAME)
assert os.path.exists(valuehead_file), f"Provided path ({checkpoint_dir}) does not contain the valuehead weights."
if not os.path.exists(valuehead_file):
logger.warning("Provided path ({}) does not contain valuehead weights.".format(checkpoint_dir))
return False
valuehead_state_dict = torch.load(valuehead_file, map_location="cpu")
model.register_buffer("reward_head_weight", valuehead_state_dict["summary.weight"])
model.register_buffer("reward_head_bias", valuehead_state_dict["summary.bias"])
model.register_buffer("default_head_weight", torch.zeros_like(valuehead_state_dict["summary.weight"]))
model.register_buffer("default_head_bias", torch.zeros_like(valuehead_state_dict["summary.bias"]))
return True
def smooth(scalars: List[float], weight: Optional[float] = 0.9) -> List[float]: