Rename 'res' in line 514 to avoid with naming conflict with line 365

liugz18

2024-07-18 d80ac2fd2df4e7fb8a28acfa512bb11472b5cc99

 funasr/train_utils/load_pretrained_model.py

@@ -7,99 +7,96 @@
import torch
import torch.nn
import torch.optim


def filter_state_dict(
   dst_state: Dict[str, Union[float, torch.Tensor]],
   src_state: Dict[str, Union[float, torch.Tensor]],
):
   """Filter name, size mismatch instances between dicts.

   Args:
      dst_state: reference state dict for filtering
      src_state: target state dict for filtering

   """
   match_state = {}
   for key, value in src_state.items():
      if key in dst_state and (dst_state[key].size() == src_state[key].size()):
         match_state[key] = value
      else:
         if key not in dst_state:
            logging.warning(
               f"Filter out {key} from pretrained dict"
               + " because of name not found in target dict"
            )
         else:
            logging.warning(
               f"Filter out {key} from pretrained dict"
               + " because of size mismatch"
               + f"({dst_state[key].size()}-{src_state[key].size()})"
            )
   return match_state
import pdb


def load_pretrained_model(
   path: str,
   model: torch.nn.Module,
   ignore_init_mismatch: bool=True,
   map_location: str = "cpu",
   oss_bucket=None,
   scope_map="module.:none",
   excludes=None,
   ignore_mismatch=False,
   **kwargs,
    path: str,
    model: torch.nn.Module,
    ignore_init_mismatch: bool = True,
    map_location: str = "cpu",
    oss_bucket=None,
    scope_map=[],
    excludes=None,
    **kwargs,
):
   """Load a model state and set it to the model.
    """Load a model state and set it to the model.

   Args:
      init_param: <file_path>:<src_key>:<dst_key>:<exclude_Keys>
    Args:
            init_param: <file_path>:<src_key>:<dst_key>:<exclude_Keys>

   Examples:
    Examples:

   """
	
   obj = model
   dst_state = obj.state_dict()
	
   print(f"ckpt: {path}")
   if oss_bucket is None:
      src_state = torch.load(path, map_location=map_location)
   else:
      buffer = BytesIO(oss_bucket.get_object(path).read())
      src_state = torch.load(buffer, map_location=map_location)
   if "state_dict" in src_state:
      src_state = src_state["state_dict"]
	
   src_state = src_state["model"] if "model" in src_state else src_state
	
   if isinstance(scope_map, str):
      scope_map = scope_map.split(",")
	
   for k in dst_state.keys():
		
      k_src = k
    """

      if scope_map is not None:
         src_prefix = ""
         dst_prefix = ""
         for i in range(0, len(scope_map), 2):
            src_prefix = scope_map[i] if scope_map[i].lower() != "none" else ""
            dst_prefix = scope_map[i+1] if scope_map[i+1].lower() != "none" else ""
    obj = model
    dst_state = obj.state_dict()

            if k.startswith(dst_prefix) and k.replace(dst_prefix, src_prefix) in src_state.keys():
               k_src = k.replace(dst_prefix, src_prefix)
               print(f"init param, map: {k} from {k_src} in ckpt")
					
      if k_src in src_state.keys():
         if ignore_init_mismatch and dst_state[k].shape != src_state[k_src].shape:
            print(f"ignore_mismatch:{ignore_mismatch}, dst: {k, dst_state[k].shape}, src: {k_src, src_state[k_src].shape}")
         else:
            dst_state[k] = src_state[k_src]
    logging.info(f"ckpt: {path}")

    if oss_bucket is None:
        src_state = torch.load(path, map_location=map_location)
    else:
        buffer = BytesIO(oss_bucket.get_object(path).read())
        src_state = torch.load(buffer, map_location=map_location)

      else:
         print(f"Warning, miss key in ckpt: {k}, mapped: {k_src}")
			
   flag = obj.load_state_dict(dst_state, strict=True)
   # print(flag)
    src_state = src_state["state_dict"] if "state_dict" in src_state else src_state
    src_state = src_state["model_state_dict"] if "model_state_dict" in src_state else src_state
    src_state = src_state["model"] if "model" in src_state else src_state

    if isinstance(scope_map, str):
        scope_map = scope_map.split(",")
    scope_map += ["module.", "None"]
    logging.info(f"scope_map: {scope_map}")

    if excludes is not None:
        if isinstance(excludes, str):
            excludes = excludes.split(",")

    logging.info(f"excludes: {excludes}")

    for k in dst_state.keys():
        excludes_flag = False
        if excludes is not None:
            for k_ex in excludes:
                if k.startswith(k_ex):
                    logging.info(f"key: {k} matching: {k_ex}, excluded")
                    excludes_flag = True
                    break
        if excludes_flag:
            continue

        k_src = k

        if scope_map is not None:
            src_prefix = ""
            dst_prefix = ""
            for i in range(0, len(scope_map), 2):
                src_prefix = scope_map[i] if scope_map[i].lower() != "none" else ""
                dst_prefix = scope_map[i + 1] if scope_map[i + 1].lower() != "none" else ""

                if dst_prefix == "" and (src_prefix + k) in src_state.keys():
                    k_src = src_prefix + k
                    if not k_src.startswith("module."):
                        logging.info(f"init param, map: {k} from {k_src} in ckpt")
                elif (
                    k.startswith(dst_prefix)
                    and k.replace(dst_prefix, src_prefix, 1) in src_state.keys()
                ):
                    k_src = k.replace(dst_prefix, src_prefix, 1)
                    if not k_src.startswith("module."):
                        logging.info(f"init param, map: {k} from {k_src} in ckpt")

        if k_src in src_state.keys():
            if ignore_init_mismatch and dst_state[k].shape != src_state[k_src].shape:
                logging.info(
                    f"ignore_init_mismatch:{ignore_init_mismatch}, dst: {k, dst_state[k].shape}, src: {k_src, src_state[k_src].shape}"
                )
            else:
                dst_state[k] = src_state[k_src]

        else:
            print(f"Warning, miss key in ckpt: {k}, {path}")

    flag = obj.load_state_dict(dst_state, strict=True)
    logging.info(f"Loading ckpt: {path}, status: {flag}")