游雁
2024-02-28 811ebea5b0d4b112a494b3ee9a63c4e35098dbf5
funasr/train_utils/load_pretrained_model.py
@@ -38,52 +38,17 @@
            )
   return match_state
def assigment_scope_map(dst_state: dict, src_state: dict, scope_map: str=None):
   """Compute the union of the current variables and checkpoint variables."""
   import collections
   import re
   # current model variables
   name_to_variable = collections.OrderedDict()
   for name, var in dst_state.items():
      name_to_variable[name] = var
   scope_map_num = 0
   if scope_map is not None:
      scope_map = scope_map.split(",")
      scope_map_num = len(scope_map) // 2
      for scope_map_idx in range(scope_map_num):
         scope_map_id = scope_map_idx * 2
         logging.info('assignment_map from scope {} to {}'.format(scope_map[scope_map_id], scope_map[scope_map_id+1]))
   assignment_map = {}
   for name, var in src_state.items():
      if scope_map:
         for scope_map_idx in range(scope_map_num):
            scope_map_id = scope_map_idx * 2
            try:
               idx = name.index(scope_map[scope_map_id])
               new_name = scope_map[scope_map_id+1] + name[idx + len(scope_map[scope_map_id]):]
               if new_name in name_to_variable:
                  assignment_map[name] = var
            except:
               continue
      else:
         if name in name_to_variable:
            assignment_map[name] = var
   return assignment_map
def load_pretrained_model(
   path: str,
   model: torch.nn.Module,
   ignore_init_mismatch: bool,
   ignore_init_mismatch: bool=True,
   map_location: str = "cpu",
   oss_bucket=None,
   scope_map="module.:none",
   excludes=None,
   ignore_mismatch=False,
   **kwargs,
):
   """Load a model state and set it to the model.
@@ -112,10 +77,7 @@
      scope_map = scope_map.split(",")
   
   for k in dst_state.keys():
      # if not k.startswith("module.") and "module." + k in src_state.keys():
      #    k_ddp = "module." + k
      # else:
      #    k_ddp = k
      k_src = k
      if scope_map is not None:
@@ -130,18 +92,14 @@
               print(f"init param, map: {k} from {k_src} in ckpt")
               
      if k_src in src_state.keys():
         dst_state[k] = src_state[k_src]
      # if k_ddp.startswith("audio_encoder"):
      #    if k_ddp.replace("audio_encoder", "encoder.model") in src_state.keys():
      #       k_ddp = k_ddp.replace("audio_encoder", "encoder.model")
      # if k_ddp.startswith("adaptor"):
      #    if k_ddp.replace("adaptor", "encoder_projector") in src_state.keys():
      #       k_ddp = k_ddp.replace("adaptor", "encoder_projector")
      # if k_ddp in src_state:
      #    dst_state[k] = src_state[k_ddp]
         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]
      else:
         print(f"Warning, miss key in ckpt: {k}, mapped: {k_src}")
         
   flag = obj.load_state_dict(dst_state, strict=False)
   flag = obj.load_state_dict(dst_state, strict=True)
   # print(flag)