init param

游雁

2024-02-28 5d916b5a8a68fa85e79f16c2df5c45871b5298e6

init param

 funasr/train_utils/load_pretrained_model.py

@@ -145,45 +145,3 @@
            
    flag = obj.load_state_dict(dst_state, strict=False)
    # print(flag)

# def load_pretrained_model(
#     path: str,
#     model: torch.nn.Module,
#     ignore_init_mismatch: bool,
#     map_location: str = "cpu",
#     oss_bucket=None,
#     scope_map=None,
#     excludes=None,
# ):
#     """Load a model state and set it to the model.
#
#     Args:
#         init_param: <file_path>:<src_key>:<dst_key>:<exclude_Keys>
#
#     Examples:
#
#     """
#
#     obj = model
#
#     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)
#     src_state = src_state["model"] if "model" in src_state else src_state
#
#     if excludes is not None:
#         for e in excludes.split(","):
#             src_state = {k: v for k, v in src_state.items() if not k.startswith(e)}
#
#     dst_state = obj.state_dict()
#     src_state = assigment_scope_map(dst_state, src_state, scope_map)
#
#     if ignore_init_mismatch:
#         src_state = filter_state_dict(dst_state, src_state)
#
#     logging.debug("Loaded src_state keys: {}".format(src_state.keys()))
#     logging.debug("Loaded dst_state keys: {}".format(dst_state.keys()))
#     dst_state.update(src_state)
#     obj.load_state_dict(dst_state, strict=True)