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kongdeqiang

2026-03-13 28ccfbfc51068a663a80764e14074df5edf2b5ba

 funasr/train_utils/load_pretrained_model.py

@@ -8,6 +8,7 @@
import torch.nn
import torch.optim
import pdb
import copy


def load_pretrained_model(
@@ -35,11 +36,12 @@
    logging.info(f"ckpt: {path}")

    if oss_bucket is None:
        src_state = torch.load(path, map_location=map_location)
        ori_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)
        ori_state = torch.load(buffer, map_location=map_location)

    src_state = copy.deepcopy(ori_state)
    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
@@ -52,14 +54,19 @@
    if excludes is not None:
        if isinstance(excludes, str):
            excludes = excludes.split(",")

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

    for k in dst_state.keys():

        for k_ex in excludes:
            if k.startswith(k_ex):
                logging.info(f"key: {{k}} matching: {k_ex}, excluded")
                continue
        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

@@ -89,9 +96,8 @@
                )
            else:
                dst_state[k] = src_state[k_src]

        else:
            logging.info(f"Warning, miss key in ckpt: {k}, mapped: {k_src}")
            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}")