seg/models/utils/load_checkpoint.py

from mmengine.runner.checkpoint import CheckpointLoader


def load_checkpoint_with_prefix(filename, prefix=None, map_location='cpu', logger='current'):
    """Load partial pretrained model with specific prefix.

    Args:
        prefix (str): The prefix of sub-module.
        filename (str): Accept local filepath, URL, ``torchvision://xxx``,
            ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
            details.
        map_location (str | None): Same as :func:`torch.load`.
            Defaults to None.
        logger: logger

    Returns:
        dict or OrderedDict: The loaded checkpoint.
    """

    checkpoint = CheckpointLoader.load_checkpoint(filename, map_location=map_location, logger=logger)

    if 'state_dict' in checkpoint:
        state_dict = checkpoint['state_dict']
    else:
        state_dict = checkpoint
    if not prefix:
        return state_dict
    if not prefix.endswith('.'):
        prefix += '.'
    prefix_len = len(prefix)

    state_dict = {
        k[prefix_len:]: v
        for k, v in state_dict.items() if k.startswith(prefix)
    }

    assert state_dict, f'{prefix} is not in the pretrained model'
    return state_dict