def __init__(self, model_path, prefix=None, ignore=()):
        """
        Args:
            model_path (str): a model name (model-xxxx) or a ``checkpoint`` file.
            prefix (str): during restore, add a ``prefix/`` for every variable in this checkpoint.
            ignore (tuple[str]): tensor names that should be ignored during loading, e.g. learning-rate
        """
        if model_path.endswith('.npy') or model_path.endswith('.npz'):
            logger.warn("SaverRestore expect a TF checkpoint, but got a model path '{}'.".format(model_path) +
                        " To load from a dict, use 'DictRestore'.")
        model_path = get_checkpoint_path(model_path)
        self.path = model_path  # attribute used by AutoResumeTrainConfig!
        self.prefix = prefix
        self.ignore = [i if i.endswith(':0') else i + ':0' for i in ignore]

        Args:
            model_path (str): a model name (model-xxxx) or a ``checkpoint`` file.
            prefix (str): during restore, add a ``prefix/`` for every variable in this checkpoint.
            ignore (tuple[str]): tensor names that should be ignored during loading, e.g. learning-rate
        
tensorpack/tfutils/sessinit.py