class_docstr: An abstract class providing basic methods for saving and loading weights of a model. Extend this class to build
  custom module weight loaders.
class_docstr_tok: ["An","abstract","class","providing","basic","methods","for","saving","and","loading","weights","of","a","model",".","Extend","this","class","to","build","custom","module","weight","loaders","."]
docstr: The callable returned by this method is used to extract the module weights to be saved or loaded based on their
  names.
  
  Args:
      name (str): An identifier of the weights to be saved.
  
  Returns:
      Callable[str, bool]: A function that takes the fully qualified name of a module parameter and returns a
      boolean value that specifies whether this parameter should be extracted.
code: def filter_func(self, name: str) -> Callable[[str], bool]:
      """
      The callable returned by this method is used to extract the module weights to be saved or loaded based on their
      names.
  
      Args:
          name (str): An identifier of the weights to be saved.
  
      Returns:
          Callable[str, bool]: A function that takes the fully qualified name of a module parameter and returns a
          boolean value that specifies whether this parameter should be extracted.
      """
      pass
  
imports: import json
  import logging
  from abc import ABC, abstractmethod
  from os import mkdir
  from os.path import exists, isdir, isfile, join
  from typing import Callable, Mapping, Sequence, Tuple
  import torch
  from .configuration import AdapterConfig, build_full_config
  from .head_utils import STATIC_TO_FLEX_HEAD_MAP, get_head_config_and_rename_list
  from .utils import ACTIVATION_RENAME, ADAPTERFUSION_CONFIG_NAME, ADAPTERFUSION_WEIGHTS_NAME, CONFIG_NAME, HEAD_CONFIG_NAME, HEAD_WEIGHTS_NAME, WEIGHTS_NAME, AdapterType, resolve_adapter_path
label_desc: Use image node_id 2 for calling the WeightsLoader obj's underlying member method code with example usage: obj.filter_func(name) without return types