code: def _filter_kwargs(kwargs, names):
      if not kwargs or not names:
          return
      for n in names:
          kwargs.pop(n, None)
  
imports: import dataclasses
  import logging
  import os
  from copy import deepcopy
  from typing import Optional, Dict, Callable, Any, Tuple
  from torch import nn
  from torch.hub import load_state_dict_from_url
  from timm.models._features import FeatureListNet, FeatureHookNet
  from timm.models._features_fx import FeatureGraphNet
  from timm.models._helpers import load_state_dict
  from timm.models._hub import has_hf_hub, download_cached_file, check_cached_file, load_state_dict_from_hf
  from timm.models._manipulate import adapt_input_conv
  from timm.models._pretrained import PretrainedCfg
  from timm.models._prune import adapt_model_from_file
  from timm.models._registry import get_pretrained_cfg
label_desc: Use image node_id 7 for calling a global function with example usage: _filter_kwargs(kwargs, names) without return types