code: def _cfg(url="", **kwargs):
      return {
          "url": url,
          "num_classes": 1000,
          "input_size": (3, 224, 224),
          "pool_size": (7, 7),
          "crop_pct": 0.875,
          "interpolation": "bicubic",
          "mean": IMAGENET_DEFAULT_MEAN,
          "std": IMAGENET_DEFAULT_STD,
          "first_conv": "stem.conv1",
          "classifier": "head.fc",
          "fixed_input_size": True,
          **kwargs,
      }
  
imports: import math
  from functools import partial
  from typing import Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.utils.checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import DropPath, to_2tuple, to_ntuple, Mlp, ClassifierHead, LayerNorm2d, get_attn, get_act_layer, get_norm_layer, RelPosBias, _assert
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_function
  from ._manipulate import named_apply
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 4 for calling a global function with example usage: _cfg(url) and returns: dict