code: def _cfg(url="", **kwargs):
      return {
          "url": url,
          "num_classes": 1000,
          "input_size": (3, 224, 224),
          "pool_size": (7, 7),
          "crop_pct": 0.95,
          "interpolation": "bicubic",
          "mean": IMAGENET_DEFAULT_MEAN,
          "std": IMAGENET_DEFAULT_STD,
          "first_conv": "stem.conv1.c",
          "classifier": ("head.head.l", "head.head_dist.l"),
          **kwargs,
      }
  
imports: import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from ._registry import register_model, generate_default_cfgs
  from ._builder import build_model_with_cfg
  from timm.layers import SqueezeExcite, trunc_normal_, to_ntuple, to_2tuple
  from ._manipulate import checkpoint_seq
  import torch
label_desc: Use image node_id 1 for calling a global function with example usage: _cfg(url) and returns: dict