code: def _cfg(url="", **kwargs):
      return {
          "url": url,
          "num_classes": 1000,
          "mean": IMAGENET_DEFAULT_MEAN,
          "std": IMAGENET_DEFAULT_STD,
          "first_conv": "patch_embed.conv1.conv",
          "classifier": "head.linear",
          "fixed_input_size": True,
          "pool_size": (4, 4),
          **kwargs,
      }
  
imports: import itertools
  from collections import OrderedDict
  from typing import Dict
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import SqueezeExcite, SelectAdaptivePool2d, trunc_normal_, _assert
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 for calling a global function with example usage: _cfg(url) and returns: dict