code: def _cfg(url="", **kwargs):
      return {
          "url": url,
          "num_classes": 1000,
          "input_size": (3, 299, 299),
          "pool_size": (10, 10),
          "crop_pct": 0.903,
          "interpolation": "bicubic",
          "mean": IMAGENET_INCEPTION_MEAN,
          "std": IMAGENET_INCEPTION_STD,
          "first_conv": "stem.0.conv",
          "classifier": "head.fc",
          **kwargs,
      }
  
imports: from functools import partial
  import torch
  import torch.nn
  from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
  from timm.layers import ClassifierHead, ConvNormAct, create_conv2d, get_norm_act_layer
  from timm.layers.helpers import to_3tuple
  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 2 for calling a global function with example usage: _cfg(url) and returns: dict