code: def _cfg(url="", **kwargs):
      return {
          "url": url,
          "num_classes": 1000,
          "input_size": (3, 224, 224),
          "pool_size": None,
          "crop_pct": 0.9,
          "interpolation": "bicubic",
          "fixed_input_size": True,
          "mean": (0.5, 0.5, 0.5),
          "std": (0.5, 0.5, 0.5),
          "first_conv": "patch_embed.backbone.stem.conv",
          "classifier": "head",
          **kwargs,
      }
  
imports: from functools import partial
  from typing import List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import StdConv2dSame, StdConv2d, to_2tuple, Format, nchw_to
  from ._registry import generate_default_cfgs, register_model, register_model_deprecations
  from .resnet import resnet26d, resnet50d
  from .resnetv2 import ResNetV2, create_resnetv2_stem
  from .vision_transformer import _create_vision_transformer, VisionTransformer
label_desc: Use image node_id 3 for calling a global function with example usage: _cfg(url) and returns: dict