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",
          "mean": IMAGENET_DEFAULT_MEAN,
          "std": IMAGENET_DEFAULT_STD,
          "first_conv": "patch_embed.proj",
          "classifier": "head",
          **kwargs,
      }
  
imports: import logging
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils
  import torch.utils.checkpoint
  from einops import rearrange
  from fairscale.nn.checkpoint.checkpoint_activations import checkpoint_wrapper
  from .helpers import load_pretrained, load_pretrained_imagenet, load_pretrained_kinetics
  from .vit_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, DropPath, to_2tuple, trunc_normal_
label_desc: Use image node_id 1 for calling a global function with example usage: _cfg(url) and returns: dict