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": OPENAI_CLIP_MEAN,
          "std": OPENAI_CLIP_STD,
          "first_conv": "patch_embed.proj",
          "classifier": "head",
          "license": "mit",
          **kwargs,
      }
  
imports: import math
  from typing import Callable, Optional, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, OPENAI_CLIP_MEAN, OPENAI_CLIP_STD
  from timm.layers import PatchEmbed, Mlp, GluMlp, SwiGLU, LayerNorm, DropPath, PatchDropout, RotaryEmbeddingCat, apply_rot_embed_cat, apply_keep_indices_nlc, trunc_normal_, resample_patch_embed, resample_abs_pos_embed, to_2tuple, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._registry import generate_default_cfgs, register_model
label_desc: Use image node_id 3 for calling a global function with example usage: _cfg(url) and returns: dict