code: def _tiny_vit_11m(
      pretrained: bool | str = False, **kwargs: Any
  ) -> TinyViT:
      model = TinyViT(
          embed_dims=[64, 128, 256, 448],
          depths=[2, 2, 6, 2],
          num_heads=[2, 4, 8, 14],
          window_sizes=[7, 7, 14, 7],
          drop_path_rate=0.1,
          **kwargs,
      )
  
      if pretrained:
          if pretrained is True:
              pretrained = "in1k"
  
          url = {
              "in22k": (
                  "https://github.com/wkcn/TinyViT-model-zoo/releases/download/checkpoints/tiny_vit_11m_22k_distill.pth"
              ),
              "in1k": "https://github.com/wkcn/TinyViT-model-zoo/releases/download/checkpoints/tiny_vit_11m_22kto1k_distill.pth",
          }[pretrained]
          model = _load_pretrained(model, url)
  
      return model
  
imports: from __future__ import annotations
  import itertools
  import warnings
  from typing import Any, Optional
  import torch
  import torch.nn.functional
  from torch import nn
  from torch.utils import checkpoint
  from kornia.contrib.models.common import DropPath, LayerNorm2d, window_partition, window_unpartition
  from kornia.core import Module, Tensor
  from kornia.core.check import KORNIA_CHECK
label_desc: Use image node_id 4 for calling a global function with example usage: _tiny_vit_11m(pretrained) and returns: model