code: def coat_lite_tiny(pretrained=False, **kwargs) -> CoaT:
      model_cfg = dict(
          patch_size=4,
          embed_dims=[64, 128, 256, 320],
          serial_depths=[2, 2, 2, 2],
          mlp_ratios=[8, 8, 4, 4],
      )
      model = _create_coat(
          "coat_lite_tiny",
          pretrained=pretrained,
          **dict(model_cfg, **kwargs),
      )
      return model
  
imports: from functools import partial
  from typing import Tuple, List, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, to_2tuple, trunc_normal_, _assert, LayerNorm
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 9 for calling a global function with example usage: coat_lite_tiny(pretrained) and returns: model