code: def mix_vit(
      pretrained: bool = False, *, in_channels: int = 3
  ) -> MixViT:
      if pretrained:
          raise ValueError("`MixViT` does not support `pretrained`")
      return MixViT(
          in_channels,
          [64, 128, 320, 512],
          num_heads_list=[1, 2, 5, 8],
          feedforward_dim_ratios=[4.0] * 4,
          num_layers_list=[3, 4, 18, 3],
          reduction_ratios=[8, 4, 2, 1],
      )
  
file_path: carefree-learn/cflearn/models/cv/encoder/backbone/models/transformer.py
imports: import torch
  from torch import nn
  from typing import Any
  from typing import List
  from typing import Optional
  from cftool.misc import shallow_copy_dict
  from ..register import register_backbone
  from ......modules.blocks import ImgToPatches
  from ......modules.blocks import MixedStackedEncoder
label_desc: Use image node_id 1 for calling a global function with example usage: mix_vit(pretrained) and returns: MixViT