code: def pit_ti_distilled_224(
      pretrained=False, **kwargs
  ) -> PoolingVisionTransformer:
      model_args = dict(
          patch_size=16,
          stride=8,
          base_dims=[32, 32, 32],
          depth=[2, 6, 4],
          heads=[2, 4, 8],
          mlp_ratio=4,
          distilled=True,
      )
      return _create_pit(
          "pit_ti_distilled_224",
          pretrained,
          **dict(model_args, **kwargs),
      )
  
imports: import math
  import re
  from functools import partial
  from typing import Sequence, Tuple
  import torch
  from torch import nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import trunc_normal_, to_2tuple, LayerNorm
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
  from .vision_transformer import Block
label_desc: Use image node_id 11 for calling a global function with example usage: pit_ti_distilled_224(pretrained) and returns: _create_pit