code: def _make_pretrained_deitb16_distil_384(
      pretrained, use_readout="ignore", hooks=None
  ):
      model = timm.create_model(
          "vit_deit_base_distilled_patch16_384", pretrained=pretrained
      )
  
      hooks = [2, 5, 8, 11] if hooks == None else hooks
      return _make_vit_b16_backbone(
          model,
          features=[96, 192, 384, 768],
          hooks=hooks,
          use_readout=use_readout,
          start_index=2,
      )
  
imports: import torch
  import torch.nn
  import timm
  import types
  import math
  import torch.nn.functional
label_desc: Use image node_id 10 for calling a global function with example usage: _make_pretrained_deitb16_distil_384(pretrained, use_readout, hooks) and returns: _make_vit_b16_backbone