code: def _create_dla(variant, pretrained=False, **kwargs):
      return build_model_with_cfg(
          DLA,
          variant,
          pretrained,
          pretrained_strict=False,
          feature_cfg=dict(out_indices=(1, 2, 3, 4, 5)),
          **kwargs,
      )
  
imports: import math
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 1 for calling a global function with example usage: _create_dla(variant, pretrained) and returns: build_model_with_cfg