code: def _create_dpn(variant, pretrained=False, **kwargs):
      return build_model_with_cfg(
          DPN,
          variant,
          pretrained,
          feature_cfg=dict(
              feature_concat=True, flatten_sequential=True
          ),
          **kwargs,
      )
  
imports: from collections import OrderedDict
  from functools import partial
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DPN_MEAN, IMAGENET_DPN_STD, IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import BatchNormAct2d, ConvNormAct, create_conv2d, create_classifier, get_norm_act_layer
  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_dpn(variant, pretrained) and returns: build_model_with_cfg