code: def _create_tresnet(variant, pretrained=False, **kwargs):
      return build_model_with_cfg(
          TResNet,
          variant,
          pretrained,
          pretrained_filter_fn=checkpoint_filter_fn,
          feature_cfg=dict(
              out_indices=(1, 2, 3, 4), flatten_sequential=True
          ),
          **kwargs,
      )
  
imports: from collections import OrderedDict
  from functools import partial
  import torch
  import torch.nn
  from timm.layers import SpaceToDepth, BlurPool2d, ClassifierHead, SEModule, ConvNormActAa, ConvNormAct, DropPath
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import register_model, generate_default_cfgs, register_model_deprecations
label_desc: Use image node_id 2 for calling a global function with example usage: _create_tresnet(variant, pretrained) and returns: build_model_with_cfg