code: def _create_nest(variant, pretrained=False, **kwargs):
      model = build_model_with_cfg(
          Nest,
          variant,
          pretrained,
          feature_cfg=dict(
              out_indices=(0, 1, 2), flatten_sequential=True
          ),
          pretrained_filter_fn=checkpoint_filter_fn,
          **kwargs,
      )
  
      return model
  
imports: import collections.abc
  import logging
  import math
  from functools import partial
  import torch
  import torch.nn.functional
  from torch import nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import PatchEmbed, Mlp, DropPath, create_classifier, trunc_normal_, _assert
  from timm.layers import create_conv2d, create_pool2d, to_ntuple, use_fused_attn, LayerNorm
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_function
  from ._manipulate import checkpoint_seq, named_apply
  from ._registry import register_model, generate_default_cfgs, register_model_deprecations
label_desc: Use image node_id 6 for calling a global function with example usage: _create_nest(variant, pretrained) and returns: model