code: def _create_inception_next(variant, pretrained=False, **kwargs):
      model = build_model_with_cfg(
          MetaNeXt,
          variant,
          pretrained,
          feature_cfg=dict(
              out_indices=(0, 1, 2, 3), flatten_sequential=True
          ),
          **kwargs,
      )
      return model
  
imports: from functools import partial
  import torch
  import torch.nn
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import trunc_normal_, DropPath, to_2tuple, get_padding, SelectAdaptivePool2d
  from ._builder import build_model_with_cfg
  from ._manipulate import checkpoint_seq
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling a global function with example usage: _create_inception_next(variant, pretrained) and returns: model