code: def pnasnet5large(pretrained=False, **kwargs) -> PNASNet5Large:
      r"""PNASNet-5 model architecture from the
      `"Progressive Neural Architecture Search"
      <https://arxiv.org/abs/1712.00559>`_ paper.
      """
      model_kwargs = dict(pad_type="same", **kwargs)
      return _create_pnasnet(
          "pnasnet5large", pretrained, **model_kwargs
      )
  
imports: from collections import OrderedDict
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.layers import ConvNormAct, create_conv2d, create_pool2d, create_classifier
  from ._builder import build_model_with_cfg
  from ._registry import register_model, generate_default_cfgs
label_desc: Use image node_id 2 for calling a global function with example usage: pnasnet5large(pretrained) and returns: _create_pnasnet