code: def wide_resnet50_6(pretrained=False, progress=True, **kwargs):
      r"""Wide ResNet-50-6 model
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
          progress (bool): If True, displays a progress bar of the download to stderr
      """
      kwargs["width_per_group"] = 64 * 6
      return _resnet(
          "wide_resnet50_6",
          Bottleneck,
          [3, 4, 6, 3],
          pretrained,
          progress,
          **kwargs,
      )
  
imports: import torch
  import torch.nn
  from torch.hub import load_state_dict_from_url
  from ..tools.custom_modules import SequentialWithArgs, FakeReLU
label_desc: Use image node_id 15 for calling a global function with example usage: wide_resnet50_6(pretrained, progress) and returns: _resnet