code: def wide_resnet101_2(
      *,
      weights: Optional[Wide_ResNet101_2_Weights] = None,
      progress: bool = True,
      **kwargs: Any,
  ) -> ResNet:
      """Wide ResNet-101-2 model from
      `Wide Residual Networks <https://arxiv.org/abs/1605.07146>`_.
  
      The model is the same as ResNet except for the bottleneck number of channels
      which is twice larger in every block. The number of channels in outer 1x1
      convolutions is the same, e.g. last block in ResNet-101 has 2048-512-2048
      channels, and in Wide ResNet-101-2 has 2048-1024-2048.
  
      Args:
          weights (:class:`~torchvision.models.Wide_ResNet101_2_Weights`, optional): The
              pretrained weights to use. See
              :class:`~torchvision.models.Wide_ResNet101_2_Weights` below for
              more details, and possible values. By default, no pre-trained
              weights are used.
          progress (bool, optional): If True, displays a progress bar of the
              download to stderr. Default is True.
          **kwargs: parameters passed to the ``torchvision.models.resnet.ResNet``
              base class. Please refer to the `source code
              <https://github.com/pytorch/vision/blob/main/torchvision/models/resnet.py>`_
              for more details about this class.
      .. autoclass:: torchvision.models.Wide_ResNet101_2_Weights
          :members:
      """
      weights = Wide_ResNet101_2_Weights.verify(weights)
  
      _ovewrite_named_param(kwargs, "width_per_group", 64 * 2)
      return _resnet(
          Bottleneck, [3, 4, 23, 3], weights, progress, **kwargs
      )
  
imports: from functools import partial
  from typing import Any, Callable, List, Optional, Type, Union
  import torch
  import torch.nn
  from torch import Tensor
  from ..transforms._presets import ImageClassification
  from ..utils import _log_api_usage_once
  from ._api import register_model, Weights, WeightsEnum
  from ._meta import _IMAGENET_CATEGORIES
  from ._utils import _ovewrite_named_param, handle_legacy_interface
label_desc: Use image node_id 13 for calling a global function with example usage: wide_resnet101_2() and returns: _resnet