code: def ResNet101(
      parameters, num_channel=3, num_classes=10, att=False, mean=False
  ):
      """
      Function that creates a ResNet 101 model
  
      :param parameters (list or tuple): List of parameters for the model
      :param num_channel (int): Number of channels in input specimens
      :param num_classes (int): Number of classes for classification
      :param att (bool): True if attention needs to be used
      :param mean (bool): True if mean teacher model needs to be used
      """
      model = ResNet
      if att and not mean:
          model = ResnetWithAT
      elif not att and mean:
          model = MeanResnet
      return model(
          Bottleneck,
          [3, 4, 23, 3],
          parameters,
          num_channel,
          num_classes=num_classes,
      )
  
imports: import torch.nn
  import torch.nn.functional
label_desc: Use image node_id 4 for calling a global function with example usage: ResNet101(parameters, num_channel, num_classes, att, mean) and returns: model