parameters: (pretrained=False, **kwargs)
return_statement: return model
docstring: Constructs a ResNet-101 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
docstring_summary: Constructs a ResNet-101 model.
docstring_tokens: Constructs a ResNet - 101 model .
function: def resnet101(pretrained=False, **kwargs):
      """Constructs a ResNet-101 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
      """
      model = ResNet(Bottleneck, [3, 4, 23, 3], **kwargs)
      if pretrained:
          model.load_state_dict(model_zoo.load_url(model_urls['resnet101']))
      return model
function_tokens: def resnet101 ( pretrained = False , * * kwargs ) : model = ResNet ( Bottleneck , [ 3 , 4 , 23 , 3 ] , * * kwargs ) if pretrained : model . load_state_dict ( model_zoo . load_url ( model_urls [ 'resnet101' ] ) ) return model