class_docstr: NN definition for fcn_resnet101 i.e. FCN with resnet 101 as backend
code: def __init__(self, num_classes=21, **kwargs):
      backbone = resnet.resnet101(
          pretrained=True,
          replace_stride_with_dilation=[False, True, True],
      )
      return_layers = {"layer4": "out"}
      return_layers["layer3"] = "aux"
      backbone = IntermediateLayerGetter(
          backbone, return_layers=return_layers
      )
  
      inplanes = 1024
      aux_classifier = FCNHead(inplanes, num_classes)
      inplanes = 2048
      classifier = FCNHead(inplanes, num_classes)
  
      super(FCNImageSegmenter, self).__init__(
          backbone, classifier, aux_classifier
      )
  
imports: from torchvision.models.segmentation.fcn import FCN
  from torchvision.models import resnet
  from intermediate_layer_getter import IntermediateLayerGetter
  from fcn import FCNHead
label_desc: Use image node_id 1 to create a new FCNImageSegmenter object from inherited base classes: FCN with example: obj = FCNImageSegmenter(num_classes)