code: def model(
      num_classes: int,
      backbone: Optional[TorchvisionBackboneConfig] = None,
      remove_internal_transforms: bool = True,
      **faster_rcnn_kwargs,
  ) -> nn.Module:
      """FasterRCNN model implemented by torchvision.
  
      # Arguments
          num_classes: Number of classes.
          backbone: Backbone model to use. Defaults to a resnet50_fpn model.
          remove_internal_transforms: The torchvision model internally applies transforms
          like resizing and normalization, but we already do this at the `Dataset` level,
          so it's safe to remove those internal transforms.
          pretrained: Argument passed to `fastercnn_resnet50_fpn` if `backbone is None`.
          By default it is set to True: this is generally used when training a new model (transfer learning).
          `pretrained = False`  is used during inference (prediction) for cases where the users have their own pretrained weights.
          **faster_rcnn_kwargs: Keyword arguments that internally are going to be passed to
          `torchvision.models.detection.faster_rcnn.FastRCNN`.
  
      # Returns
          A Pytorch `nn.Module`.
      """
      if backbone is None:
          model = fasterrcnn_resnet50_fpn(
              pretrained=True,
              pretrained_backbone=True,
              **faster_rcnn_kwargs,
          )
  
          in_features = (
              model.roi_heads.box_predictor.cls_score.in_features
          )
          model.roi_heads.box_predictor = FastRCNNPredictor(
              in_features, num_classes
          )
  
          resnet_fpn.patch_param_groups(model.backbone)
      else:
          model = FasterRCNN(
              backbone.backbone,
              num_classes=num_classes,
              **faster_rcnn_kwargs,
          )
  
      patch_rcnn_param_groups(model=model)
  
      if remove_internal_transforms:
          remove_internal_model_transforms(model)
  
      return model
  
imports: from icevision.imports import *
  from icevision.models.torchvision.faster_rcnn.backbones import resnet_fpn_configs
  from icevision.models.torchvision.utils import *
  from icevision.models.torchvision.backbone_config import TorchvisionBackboneConfig
  from torchvision.models.detection.faster_rcnn import fasterrcnn_resnet50_fpn, FasterRCNN, FastRCNNPredictor
label_desc: Use image node_id 1 for calling a global function with example usage: model(num_classes, backbone, remove_internal_transforms) and returns: model