code: def fasterrcnn_mobilenet_v3_large_fpn(
      *,
      weights: Optional[
          FasterRCNN_MobileNet_V3_Large_FPN_Weights
      ] = None,
      progress: bool = True,
      num_classes: Optional[int] = None,
      weights_backbone: Optional[
          MobileNet_V3_Large_Weights
      ] = MobileNet_V3_Large_Weights.IMAGENET1K_V1,
      trainable_backbone_layers: Optional[int] = None,
      **kwargs: Any,
  ) -> FasterRCNN:
      """
      Constructs a high resolution Faster R-CNN model with a MobileNetV3-Large FPN backbone.
  
      .. betastatus:: detection module
  
      It works similarly to Faster R-CNN with ResNet-50 FPN backbone. See
      :func:`~torchvision.models.detection.fasterrcnn_resnet50_fpn` for more
      details.
  
      Example::
  
          >>> model = torchvision.models.detection.fasterrcnn_mobilenet_v3_large_fpn(weights=FasterRCNN_MobileNet_V3_Large_FPN_Weights.DEFAULT)
          >>> model.eval()
          >>> x = [torch.rand(3, 300, 400), torch.rand(3, 500, 400)]
          >>> predictions = model(x)
  
      Args:
          weights (:class:`~torchvision.models.detection.FasterRCNN_MobileNet_V3_Large_FPN_Weights`, optional): The
              pretrained weights to use. See
              :class:`~torchvision.models.detection.FasterRCNN_MobileNet_V3_Large_FPN_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.
          num_classes (int, optional): number of output classes of the model (including the background)
          weights_backbone (:class:`~torchvision.models.MobileNet_V3_Large_Weights`, optional): The
              pretrained weights for the backbone.
          trainable_backbone_layers (int, optional): number of trainable (not frozen) layers starting from
              final block. Valid values are between 0 and 6, with 6 meaning all backbone layers are
              trainable. If ``None`` is passed (the default) this value is set to 3.
          **kwargs: parameters passed to the ``torchvision.models.detection.faster_rcnn.FasterRCNN``
              base class. Please refer to the `source code
              <https://github.com/pytorch/vision/blob/main/torchvision/models/detection/faster_rcnn.py>`_
              for more details about this class.
  
      .. autoclass:: torchvision.models.detection.FasterRCNN_MobileNet_V3_Large_FPN_Weights
          :members:
      """
      weights = FasterRCNN_MobileNet_V3_Large_FPN_Weights.verify(
          weights
      )
      weights_backbone = MobileNet_V3_Large_Weights.verify(
          weights_backbone
      )
  
      defaults = {
          "rpn_score_thresh": 0.05,
      }
  
      kwargs = {**defaults, **kwargs}
      return _fasterrcnn_mobilenet_v3_large_fpn(
          weights=weights,
          progress=progress,
          num_classes=num_classes,
          weights_backbone=weights_backbone,
          trainable_backbone_layers=trainable_backbone_layers,
          **kwargs,
      )
  
imports: from typing import Any, Callable, List, Optional, Tuple, Union
  import torch
  import torch.nn.functional
  from torch import nn
  from torchvision.ops import MultiScaleRoIAlign
  from ...ops import misc
  from ...transforms._presets import ObjectDetection
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _COCO_CATEGORIES
  from .._utils import _ovewrite_value_param, handle_legacy_interface
  from ..mobilenetv3 import mobilenet_v3_large, MobileNet_V3_Large_Weights
  from ..resnet import resnet50, ResNet50_Weights
  from ._utils import overwrite_eps
  from .anchor_utils import AnchorGenerator
  from .backbone_utils import _mobilenet_extractor, _resnet_fpn_extractor, _validate_trainable_layers
  from .generalized_rcnn import GeneralizedRCNN
  from .roi_heads import RoIHeads
  from .rpn import RegionProposalNetwork, RPNHead
  from .transform import GeneralizedRCNNTransform
label_desc: Use image node_id 6 for calling a global function with example usage: fasterrcnn_mobilenet_v3_large_fpn() and returns: _fasterrcnn_mobilenet_v3_large_fpn