code: def _deeplabv3_mobilenetv3(
      backbone: MobileNetV3,
      num_classes: int,
      aux: Optional[bool],
  ) -> DeepLabV3:
      backbone = backbone.features
      # Gather the indices of blocks which are strided. These are the locations of C1, ..., Cn-1 blocks.
      # The first and last blocks are always included because they are the C0 (conv1) and Cn.
      stage_indices = (
          [0]
          + [
              i
              for i, b in enumerate(backbone)
              if getattr(b, "_is_cn", False)
          ]
          + [len(backbone) - 1]
      )
      out_pos = stage_indices[-1]  # use C5 which has output_stride = 16
      out_inplanes = backbone[out_pos].out_channels
      aux_pos = stage_indices[
          -4
      ]  # use C2 here which has output_stride = 8
      aux_inplanes = backbone[aux_pos].out_channels
      return_layers = {str(out_pos): "out"}
      if aux:
          return_layers[str(aux_pos)] = "aux"
      backbone = IntermediateLayerGetter(
          backbone, return_layers=return_layers
      )
  
      aux_classifier = (
          FCNHead(aux_inplanes, num_classes) if aux else None
      )
      classifier = DeepLabHead(out_inplanes, num_classes)
      return DeepLabV3(backbone, classifier, aux_classifier)
  
imports: from functools import partial
  from typing import Any, Optional, Sequence
  import torch
  from torch import nn
  from torch.nn import functional
  from ...transforms._presets import SemanticSegmentation
  from .._api import register_model, Weights, WeightsEnum
  from .._meta import _VOC_CATEGORIES
  from .._utils import _ovewrite_value_param, handle_legacy_interface, IntermediateLayerGetter
  from ..mobilenetv3 import mobilenet_v3_large, MobileNet_V3_Large_Weights, MobileNetV3
  from ..resnet import ResNet, resnet101, ResNet101_Weights, resnet50, ResNet50_Weights
  from ._utils import _SimpleSegmentationModel
  from .fcn import FCNHead
label_desc: Use image node_id 2 for calling a global function with example usage: _deeplabv3_mobilenetv3(backbone, num_classes, aux) and returns: DeepLabV3