code: def mobilenet_backbone(
      *,
      backbone_name: str,
      weights: Optional[WeightsEnum],
      fpn: bool,
      norm_layer: Callable[
          ..., nn.Module
      ] = misc_nn_ops.FrozenBatchNorm2d,
      trainable_layers: int = 2,
      returned_layers: Optional[List[int]] = None,
      extra_blocks: Optional[ExtraFPNBlock] = None,
  ) -> nn.Module:
      backbone = mobilenet.__dict__[backbone_name](
          weights=weights, norm_layer=norm_layer
      )
      return _mobilenet_extractor(
          backbone, fpn, trainable_layers, returned_layers, extra_blocks
      )
  
file_path: vision/torchvision/models/detection/backbone_utils.py
imports: import warnings
  from typing import Callable, Dict, List, Optional, Union
  from torch import nn, Tensor
  from torchvision.ops import misc
  from torchvision.ops.feature_pyramid_network import ExtraFPNBlock, FeaturePyramidNetwork, LastLevelMaxPool
  from ..None import mobilenet, resnet
  from .._api import _get_enum_from_fn, WeightsEnum
  from .._utils import handle_legacy_interface, IntermediateLayerGetter
label_desc: Use image node_id 4 for calling a global function with example usage: mobilenet_backbone() and returns: _mobilenet_extractor