code: def get_bottleneck_layer(backbone: str, **kwargs) -> OCBE:
      """Get appropriate bottleneck layer based on the name of the backbone.
  
      Args:
          backbone (str): Name of the backbone.
  
      Returns:
          Bottleneck_layer: One-Class Bottleneck Embedding module.
      """
      if backbone in ("resnet18", "resnet34"):
          ocbe = OCBE(BasicBlock, 2, **kwargs)
      else:
          ocbe = OCBE(Bottleneck, 3, **kwargs)
  
      return ocbe
  
file_path: anomalib/src/anomalib/models/reverse_distillation/components/bottleneck.py
imports: from __future__ import annotations
  from typing import Callable
  import torch
  from torch import Tensor, nn
  from torchvision.models.resnet import BasicBlock, Bottleneck
label_desc: Use image node_id 3 for calling a global function with example usage: get_bottleneck_layer(backbone) and returns: ocbe