code: def set_last_layer(model: torch.nn.Module):
      r"""
      Iterates over the module list containing the `LayerBetterTransformer` modules. Sets the last layer's `is_last_layer`
      attribute to `True`
  
      Args:
          `model` (`torch.nn.Module`):
              The input converted model
      Raises:
          `NotImplementedError`: Raised if this method fails, in which case the model is not supported.
      """
      dict_named_module = dict(model.named_modules())
      sort_fn = lambda list_modules: [
          module.__class__.__name__ for module in list_modules
      ]  # noqa: E731
  
      modulelist_lengths = []
  
      for key in dict_named_module.keys():
          if (
              isinstance(dict_named_module[key], torch.nn.ModuleList)
              and "encoder" in key
              and (
                  model.config.model_type
                  not in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM
                  or (
                      model.config.model_type
                      in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM
                      and all(
                          name not in key
                          for name in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM[
                              model.config.model_type
                          ]
                      )
                  )
              )
          ):
              modulelist_lengths.append(
                  (len(dict_named_module[key]), key)
              )
  
      # For Albert, each transformer layer is wrapped
      # inside a ModuleList
      if len(modulelist_lengths) > 1:
          _, key = max(modulelist_lengths, key=lambda item: item[0])
          largest_module_list = dict_named_module[key]
  
          for module in largest_module_list[-1].modules():
              if "LayerBetterTransformer" in module.__class__.__name__:
                  setattr(module, "is_last_layer", True)
                  return
      else:
          for key in dict_named_module.keys():
              if isinstance(
                  dict_named_module[key], torch.nn.ModuleList
              ) and all(
                  "LayerBetterTransformer" in module_name
                  for module_name in sort_fn(dict_named_module[key])
              ):
                  setattr(
                      dict_named_module[key][-1], "is_last_layer", True
                  )
                  return
  
      raise Exception(
          f"The transformation of the model {model.__class__.__name__} to BetterTransformer failed while it should not. Please fill"
          " a bug report or open a PR to support this model at https://github.com/huggingface/optimum/"
      )
  
file_path: optimum/optimum/bettertransformer/transformation.py
imports: import logging
  import os
  import types
  from copy import deepcopy
  from typing import TYPE_CHECKING, Dict, Optional, Union
  import torch
  from packaging.version import parse
  from ..utils import check_if_pytorch_greater, is_accelerate_available, recurse_getattr, recurse_setattr
  from .models import BetterTransformerManager
label_desc: Use image node_id 3 for calling a global function with example usage: set_last_layer(model) without return types