code: def replace_to_bettertransformer(model, config):
      r"""
      Replaces the current model to its `BetterTransformer` implementation. Loops recursively into the model and replaces the
      `Layer` modules with its `BetterTransformer` correspondant model
  
      - Step 1: Recurse over the modules of the model
      - Step 2: Verify if the module `BetterTransformer` is present for that model
      - Step 3: If yes, replace the `...Layer` module with the `...LayerBetterTransformer` modules
      - Step 4: If not, yield an error.
      - Step 5: Post process the potentially converted model by setting the `is_last_layer` attribute to `True` for the last `BetterTransformer` layer.
      (done in `set_last_layer` function)
  
      Args:
          `model` (`torch.nn.Module`):
              The input model to convert
          `config` (`transformers.PreTrainedConfig`):
              The configuration dictionary of the model
      Returns:
          The converted model
      """
      for name, module in model.named_children():
          if hasattr(module, "SCB"):
              # 8-bit modules are not supported
              raise ValueError(
                  "`load_in_8bit` and `BetterTransformers` are mutually exclusive",
                  " please pass a model that is not loaded in 8-bit.",
              )
  
          # replace the module if it is a transformer layer compatible with bettertransformer
          target_classes = list(
              BetterTransformerManager.MODEL_MAPPING[
                  config.model_type
              ].keys()
          )
  
          # We may want to override methods without having to override whole modules.
          # For example, some methods handle the mask generation, which we do not need when using PyTorch SDPA.
          if (
              config.model_type
              in BetterTransformerManager.OVERWRITE_METHODS
          ):
              for (
                  class_name,
                  method_name_and_replacement,
              ) in BetterTransformerManager.OVERWRITE_METHODS[
                  config.model_type
              ].items():
                  if module.__class__.__name__ == class_name:
                      method_name = method_name_and_replacement[0]
                      new_method = method_name_and_replacement[1]
                      setattr(
                          module,
                          method_name,
                          types.MethodType(new_method, module),
                      )
  
          should_replace_module = False
          for target_class in target_classes:
              should_replace_module = (
                  module.__class__.__name__ == target_class
              )
              if should_replace_module:
                  bettertransformer_module = (
                      BetterTransformerManager.MODEL_MAPPING[
                          config.model_type
                      ][target_class](module, config)
                  )
                  model._modules[name] = bettertransformer_module
                  break
  
          if (
              len(list(module.children())) > 0
              and should_replace_module is False
          ):
              # we may explicitly exclude part of the model to use BetterTransformer
              if (
                  config.model_type
                  not in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM
                  or (
                      config.model_type
                      in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM
                      and name
                      not in BetterTransformerManager.EXCLUDE_FROM_TRANSFORM[
                          config.model_type
                      ]
                  )
              ):
                  replace_to_bettertransformer(module, config)
  
      return model
  
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 2 for calling a global function with example usage: replace_to_bettertransformer(model, config) and returns: model