code: def _fuse_awq_layernorm(fuse_module_names, module, target_cls):
      """
      Fuse the LayerNorm layers into a target class using autoawq
  
      Args:
          fuse_module_names (`List[str]`):
              The list of module names to fuse
          module (`nn.Module`):
              The pytorch parent module that has layernorm modules to fuse
          target_cls (`~autoawq.FasterTransformerRMSNorm`):
              The `FasterTransformerRMSNorm` class as it only supports that class
              for now.
      """
      for module_name in fuse_module_names:
          if hasattr(module, module_name):
              old_module = getattr(module, module_name)
              module._modules[module_name] = target_cls(
                  old_module.weight,
                  old_module.variance_epsilon,
              ).to(old_module.weight.device)
              del old_module
  
file_path: transformers/src/transformers/integrations/awq.py
imports: from ..activations import ACT2FN
  from ..modeling_utils import PreTrainedModel
  from ..utils import is_auto_awq_available, is_torch_available
  from ..utils.quantization_config import AwqBackendPackingMethod, AwqConfig, AWQLinearVersion
label_desc: Use image node_id 4 for calling a global function with example usage: _fuse_awq_layernorm(fuse_module_names, module, target_cls) without return types