code: def __init__(self, client_module, inference=True):
      super().__init__(
          inference,
          mlp_act_func_type=ActivationFuncType.GATED_SILU,
          norm_type=NormType.RMSNorm,
      )
      self.client_module = client_module
      try:
          import transformers
  
          LLAMALayerPolicy._orig_layer_class = transformers.models.llama.modeling_llama.LlamaDecoderLayer  # type: ignore
      except:
          LLAMALayerPolicy._orig_layer_class = None
  
imports: from .base import *
  from .features import HybridSplitQKVContainer, HybridGatedMLPContainer, MetaTensorContainer
  from deepspeed.utils.types import ActivationFuncType, NormType
  from deepspeed.model_implementations.transformers.ds_gpt import DeepSpeedGPTInference
  import torch
  from torch.nn.parameter import Parameter
  from ..policy import TransformerPolicy, transformer_param_names, maybe_copy, maybe_copy_qkv, maybe_copy_geglu, maybe_get_lora
label_desc: Use image node_id 1 to create a new LLAMALayerPolicy object from inherited base classes: TransformerPolicy with example: obj = LLAMALayerPolicy(client_module, inference)