code: def build_container_map(self) -> ContainerMap:
      map = ContainerMap()
  
      transformer_containers = [
          Llama2TransformerContainer(self.model)
          for _ in range(self.model.num_layers)
      ]
  
      map.set_transformer_params(
          ["model.layers"], transformer_containers
      )
  
      map.set_non_transformer_params(
          Llama2NonTransformerContainer(self.model)
      )
  
      map.set_unmapped_params(
          [
              f"model.layers.{i}.self_attn.rotary_emb.inv_freq"
              for i in range(self.model.num_layers)
          ]
      )
  
      return map
  
file_path: deepspeed/deepspeed/inference/v2/model_implementations/llama_v2/policy.py
imports: from typing import Any
  from ...config_v2 import RaggedInferenceEngineConfig
  from ..inference_policy_base import ContainerMap, InferenceV2Policy
  from .container import Llama2NonTransformerContainer, Llama2TransformerContainer
  from .model import Llama2InferenceModel
label_desc: Use image node_id 2 for calling the Llama2Policy obj's underlying member method code with example usage: obj.build_container_map() and returns: map