code: def instantiate_moe(
      moe_config: DSMoEConfig,
      engine_config: RaggedInferenceEngineConfig,
  ) -> DSMoEBase:
      """
      Choose an appropriate MoE implementation based on the given configurations. This
      method is currently a stub, but as more implementations may be developed  we can centralize
      the logic for choosing between them here.
  
      Arguments:
          moe_config (DSMoEConfig): Configuration for the MoE module.
          engine_config (RaggedInferenceEngineConfig): Configuration for the inference engine.
  
      Returns:
          A MoE module implementing the given configuration.
      """
  
      moe_type = "cutlass_multi_gemm_moe"
  
      if moe_type == "cutlass_multi_gemm_moe":
          # TODO: Get this off an engine config
          implementation_config = {
              "weight_dtype": moe_config.input_dtype,
          }
  
      # Currently, we only have one implementation, so we just return it.
      config = ConfigBundle(
          name="cutlass_multi_gemm_moe",
          config=moe_config,
          implementation_config=implementation_config,
      )
      return DSMoERegistry.instantiate_config(config)
  
file_path: deepspeed/deepspeed/inference/v2/modules/heuristics.py
imports: from ..config_v2 import RaggedInferenceEngineConfig
  from ..inference_utils import NormTypeEnum
  from .module_registry import ConfigBundle
  from ..modules.configs import DSEmbeddingsConfig, DSLinearConfig, DSMoEConfig, DSNormConfig, DSSelfAttentionConfig, DSUnembedConfig
  from ..modules.interfaces import DSEmbeddingBase, DSEmbeddingRegistry, DSLinearBase, DSLinearRegistry, DSMoEBase, DSMoERegistry, DSPostNormBase, DSPostNormRegistry, DSPreNormBase, DSPreNormRegistry, DSSelfAttentionBase, DSSelfAttentionRegistry, DSUnembedBase, DSUnembedRegistry
label_desc: Use image node_id 4 for calling a global function with example usage: instantiate_moe(moe_config, engine_config) and returns: DSMoERegistry