text: import torch.distributed as dist
  
  from colossalai.registry import DIST_GROUP_INITIALIZER
  from colossalai.global_variables import moe_env
  from .process_group_initializer import ProcessGroupInitializer
  from ..parallel_mode import ParallelMode
  
  
  @DIST_GROUP_INITIALIZER.register_module
  class Initializer_Moemodel(ProcessGroupInitializer):
      """Model parallel initialization for MoE system.
  
      :param moe_moel: Size of moe model parallel
      :param moe_data: Size of moe data parallel
      :param args: Args used in base class
      :param kwargs: Kwargs used in base class
  
      :type moe_model: int
      :type moe_data: int
      """
      def __init__(self, moe_model, moe_data, *args, **kwargs):
          super().__init__(*args, **kwargs)
          self.moe_model = moe_model
          self.moe_data = moe_data
  
      def init_dist_group(self):
          """Initialize model parallel groups in moe parallel environment,
          and assign local_ranks and groups to each gpu.
  
          :return: MoE model parallelism's information
          :rtype: Tuple(local_rank, group_world_size, process_group, ranks_in_group, mode)
          """
          local_rank = None
          ranks_in_group = None
          process_group = None
          group_world_size = None
          mode = ParallelMode.MOE_MODEL
  
          for i in range(self.moe_data):
              ranks = [i * self.moe_model + j for j in range(self.moe_model)]
              group = dist.new_group(ranks)
  
              if self.rank in ranks:
                  local_rank = ranks.index(self.rank)
                  group_world_size = len(ranks)
                  process_group = group
                  ranks_in_group = ranks
  
          return local_rank, group_world_size, process_group, ranks_in_group, mode
  
  
  @DIST_GROUP_INITIALIZER.register_module
  class Initializer_Moedata(ProcessGroupInitializer):
      """Data parallel initialization for MoE system.
  
      :param moe_moel: Size of moe model parallel
      :param moe_data: Size of moe data parallel
      :param args: Args used in base class
      :param kwargs: Kwargs used in base class
  
      :type moe_model: int
      :type moe_data: int
      """
      def __init__(self, moe_model, moe_data, *args, **kwargs):
          super().__init__(*args, **kwargs)
          self.moe_model = moe_model
          self.moe_data = moe_data
  
      def init_dist_group(self):
          """Initialize data parallel groups in moe parallel environment,
          and assign local_ranks and groups to each gpu.
  
          :return: MoE data parallelism's information
          :rtype: Tuple(local_rank, group_world_size, process_group, ranks_in_group, mode)
          """
          local_rank = None
          ranks_in_group = None
          process_group = None
          group_world_size = None
          mode = ParallelMode.MOE_DATA
  
          for i in range(self.moe_model):
              ranks = [i + j * self.moe_model for j in range(self.moe_data)]
              group = dist.new_group(ranks)
  
              if self.rank in ranks:
                  local_rank = ranks.index(self.rank)
                  group_world_size = len(ranks)
                  process_group = group
                  ranks_in_group = ranks
  
          return local_rank, group_world_size, process_group, ranks_in_group, mode
  
  
  @DIST_GROUP_INITIALIZER.register_module
  class Initializer_Moe(ProcessGroupInitializer):
      """Serves as the single entry point to MoE parallel initialization.
  
      :param args: Args used to initialize ProcessGroupInitializer
      :param kwargs: Kwargs used to initialize ProcessGroupInitializer
      """
      def __init__(self, *args, **kwargs):
          super().__init__(*args, **kwargs)
          self.moe_model = moe_env.model_parallel_size
          self.moe_data = moe_env.data_parallel_size
          self.model_initializer = Initializer_Moemodel(
              self.moe_model, self.moe_data, *args, **kwargs)
          self.data_initializer = Initializer_Moedata(
              self.moe_model, self.moe_data, *args, **kwargs)
  
      def init_dist_group(self):
          """Initializes MoE parallel communication groups.
  
          :return: MoE parallelism's information
          :rtype: list of Tuples (local_rank, group_world_size, process_group, ranks_in_group, mode)
          """
          parallel_setting = [self.model_initializer.init_dist_group(),
                              self.data_initializer.init_dist_group()]
          return parallel_setting
  