class_docstr: LayoutConverter is a singleton class which converts the layout of a distributed tensor.
class_docstr_tok: ["LayoutConverter","is","a","singleton","class","which","converts","the","layout","of","a","distributed","tensor","."]
docstr: Get the total communication cost of the layout converting process.
docstr_tok: ["Get","the","total","communication","cost","of","the","layout","converting","process","."]
code: def get_total_comm_cost(
      self, source_layout: Layout, target_layout: Layout
  ) -> Dict[str, float]:
      """
      Get the total communication cost of the layout converting process.
      """
      transform_path, comm_action_sequence = self.layout_converting(
          source_layout, target_layout
      )
      total_cost = {"forward": 0.0, "backward": 0.0, "total": 0.0}
      for layout, comm_spec in zip(
          transform_path, comm_action_sequence
      ):
          cost_dict = get_comm_cost(
              layout, comm_spec, self.forward_only
          )
          for key in total_cost:
              total_cost[key] += cost_dict[key]
      return total_cost
  
imports: import math
  from copy import deepcopy
  from dataclasses import dataclass
  from typing import Dict, List, Tuple
  import torch
  import torch.distributed
  from colossalai.context.singleton_meta import SingletonMeta
  from colossalai.tensor.d_tensor.comm_spec import *
  from colossalai.tensor.d_tensor.layout import Layout
  from colossalai.tensor.d_tensor.misc import LayoutException
  from colossalai.tensor.utils import all_gather_simulator, all_to_all_simulator, shard_simulator
  from .sharding_spec import ShardingSpec
  from .utils import get_comm_cost
label_desc: Use image node_id 11 for calling the LayoutConverter obj's underlying member method code with example usage: obj.get_total_comm_cost(source_layout, target_layout) and returns: total_cost