code: def memory_workload(self):
      if self.mode == "fwd":
          sol_count = 1
          algorithmic_count = 1
      else:
          sol_count = (1) + (1)
          algorithmic_count = 1 + (1 + 1)
  
      buffer_size = self.M * self.N * self.K
      return {
          "sol": buffer_size * sol_count,
          "algorithmic": buffer_size * algorithmic_count,
      }
  
imports: import itertools
  import operator
  import numpy
  import torch
  from .None import benchmark
label_desc: Use image node_id 6 for calling the BroadcastMulBench obj's underlying member method code with example usage: obj.memory_workload() and returns: dict