code: def time_evaluation(self, threads):
      with ThreadPoolExecutor(max_workers=threads) as pool:
          wait(
              {
                  pool.submit(linear_sum_assignment, cost_matrix)
                  for cost_matrix in self.cost_matrices
              }
          )
  
file_path: scipy/benchmarks/benchmarks/optimize_lap.py
imports: from concurrent.futures import ThreadPoolExecutor, wait
  import numpy
  from .common import Benchmark, safe_import
label_desc: Use image node_id 2 for calling the ParallelLinearAssignment obj's underlying member method code with example usage: obj.time_evaluation(threads) without return types