code: def permuted_input_test(hyp, ref, calculated):
      """
      Randomly permute the input to see if evaluation result stays the same.
      """
      for hyp_permed in permutations(hyp):
          cpWER, hyp_min, ref_str = calculate_session_cpWER(
              spk_hypothesis=hyp_permed, spk_reference=ref
          )
          diff = torch.abs(torch.tensor(calculated - cpWER))
          assert diff <= 1e-6
  
file_path: NeMo/tests/collections/asr/test_diar_metrics.py
imports: from itertools import permutations
  import pytest
  import torch
  from nemo.collections.asr.metrics.der import calculate_session_cpWER, calculate_session_cpWER_bruteforce, get_online_DER_stats, get_partial_ref_labels
label_desc: Use image node_id 3 for calling a global function with example usage: permuted_input_test(hyp, ref, calculated) without return types