code: def test_accumulatable_wer_stats():
      from speechbrain.utils.edit_distance import (
          accumulatable_wer_stats,
      )
  
      refs = [[[1, 2, 3], [4, 5, 6]], [[7, 8], [9]]]
      hyps = [[[1, 2, 4], [5, 6]], [[7, 8], [10]]]
      # Test basic functionality:
      stats = accumulatable_wer_stats(refs[0], hyps[0])
      assert stats["WER"] == 100.0 * 2 / 6
      stats = accumulatable_wer_stats(refs[1], hyps[1], stats)
      assert stats["WER"] == 100.0 * 3 / 9
      # Test edge cases:
      import math
  
      # No batches:
      stats = accumulatable_wer_stats([], [])
      assert stats["num_ref_tokens"] == 0
      assert math.isnan(stats["WER"])
      # Empty hyp sequence:
      stats = accumulatable_wer_stats([[1, 2, 3]], [[]])
      assert stats["num_ref_tokens"] == 3
      assert stats["WER"] == 100.0
      # Empty ref sequence:
      stats = accumulatable_wer_stats([[]], [[1, 2, 3]])
      assert stats["num_ref_tokens"] == 0
      assert stats["insertions"] == 3
      assert math.isnan(stats["WER"])
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_accumulatable_wer_stats() without return types