code: def get_wer_ctc(
      self, prediction: str, reference: str, test_wer_bpe: bool
  ):
      ctc_decoder_predictions_tensor_mock = Mock(
          return_value=([prediction], None)
      )
      if test_wer_bpe:
          decoding = Mock(
              blank_id=self.char_tokenizer.tokenizer.vocab_size,
              tokenizer=deepcopy(self.char_tokenizer),
              ctc_decoder_predictions_tensor=ctc_decoder_predictions_tensor_mock,
              decode_tokens_to_str=self.char_tokenizer.ids_to_text,
              spec=CTCBPEDecoding,
          )
          wer = WER(decoding, use_cer=False)
      else:
          decoding = Mock(
              blank_id=len(self.vocabulary),
              labels_map=self.vocabulary.copy(),
              ctc_decoder_predictions_tensor=ctc_decoder_predictions_tensor_mock,
              decode_tokens_to_str=self.decode_token_to_str_with_vocabulary_mock,
              spec=CTCDecoding,
          )
          wer = WER(decoding, use_cer=False)
      targets_tensor = self.__reference_string_to_tensor(
          reference, test_wer_bpe
      )
  
      wer(
          predictions=None,
          predictions_lengths=None,
          targets=targets_tensor,
          targets_lengths=torch.tensor([len(reference)]),
      )
      res, _, _ = wer.compute()
      res = res.detach().cpu()
      # return res[0] / res[1]
      return res.item()
  
imports: import dataclasses
  import io
  import random
  import string
  from copy import deepcopy
  from typing import List
  from unittest.mock import Mock, patch
  import pytest
  import torch
  from torchmetrics.audio.snr import SignalNoiseRatio
  from nemo.collections.asr.metrics.audio import AudioMetricWrapper
  from nemo.collections.asr.metrics.wer import WER, word_error_rate, word_error_rate_detail, word_error_rate_per_utt
  from nemo.collections.asr.parts.submodules.ctc_decoding import CTCBPEDecoding, CTCBPEDecodingConfig, CTCDecoding, CTCDecodingConfig
  from nemo.collections.asr.parts.submodules.rnnt_decoding import RNNTBPEDecoding, RNNTDecoding
  from nemo.collections.asr.parts.utils.rnnt_utils import Hypothesis
  from nemo.collections.common.tokenizers import CharTokenizer
  from nemo.utils.config_utils import assert_dataclass_signature_match
label_desc: Use image node_id 10 for calling the TestWordErrorRate obj's underlying member method code with example usage: obj.get_wer_ctc(prediction, reference, test_wer_bpe) and returns: res