code: def test_return_timestamps_ctc_fast(self):
      speech_recognizer = pipeline(
          task="automatic-speech-recognition",
          model="hf-internal-testing/tiny-random-wav2vec2",
      )
  
      ds = load_dataset(
          "hf-internal-testing/librispeech_asr_dummy",
          "clean",
          split="validation",
      ).sort("id")
      # Take short audio to keep the test readable
      audio = ds[40]["audio"]["array"][:800]
  
      output = speech_recognizer(audio, return_timestamps="char")
      self.assertEqual(
          output,
          {
              "text": "ZBT ZX G",
              "chunks": [
                  {"text": " ", "timestamp": (0.0, 0.012)},
                  {"text": "Z", "timestamp": (0.012, 0.016)},
                  {"text": "B", "timestamp": (0.016, 0.02)},
                  {"text": "T", "timestamp": (0.02, 0.024)},
                  {"text": " ", "timestamp": (0.024, 0.028)},
                  {"text": "Z", "timestamp": (0.028, 0.032)},
                  {"text": "X", "timestamp": (0.032, 0.036)},
                  {"text": " ", "timestamp": (0.036, 0.04)},
                  {"text": "G", "timestamp": (0.04, 0.044)},
              ],
          },
      )
  
      output = speech_recognizer(audio, return_timestamps="word")
      self.assertEqual(
          output,
          {
              "text": "ZBT ZX G",
              "chunks": [
                  {"text": "ZBT", "timestamp": (0.012, 0.024)},
                  {"text": "ZX", "timestamp": (0.028, 0.036)},
                  {"text": "G", "timestamp": (0.04, 0.044)},
              ],
          },
      )
  
imports: import unittest
  import numpy
  import pytest
  from datasets import load_dataset
  from huggingface_hub import snapshot_download
  from transformers import MODEL_FOR_CTC_MAPPING, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, AutoFeatureExtractor, AutoTokenizer, Speech2TextForConditionalGeneration, Wav2Vec2ForCTC, WhisperForConditionalGeneration, WhisperProcessor
  from transformers.pipelines import AutomaticSpeechRecognitionPipeline, pipeline
  from transformers.pipelines.audio_utils import chunk_bytes_iter
  from transformers.pipelines.automatic_speech_recognition import chunk_iter
  from transformers.testing_utils import is_torch_available, nested_simplify, require_pyctcdecode, require_tf, require_torch, require_torchaudio, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 19 for calling the AutomaticSpeechRecognitionPipelineTests obj's underlying member method code with example usage: obj.test_return_timestamps_ctc_fast() without return types