code: def test_chunk_iterator(self):
      feature_extractor = AutoFeatureExtractor.from_pretrained(
          "facebook/wav2vec2-base-960h"
      )
      inputs = torch.arange(100).long()
      ratio = 1
      outs = list(
          chunk_iter(inputs, feature_extractor, 100, 0, 0, ratio)
      )
      self.assertEqual(len(outs), 1)
      self.assertEqual([o["stride"] for o in outs], [(100, 0, 0)])
      self.assertEqual(
          [o["input_values"].shape for o in outs], [(1, 100)]
      )
      self.assertEqual([o["is_last"] for o in outs], [True])
  
      # two chunks no stride
      outs = list(
          chunk_iter(inputs, feature_extractor, 50, 0, 0, ratio)
      )
      self.assertEqual(len(outs), 2)
      self.assertEqual(
          [o["stride"] for o in outs], [(50, 0, 0), (50, 0, 0)]
      )
      self.assertEqual(
          [o["input_values"].shape for o in outs], [(1, 50), (1, 50)]
      )
      self.assertEqual([o["is_last"] for o in outs], [False, True])
  
      # two chunks incomplete last
      outs = list(
          chunk_iter(inputs, feature_extractor, 80, 0, 0, ratio)
      )
      self.assertEqual(len(outs), 2)
      self.assertEqual(
          [o["stride"] for o in outs], [(80, 0, 0), (20, 0, 0)]
      )
      self.assertEqual(
          [o["input_values"].shape for o in outs], [(1, 80), (1, 20)]
      )
      self.assertEqual([o["is_last"] for o in outs], [False, True])
  
      # one chunk since first is also last, because it contains only data
      # in the right strided part we just mark that part as non stride
      # This test is specifically crafted to trigger a bug if next chunk
      # would be ignored by the fact that all the data would be
      # contained in the strided left data.
      outs = list(
          chunk_iter(inputs, feature_extractor, 105, 5, 5, ratio)
      )
      self.assertEqual(len(outs), 1)
      self.assertEqual([o["stride"] for o in outs], [(100, 0, 0)])
      self.assertEqual(
          [o["input_values"].shape for o in outs], [(1, 100)]
      )
      self.assertEqual([o["is_last"] for o in outs], [True])
  
imports: import unittest
  import numpy
  import pytest
  from datasets import Audio, load_dataset
  from huggingface_hub import hf_hub_download, snapshot_download
  from transformers import MODEL_FOR_CTC_MAPPING, MODEL_FOR_SPEECH_SEQ_2_SEQ_MAPPING, AutoFeatureExtractor, AutoProcessor, AutoTokenizer, Speech2TextForConditionalGeneration, Wav2Vec2ForCTC, WhisperForConditionalGeneration
  from transformers.pipelines import AutomaticSpeechRecognitionPipeline, pipeline
  from transformers.pipelines.audio_utils import chunk_bytes_iter
  from transformers.pipelines.automatic_speech_recognition import _find_timestamp_sequence, chunk_iter
  from transformers.testing_utils import is_pipeline_test, is_torch_available, nested_simplify, require_pyctcdecode, require_tf, require_torch, require_torch_accelerator, require_torchaudio, slow, torch_device
  from .test_pipelines_common import ANY
label_desc: Use image node_id 37 for calling the AutomaticSpeechRecognitionPipelineTests obj's underlying member method code with example usage: obj.test_chunk_iterator() without return types