code: def test_small_model_pt(self):
      model = "anton-l/wav2vec2-random-tiny-classifier"
  
      audio_classifier = pipeline("audio-classification", model=model)
  
      audio = np.ones((8000,))
      output = audio_classifier(audio, top_k=4)
      self.assertEqual(
          nested_simplify(output, decimals=4),
          [
              {"score": 0.0842, "label": "no"},
              {"score": 0.0838, "label": "up"},
              {"score": 0.0837, "label": "go"},
              {"score": 0.0834, "label": "right"},
          ],
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_audio_classification.py
imports: import unittest
  import numpy
  from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
  from transformers.pipelines import AudioClassificationPipeline, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch, require_torchaudio, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 4 for calling the AudioClassificationPipelineTests obj's underlying member method code with example usage: obj.test_small_model_pt() without return types