class_docstr: Implements test for Transforms that are performed for different devices
class_docstr_tok: ["Implements","test","for","Transforms","that","are","performed","for","different","devices"]
code: def test_PitchShift(self):
      sample_rate = 8000
      n_steps = 4
      waveform = common_utils.get_whitenoise(sample_rate=sample_rate)
      pitch_shift = T.PitchShift(
          sample_rate=sample_rate, n_steps=n_steps
      )
      # dry-run for initializing parameters
      pitch_shift(waveform)
      self._assert_consistency(pitch_shift, waveform)
  
imports: import torch
  import torchaudio.transforms
  from parameterized import parameterized
  from torchaudio_unittest import common_utils
  from torchaudio_unittest.common_utils import skipIfRocm, TestBaseMixin, torch_script
label_desc: Use image node_id 24 for calling the Transforms obj's underlying member method code with example usage: obj.test_PitchShift() without return types