class_docstr: Test suite for classes defined in `transforms` module
class_docstr_tok: ["Test","suite","for","classes","defined","in","`","transforms","`","module"]
code: def test_rtf_mvdr(self):
      waveform = common_utils.get_whitenoise(
          sample_rate=8000, duration=1, n_channels=6
      )
      specgram = common_utils.get_spectrogram(waveform, n_fft=400)
      batch_size, channel, freq, time = (
          3,
          2,
          specgram.shape[-2],
          specgram.shape[-1],
      )
      specgram = specgram.reshape(batch_size, channel, freq, time)
      rtf = torch.rand(batch_size, freq, channel, dtype=torch.cfloat)
      psd_n = torch.rand(
          batch_size, freq, channel, channel, dtype=torch.cfloat
      )
      reference_channel = 0
      transform = T.RTFMVDR()
  
      # Single then transform then batch
      expected = [
          transform(specgram[i], rtf[i], psd_n[i], reference_channel)
          for i in range(batch_size)
      ]
      expected = torch.stack(expected)
  
      # Batch then transform
      computed = transform(specgram, rtf, psd_n, reference_channel)
  
      self.assertEqual(computed, expected)
  
imports: import os
  import torch
  from parameterized import parameterized
  from torchaudio import transforms
  from torchaudio_unittest import common_utils
label_desc: Use image node_id 21 for calling the TestTransforms obj's underlying member method code with example usage: obj.test_rtf_mvdr() without return types