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_deemphasis(self):
      waveform = torch.rand(
          3, 4, 10, dtype=self.dtype, device=self.device
      )
      deemphasis = T.Deemphasis(coeff=0.97).to(
          dtype=self.dtype, device=self.device
      )
      output = deemphasis(waveform)
      ts_output = torch_script(deemphasis)(waveform)
      self.assertEqual(ts_output, output)
  
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 35 for calling the Transforms obj's underlying member method code with example usage: obj.test_deemphasis() without return types