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_Spectrogram_return_complex(self):
      tensor = torch.rand((1, 1000))
      self._assert_consistency(
          T.Spectrogram(power=None, return_complex=True), tensor
      )
  
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 4 for calling the Transforms obj's underlying member method code with example usage: obj.test_Spectrogram_return_complex() without return types