code: def test_rtf_power(self, n_iter, diagonal_loading):
      channel = 4
      n_fft_bin = 5
      psd_speech = torch.rand(
          n_fft_bin, channel, channel, dtype=torch.cfloat
      )
      psd_noise = torch.rand(
          n_fft_bin, channel, channel, dtype=torch.cfloat
      )
      self.assert_grad(
          F.rtf_power,
          (psd_speech, psd_noise, 0, n_iter, diagonal_loading),
      )
  
imports: from functools import partial
  from typing import Callable, Tuple
  import torch
  import torchaudio.functional
  from parameterized import parameterized
  from torch import Tensor
  from torch.autograd import gradcheck, gradgradcheck
  from torchaudio_unittest.common_utils import get_spectrogram, get_whitenoise, nested_params, rnnt_utils, TestBaseMixin, use_deterministic_algorithms
label_desc: Use image node_id 32 for calling the Autograd obj's underlying member method code with example usage: obj.test_rtf_power(n_iter, diagonal_loading) without return types