docstr: Tests convolving signals using fast fourier transform (fft).
  
  Generate random signals and convolve using fft. Compare outputs to the
  implementation in scipy.signal.
  
  Args:
    audio_size: Size of the audio to convolve.
    impulse_response_size: Size of the impulse response to convolve.
docstr_tok: ["Tests","convolving","signals","using","fast","fourier","transform","(","fft",")",".","Generate","random","signals","and","convolve","using","fft",".","Compare","outputs","to","the","implementation","in","scipy.signal",".","Args",":","audio_size",":","Size","of","the","audio","to","convolve",".","impulse_response_size",":","Size","of","the","impulse","response","to","convolve","."]
code: def test_fft_convolve_is_accurate(
      self, audio_size, impulse_response_size
  ):
      """Tests convolving signals using fast fourier transform (fft).
  
      Generate random signals and convolve using fft. Compare outputs to the
      implementation in scipy.signal.
  
      Args:
        audio_size: Size of the audio to convolve.
        impulse_response_size: Size of the impulse response to convolve.
      """
  
      # Create random signals to convolve.
      audio = np.ones([1, audio_size]).astype(np.float32)
      impulse_response = np.ones([1, impulse_response_size]).astype(
          np.float32
      )
  
      output_tf = core.fft_convolve(
          audio, impulse_response, padding="valid", delay_compensation=0
      )[0]
  
      output_np = signal.fftconvolve(audio[0], impulse_response[0])
  
      difference = output_np - output_tf
      total_difference = np.abs(difference).mean()
      threshold = 1e-3
      self.assertLessEqual(total_difference, threshold)
  
imports: from absl.testing import parameterized
  from ddsp import core
  import librosa
  import numpy
  from scipy import signal
  import tensorflow.compat.v2
label_desc: Use image node_id 2 for calling the FiniteImpulseResponseTest obj's underlying member method code with example usage: obj.test_fft_convolve_is_accurate(audio_size, impulse_response_size) without return types