code: def test_biquad(self):
      x = get_whitenoise(sample_rate=22050, duration=0.01, n_channels=1)
      a = torch.tensor([0.7, 0.2, 0.6])
      b = torch.tensor([0.4, 0.2, 0.9])
      self.assert_grad(
          F.biquad, (x, b[0], b[1], b[2], a[0], a[1], a[2])
      )
  
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 12 for calling the Autograd obj's underlying member method code with example usage: obj.test_biquad() without return types