code: def test_speed(self):
      leading_dims = (3, 2)
      T = 200
      waveform = torch.rand(
          *leading_dims,
          T,
          dtype=self.dtype,
          device=self.device,
          requires_grad=True,
      )
      lengths = torch.randint(
          1, T, leading_dims, dtype=self.dtype, device=self.device
      )
      self.assert_grad(
          F.speed, (waveform, 1000, 1.1, lengths), enable_all_grad=False
      )
  
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 37 for calling the Autograd obj's underlying member method code with example usage: obj.test_speed() without return types