code: def gabor_impulse_response(t, center, fwhm):
      """
      Function for generating gabor impulse responses
      as used by GaborConv1d proposed in
  
      Neil Zeghidour, Olivier Teboul, F{\'e}lix de Chaumont Quitry & Marco Tagliasacchi, "LEAF: A LEARNABLE FRONTEND
      FOR AUDIO CLASSIFICATION", in Proc of ICLR 2021 (https://arxiv.org/abs/2101.08596)
      """
      denominator = 1.0 / (
          torch.sqrt(torch.tensor(2.0) * math.pi) * fwhm
      )
      gaussian = torch.exp(
          torch.tensordot(
              1.0 / (2.0 * fwhm.unsqueeze(1) ** 2),
              (-(t**2.0)).unsqueeze(0),
              dims=1,
          )
      )
      center_frequency_complex = center.type(torch.complex64)
      t_complex = t.type(torch.complex64)
      sinusoid = torch.exp(
          torch.complex(torch.tensor(0.0), torch.tensor(1.0))
          * torch.tensordot(
              center_frequency_complex.unsqueeze(1),
              t_complex.unsqueeze(0),
              dims=1,
          )
      )
      denominator = denominator.type(torch.complex64).unsqueeze(1)
      gaussian = gaussian.type(torch.complex64)
      return denominator * sinusoid * gaussian
  
file_path: speechbrain/speechbrain/processing/signal_processing.py
imports: import torch
  import math
  from packaging import version
label_desc: Use image node_id 11 for calling a global function with example usage: gabor_impulse_response(t, center, fwhm) and returns: unknown