code: def make_discriminator_args(**kwargs):
      defaults = dict(
          in_channels=1,
          out_channels=1,
          kernel_size=3,
          layers=5,
          conv_channels=16,
          nonlinear_activation="LeakyReLU",
          nonlinear_activation_params={"negative_slope": 0.2},
          bias=True,
          use_weight_norm=True,
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/espnet2/gan_tts/parallel_wavegan/test_parallel_wavegan.py
imports: import numpy
  import pytest
  import torch
  from espnet2.gan_tts.hifigan.loss import DiscriminatorAdversarialLoss, GeneratorAdversarialLoss
  from espnet2.gan_tts.parallel_wavegan import ParallelWaveGANDiscriminator, ParallelWaveGANGenerator
label_desc: Use image node_id 2 for calling a global function with example usage: make_discriminator_args() and returns: defaults