code: def make_melgan_discriminator_args(**kwargs):
      defaults = dict(
          in_channels=1,
          out_channels=1,
          scales=2,
          downsample_pooling="AvgPool1d",
          # follow the official implementation setting
          downsample_pooling_params={
              "kernel_size": 4,
              "stride": 2,
              "padding": 1,
              "count_include_pad": False,
          },
          kernel_sizes=[5, 3],
          channels=16,
          max_downsample_channels=32,
          bias=True,
          downsample_scales=[2, 2],
          nonlinear_activation="LeakyReLU",
          nonlinear_activation_params={"negative_slope": 0.2},
          pad="ReflectionPad1d",
          pad_params={},
          use_weight_norm=True,
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/espnet2/gan_tts/melgan/test_melgan.py
imports: import numpy
  import pytest
  import torch
  from espnet2.gan_tts.hifigan.loss import DiscriminatorAdversarialLoss, FeatureMatchLoss, GeneratorAdversarialLoss
  from espnet2.gan_tts.melgan import MelGANGenerator, MelGANMultiScaleDiscriminator
label_desc: Use image node_id 2 for calling a global function with example usage: make_melgan_discriminator_args() and returns: defaults