code: def make_melgan_generator_args(**kwargs):
      defaults = dict(
          in_channels=80,
          out_channels=1,
          kernel_size=7,
          channels=32,
          bias=True,
          upsample_scales=[4, 4],
          stack_kernel_size=3,
          stacks=2,
          nonlinear_activation="LeakyReLU",
          nonlinear_activation_params={"negative_slope": 0.2},
          pad="ReflectionPad1d",
          pad_params={},
          use_final_nonlinear_activation=True,
          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 1 for calling a global function with example usage: make_melgan_generator_args() and returns: defaults