code: def make_vits_discriminator_args(**kwargs):
      defaults = dict(
          discriminator_type="hifigan_multi_scale_multi_period_discriminator",
          discriminator_params={
              "scales": 2,
              "scale_downsample_pooling": "AvgPool1d",
              "scale_downsample_pooling_params": {
                  "kernel_size": 4,
                  "stride": 2,
                  "padding": 2,
              },
              "scale_discriminator_params": {
                  "in_channels": 1,
                  "out_channels": 1,
                  "kernel_sizes": [15, 41, 5, 3],
                  "channels": 16,
                  "max_downsample_channels": 32,
                  "max_groups": 16,
                  "bias": True,
                  "downsample_scales": [2, 1],
                  "nonlinear_activation": "LeakyReLU",
                  "nonlinear_activation_params": {
                      "negative_slope": 0.1
                  },
              },
              "follow_official_norm": True,
              "periods": [2, 3],
              "period_discriminator_params": {
                  "in_channels": 1,
                  "out_channels": 1,
                  "kernel_sizes": [5, 3],
                  "channels": 4,
                  "downsample_scales": [3, 1],
                  "max_downsample_channels": 16,
                  "bias": True,
                  "nonlinear_activation": "LeakyReLU",
                  "nonlinear_activation_params": {
                      "negative_slope": 0.1
                  },
                  "use_weight_norm": True,
                  "use_spectral_norm": False,
              },
          },
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/espnet2/gan_tts/vits/test_vits.py
imports: import pytest
  import torch
  from espnet2.gan_tts.vits import VITS
label_desc: Use image node_id 3 for calling a global function with example usage: make_vits_discriminator_args() and returns: defaults