code: def test_hifi_decoder():
      dummy_input = torch.rand((1, 207, 100)).to(device)
      dummy_spec_lens = torch.tensor([207]).to(device)
  
      waveform_decoder = HifiganGenerator(
          100,
          1,
          v_args.resblock_type_decoder,
          v_args.resblock_dilation_sizes_decoder,
          v_args.resblock_kernel_sizes_decoder,
          v_args.upsample_kernel_sizes_decoder,
          v_args.upsample_initial_channel_decoder,
          v_args.upsample_rates_decoder,
          inference_padding=0,
          cond_channels=0,
          conv_pre_weight_norm=False,
          conv_post_weight_norm=False,
          conv_post_bias=False,
      ).to(device)
      waveform_decoder = waveform_decoder.train()
  
      (
          vocoder_input_slices,
          slice_ids,
      ) = rand_segments(  # pylint: disable=unused-variable
          x=dummy_input.transpose(1, 2),
          x_lengths=dummy_spec_lens,
          segment_size=32,
          let_short_samples=True,
          pad_short=True,
      )
  
      outputs = waveform_decoder(x=vocoder_input_slices.detach())
      assert list(outputs.shape) == [1, 1, 8192]
  
file_path: TTS/tests/tts_tests2/test_delightful_tts_layers.py
imports: import torch
  from TTS.tts.configs.delightful_tts_config import DelightfulTTSConfig
  from TTS.tts.layers.delightful_tts.acoustic_model import AcousticModel
  from TTS.tts.models.delightful_tts import DelightfulTtsArgs, VocoderConfig
  from TTS.tts.utils.helpers import rand_segments
  from TTS.tts.utils.text.tokenizer import TTSTokenizer
  from TTS.vocoder.models.hifigan_generator import HifiganGenerator
label_desc: Use image node_id 2 for calling a global function with example usage: test_hifi_decoder() without return types