code: def _get_inputs(self):
      input_config = self._get_input_config()
      batch_size = input_config["batch_size"]
      time_length = input_config["time_length"]
      in_channels = input_config["in_channels"]
  
      input = torch.rand(batch_size, in_channels, time_length).to(
          device=self.device, dtype=self.dtype
      )
      return input
  
imports: import math
  import torch
  from parameterized import parameterized
  from torchaudio.prototype.models import hifigan_vocoder, hifigan_vocoder_v1, hifigan_vocoder_v2, hifigan_vocoder_v3
  from torchaudio.prototype.pipelines import HIFIGAN_VOCODER_V3_LJSPEECH
  from torchaudio_unittest.common_utils import TestBaseMixin, torch_script
  from .original.env import AttrDict
  from .original.meldataset import mel_spectrogram
  from .original.models import Generator
label_desc: Use image node_id 4 for calling the HiFiGANTestImpl obj's underlying member method code with example usage: obj._get_inputs() and returns: input