text: # coding: utf-8
  from __future__ import with_statement, print_function, absolute_import
  
  
  def wavenet(out_channels=256,
              layers=20,
              stacks=2,
              residual_channels=512,
              gate_channels=512,
              skip_out_channels=512,
              cin_channels=-1,
              gin_channels=-1,
              weight_normalization=True,
              dropout=1 - 0.95,
              kernel_size=3,
              n_speakers=None,
              upsample_conditional_features=False,
              upsample_scales=[16, 16],
              freq_axis_kernel_size=3,
              scalar_input=False,
              use_speaker_embedding=True,
              legacy=True,
              ):
      from wavenet_vocoder_core import WaveNet
  
      model = WaveNet(out_channels=out_channels, layers=layers, stacks=stacks,
                      residual_channels=residual_channels,
                      gate_channels=gate_channels,
                      skip_out_channels=skip_out_channels,
                      kernel_size=kernel_size, dropout=dropout,
                      weight_normalization=weight_normalization,
                      cin_channels=cin_channels, gin_channels=gin_channels,
                      n_speakers=n_speakers,
                      upsample_conditional_features=upsample_conditional_features,
                      upsample_scales=upsample_scales,
                      freq_axis_kernel_size=freq_axis_kernel_size,
                      scalar_input=scalar_input,
                      use_speaker_embedding=use_speaker_embedding,
                      legacy=legacy,
                      )
  
      return model
  