class_docstr: This encoder maps directly from audio to synthesizer parameters.
  
  EXPERIMENTAL
  
  It is equivalent of a base Encoder and Decoder together.
code: def __init__(
      self,
      output_splits=(
          ("frequencies", 100 * 64),
          ("amplitudes", 100),
          ("noise_magnitudes", 60),
      ),
      spectral_fn=spectral_ops.compute_logmel,
      size="tiny",
      **kwargs,
  ):
      super().__init__(
          output_keys=[key for key, dim in output_splits], **kwargs
      )
      self.output_splits = output_splits
      self.spectral_fn = spectral_fn
  
      # Layers.
      self.resnet = nn.ResNet(size=size)
      self.dense_outs = [tfkl.Dense(v[1]) for v in output_splits]
  
imports: import ddsp
  from ddsp import spectral_ops
  from ddsp.training import nn
  import gin
  import tensorflow.compat.v2
label_desc: Use image node_id 1 to create a new ResnetSinusoidalEncoder object from inherited base classes: nn with example: obj = ResnetSinusoidalEncoder(output_splits, spectral_fn, size)