class_docstr: Inverse synthesis model (ddsp-inv).
  
  EXPERIMENTAL
  
  Builds a hierarchical model of audio:
  Audio -> Sinusoid -> Harmonic -> Sinusoid -> Audio.
  
  Unlike other models, the processor group is defined in the constructor, as
  there are many synthesizer specific regularizers and self-supervised losses.
class_docstr_tok: ["Inverse","synthesis","model","(","ddsp-inv",")",".","EXPERIMENTAL","Builds","a","hierarchical","model","of","audio",":","Audio","-",">","Sinusoid","-",">","Harmonic","-",">","Sinusoid","-",">","Audio",".","Unlike","other","models",",","the","processor","group","is","defined","in","the","constructor",",","as","there","are","many","synthesizer","specific","regularizers","and","self-supervised","losses","."]
docstr: Extract audio output tensor from outputs dict of call().
docstr_tok: ["Extract","audio","output","tensor","from","outputs","dict","of","call","(",")","."]
code: def get_audio_from_outputs(self, outputs):
      """Extract audio output tensor from outputs dict of call()."""
      audio_out = (
          outputs["sin_audio"]
          if self.harmonic_encoder is None
          else outputs["harm_audio"]
      )
      return audio_out
  
file_path: ddsp/ddsp/training/models/inverse_synthesis.py
imports: import functools
  import ddsp
  from ddsp.training.models.model import Model
  import tensorflow
label_desc: Use image node_id 4 for calling the InverseSynthesis obj's underlying member method code with example usage: obj.get_audio_from_outputs(outputs) and returns: audio_out