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: Convert synthetic controls into audio.
docstr_tok: ["Convert","synthetic","controls","into","audio","."]
code: def generate_synthetic_audio(self, features):
      """Convert synthetic controls into audio."""
      return self.processor_group(
          {
              "amplitudes": features["sin_amps"],
              "frequencies": features["sin_freqs"],
              "noise_magnitudes": features["noise_magnitudes"],
          }
      )
  
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 2 for calling the InverseSynthesis obj's underlying member method code with example usage: obj.generate_synthetic_audio(features) and returns: self