class_docstr: Dynamically compute additional power_db feature.
class_docstr_tok: ["Dynamically","compute","additional","power_db","feature","."]
docstr: Puts scaled f0, loudness, and power back to hz & db scales.
docstr_tok: ["Puts","scaled","f0",",","loudness",",","and","power","back","to","hz","&","db","scales","."]
code: def invert_scaling(f0_scaled, pw_scaled):
      """Puts scaled f0, loudness, and power back to hz & db scales."""
      f0_hz = inv_scale_f0_hz(f0_scaled)
      power_db = inv_scale_db(pw_scaled)
      return f0_hz, power_db
  
imports: import ddsp
  from ddsp.training import nn
  import gin
  import tensorflow
label_desc: Use image node_id 3 for calling the F0PowerPreprocessor obj's underlying member method code with example usage: obj.invert_scaling(f0_scaled, pw_scaled) and returns: f0_hz,  power_db