class_docstr: Dynamically compute additional power_db feature.
class_docstr_tok: ["Dynamically","compute","additional","power_db","feature","."]
code: def __init__(
      self,
      time_steps=1000,
      frame_rate=250,
      sample_rate=16000,
      frame_size=64,
      **kwargs,
  ):
      super().__init__(time_steps, **kwargs)
      self.frame_rate = frame_rate
      self.sample_rate = sample_rate
      self.frame_size = frame_size
  
imports: import ddsp
  from ddsp.training import nn
  import gin
  import tensorflow
label_desc: Use image node_id 1 to create a new F0PowerPreprocessor object from inherited base classes: F0LoudnessPreprocessor with example: obj = F0PowerPreprocessor(time_steps, frame_rate, sample_rate, frame_size)