class_docstr: Resamples and scales 'f0_hz' and 'loudness_db' features.
class_docstr_tok: ["Resamples","and","scales","'f0_hz","'","and","'loudness_db","'","features","."]
code: def call(
      self, loudness_db, f0_hz, audio=None
  ) -> ["f0_hz", "loudness_db", "f0_scaled", "ld_scaled"]:
      # Compute loudness fresh (it's fast).
      if self.compute_loudness:
          loudness_db = ddsp.spectral_ops.compute_loudness(
              audio,
              sample_rate=self.sample_rate,
              frame_rate=self.frame_rate,
          )
  
      # Resample features to the frame_rate.
      f0_hz = self.resample(f0_hz)
      loudness_db = self.resample(loudness_db)
      # For NN training, scale frequency and loudness to the range [0, 1].
      # Log-scale f0 features. Loudness from [-1, 0] to [1, 0].
      f0_scaled = scale_f0_hz(f0_hz)
      ld_scaled = scale_db(loudness_db)
      return f0_hz, loudness_db, f0_scaled, ld_scaled
  
imports: import ddsp
  from ddsp.training import nn
  import gin
  import tensorflow
label_desc: Use image node_id 2 for calling the F0LoudnessPreprocessor obj's underlying member method code with example usage: obj.call(loudness_db, f0_hz, audio) and returns: f0_hz,  loudness_db,  f0_scaled,  ld_scaled