class_docstr: VST inference modules, for models trained with `models/vst/vst.gin`.
class_docstr_tok: ["VST","inference","modules",",","for","models","trained","with","`","models\/vst\/vst.gin","`","."]
docstr: Parse the model operative config with special streaming parameters.
code: def configure_gin(self):
      """Parse the model operative config with special streaming parameters."""
      # Customize config.
      config = [
          'OnlineF0PowerPreprocessor.padding = "valid"',
          "OnlineF0PowerPreprocessor.compute_f0 = True",
          "OnlineF0PowerPreprocessor.compute_power = True",
          "OnlineF0PowerPreprocessor.viterbi = False",
      ]
      if self.crepe_saved_model_path is not None:
          config.append(
              "OnlineF0PowerPreprocessor.crepe_saved_model_path = "
              f"'{self.crepe_saved_model_path}'"
          )
      with gin.unlock_config():
          gin.parse_config(config)
  
imports: import ddsp
  from ddsp.training import models
  from ddsp.training import train_util
  import gin
  import tensorflow
label_desc: Use image node_id 2 for calling the VSTExtractFeatures obj's underlying member method code with example usage: obj.configure_gin() without return types