code: def export_impulse_response(model_path, save_dir, target_sr=None):
      """Extracts and saves the reverb impulse response."""
      with gin.unlock_config():
          ddsp.training.inference.parse_operative_config(model_path)
          model = ddsp.training.models.Autoencoder()
          model.restore(model_path)
      sr = model.processor_group.harmonic.sample_rate
      reverb = model.processor_group.reverb
      reverb.build(unused_input_shape=[])
      ir = reverb.get_controls(audio=tf.zeros([1, 1]))["ir"].numpy()[0]
      print(
          f"Reverb Impulse Response is {ir.shape[0] / sr} seconds long"
      )
  
      def save_ir(ir, sr):
          """Save the impulse response."""
          ir_path = os.path.join(save_dir, f"reverb_ir_{sr}_hz.wav")
          with tf.io.gfile.GFile(ir_path, "wb") as f:
              wav_data = note_seq.audio_io.samples_to_wav_data(ir, sr)
              f.write(wav_data)
  
      # Save to original impulse response.
      save_ir(ir, sr)
  
      # Save the resampled impulse response.
      if target_sr is not None:
          sr = target_sr
          ir = librosa.resample(ir, orig_sr=sr, target_sr=target_sr)
          save_ir(ir, sr)
  
imports: import datetime
  import json
  import os
  from absl import app
  from absl import flags
  import ddsp
  from ddsp.training import data
  from ddsp.training import inference
  from ddsp.training import postprocessing
  from ddsp.training import train_util
  import gin
  import librosa
  import note_seq
  import tensorflow
  from tensorflowjs.converters import converter
  from tflite_support import metadata
label_desc: Use image node_id 7 for calling a global function with example usage: export_impulse_response(model_path, save_dir, target_sr) without return types