code: def stft_np(audio, frame_size=2048, overlap=0.75, pad_end=True):
      """Non-differentiable stft using librosa, one example at a time."""
      assert frame_size * overlap % 2.0 == 0.0
      hop_size = int(frame_size * (1.0 - overlap))
      is_2d = len(audio.shape) == 2
  
      if pad_end:
          audio = pad(
              audio, frame_size, hop_size, "same", axis=is_2d
          ).numpy()
  
      def stft_fn(y):
          return librosa.stft(
              y=y,
              n_fft=int(frame_size),
              hop_length=hop_size,
              center=False,
          ).T
  
      s = (
          np.stack([stft_fn(a) for a in audio])
          if is_2d
          else stft_fn(audio)
      )
      return s
  
imports: import crepe
  from ddsp import core
  from ddsp.core import safe_log
  from ddsp.core import tf_float32
  import gin
  import librosa
  import numpy
  import tensorflow.compat.v2
  import tensorflow_probability
label_desc: Use image node_id 2 for calling a global function with example usage: stft_np(audio, frame_size, overlap, pad_end) and returns: s, librosa