code: def stft(audio, frame_size=2048, overlap=0.75, pad_end=True):
      """Differentiable stft in tensorflow, computed in batch."""
      # Remove channel dim if present.
      audio = tf_float32(audio)
      if len(audio.shape) == 3:
          audio = tf.squeeze(audio, axis=-1)
  
      s = tf.signal.stft(
          signals=audio,
          frame_length=int(frame_size),
          frame_step=int(frame_size * (1.0 - overlap)),
          fft_length=None,  # Use enclosing power of 2.
          pad_end=pad_end,
      )
      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 1 for calling a global function with example usage: stft(audio, frame_size, overlap, pad_end) and returns: s