code: def inv_mu_law_numpy(x, mu=255.0):
      """A numpy implementation of inverse Mu-Law.
  
      Args:
        x: The Mu-Law samples to decode.
        mu: The Mu we used to encode these samples.
  
      Returns:
        out: The decoded data.
      """
      x = np.array(x).astype(np.float32)
      out = (x + 0.5) * 2.0 / (mu + 1)
      out = np.sign(out) / mu * ((1 + mu) ** np.abs(out) - 1)
      out = np.where(np.equal(x, 0), x, out)
      return out
  
imports: import importlib
  import os
  import librosa
  import numpy
  import tensorflow.compat.v1
  import tf_slim
label_desc: Use image node_id 6 for calling a global function with example usage: inv_mu_law_numpy(x, mu) and returns: out