code: def normalize_input(signal, normalization_threshold=5e-4):
      """Normalizes the signal to the [-1, 1] range."""
      sig_min = tf.reduce_min(signal, name="norm_min", keepdims=True)
      sig_max = tf.reduce_max(signal, name="norm_max", keepdims=True)
      # Don't normalize silent noise.
      sig_delta = tf.maximum(
          (sig_max - sig_min) * 0.5,
          normalization_threshold,
          name="norm_delta",
      )
      return (signal - sig_min) / sig_delta - 1.0
  
imports: import functools
  from typing import Any, Dict, Optional, Sequence
  from absl import logging
  from dmvr import builders
  from dmvr import processors
  from dmvr import tokenizers
  import numpy
  from scenic.projects.mbt.datasets.dataset_utils import _decode_spectrogram
  from scenic.projects.mbt.datasets.dataset_utils import apply_specaugment
  import tensorflow
label_desc: Use image node_id 2 for calling a global function with example usage: normalize_input(signal, normalization_threshold) and returns: unknown