code: def _quantize_overflow(x, k):
      G = tf.compat.v1.get_default_graph()
      n = float(2**k - 1)
      max_value = tf.reduce_max(input_tensor=x)
      min_value = tf.reduce_min(input_tensor=x)
      with G.gradient_override_map({"Round": "Identity"}):
          step = tf.stop_gradient((max_value - min_value) / n)
          return (
              tf.round(
                  (
                      tf.maximum(tf.minimum(x, max_value), min_value)
                      - min_value
                  )
                  / step
              )
              * step
              + min_value
          )
  
imports: import numpy
  import tensorflow
  from tensorflow.python.ops.rnn_cell import LSTMStateTuple
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated, deprecated_alias
label_desc: Use image node_id 22 for calling a global function with example usage: _quantize_overflow(x, k) and returns: unknown