code: def prelu(self, inp, name):
      with tf.variable_scope(name):
          i = inp.get_shape().as_list()
          alpha = self.make_var("alpha", shape=(i[-1]))
          output = tf.nn.relu(inp) + tf.multiply(
              alpha, -tf.nn.relu(-inp)
          )
      return output
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import cv2
  import os
  import inspect
label_desc: Use image node_id 10 for calling the Network obj's underlying member method code with example usage: obj.prelu(inp, name) and returns: output