text: from __future__ import unicode_literals
  from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  
  import tensorflow as tf
  
  
  def prelu(inputs, alpha_initializer=tf.constant_initializer()):
      """Probabilistic ReLu activation function
  
      Args:
          (tf.Tensor): input Tensor
          alpha_initializer (float, optional): an initial value for alpha
  
      Returns:
          tf.Tensor: a PreLu activated tensor
      """
  
      alpha = tf.get_variable('alpha',
                              shape=[],
                              dtype=tf.float32,
                              initializer=alpha_initializer)
  
      return leaky_relu(inputs, alpha)
  
  
  def leaky_relu(inputs, alpha=0.1):
      """Leaky ReLu activation function
  
      Args:
          inputs (tf.Tensor): input Tensor
          alpha (float): leakiness parameter
  
      Returns:
          tf.Tensor: a leaky ReLu activated tensor
      """
      return tf.maximum(inputs, alpha * inputs)
  