old_contents: from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import division
  
  import tensorflow as tf
  
  def prelu(features, initializer=tf.constant_initializer(1), name=None):
      """
      Implementation of [Parametric ReLU](https://arxiv.org/abs/1502.01852) borrowed from Keras.
      """
      with tf.variable_scope(name or 'PReLU'):
          alpha = tf.get_variable('alpha',
              shape=features.get_shape().as_list()[1:],
              initializer=initializer)
          pos = tf.nn.relu(features)
          neg = alpha * (features - tf.abs(features)) * 0.5
          return pos + neg
  
new_contents: from __future__ import absolute_import
  from __future__ import print_function
  from __future__ import division
  
  import tensorflow as tf
  
  def prelu(features, initializer=None, name=None):
      """
      Implementation of [Parametric ReLU](https://arxiv.org/abs/1502.01852) borrowed from Keras.
      """
      with tf.variable_scope(name or 'PReLU'):
          alpha = tf.get_variable('alpha',
              shape=features.get_shape().as_list()[1:],
              initializer=initializer)
          pos = tf.nn.relu(features)
          neg = alpha * (features - tf.abs(features)) * 0.5
          return pos + neg
  
subject: Remove default initializer from prelu