content: import tensorflow as tf
  import numpy as np
  
  def weight_variable_glorot(input_dim, output_dim, name=""):
      """Create a weight variable with Glorot & Bengio (AISTATS 2010)
      initialization.
      """
      init_range = np.sqrt(6.0 / (input_dim + output_dim))
      initial = tf.random_uniform([input_dim, output_dim], minval=-init_range,
                                  maxval=init_range, dtype=tf.float32)
      return tf.Variable(initial, name=name)
  