title: What are the differences between tf.initialize_all_variables() and tf.global_variables_initializer()
body: <p>On Tensorflow official website, it gives explantions of the <code>tf.initialize_all_variables()</code> and <code>tf.global_variables_initializer()</code> functions as follow  </p>
  
  <blockquote>
    <h3>tf.initialize_all_variables():</h3>
    
    <p>Returns an op that initializes all variables.</p>
    
    <h3>tf.global_variables_initializer():</h3>
    
    <p>Adds an op to initialize all variables in the model</p>
  </blockquote>
  
  <p>It seems like both can be used to initialize all variables in graphs. Can we use these two functions exchangbly? If not, what would be the differences? </p>