title: Different types of divisions in TensorFlow
body: <p>I am very new to TensorFlow. So I came across this different types of division in TensorFlow from <a href="https://docs.google.com/presentation/d/1iO_bBL_5REuDQ7RJ2F35vH2BxAiGMocLC6t_N-6eXaE/edit#slide=id.g2ee508db2e_1_20" rel="noreferrer">here</a>. Code printed below:</p>
  
  <pre><code>a = tf.constant([2, 2], name='a')
  b = tf.constant([[0, 1], [2, 3]], name='b')
  with tf.Session() as sess:
      print(sess.run(tf.div(b, a)))             ⇒ [[0 0] [1 1]]
      print(sess.run(tf.divide(b, a)))          ⇒ [[0. 0.5] [1. 1.5]]
      print(sess.run(tf.truediv(b, a)))         ⇒ [[0. 0.5] [1. 1.5]]
      print(sess.run(tf.floordiv(b, a)))        ⇒ [[0 0] [1 1]]
      print(sess.run(tf.realdiv(b, a)))         ⇒ # Error: only works for real values
      print(sess.run(tf.truncatediv(b, a)))     ⇒ [[0 0] [1 1]]
      print(sess.run(tf.floor_div(b, a)))       ⇒ [[0 0] [1 1]]
  </code></pre>
  
  <p>Since I am a noob in programming languages I could not understand some of their documentation which included things like "computes division python style", etc. If someone can explain the differences between all and their practical aspect, I would be grateful.</p>