message: Modified tf.bitcast
diff: @@ -12,6 +12,26 @@ If `T` is smaller than `type`, the operator requires that the rightmost
  dimension be equal to sizeof(`type`)/sizeof(`T`). The shape then goes from
  [..., sizeof(`type`)/sizeof(`T`)] to [...].
  +tf.bitcast can be used over tf.cast when you have to assign some unsigned data type.
  +For example,
  + tf.bitcast(tf.cast(my_tensor, tf.int8), tf.uint8)
  +
  +Example,
  +>>> import tensorflow as tf
  +>>> x = [1., 2., 3.]
  +>>> y = [0., 2., 3.]
  +>>> equality =tf.equal(x,y)
  +>>> equality_cast = tf.cast(equality,tf.float32)
  +>>> equality_bitcast = tf.bitcast(equality_cast,tf.uint8)
  +>>> sess = tf.Session()
  +>>> print(sess.run(equality))
  +>>> [False True True]
  +>>> print(sess.run(equality_cast))
  +>>> [0. 1. 1.]
  +>>> print(sess.run(equality_bitcast))
  +>>> [[ 0 0 0 0]
  + [ 0 0 128 63]
  + [ 0 0 128 63]]
  *NOTE*: Bitcast is implemented as a low-level cast, so machines with different
  endian orderings will give different results.
  END
  