message: Finished with errors
diff: @@ -12,6 +12,43 @@ 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() and tf.cast() work differently when real dtype is casted as a complex dtype
  +(e.g. tf.complex64 or tf.complex128) as tf.cast() make imaginary part 0 while tf.bitcast()
  +gives module error.
  +For example,
  +
  +Example 1:
  +```python
  +>>> a = [1., 2., 3.]
  +>>> equality_bitcast = tf.bitcast(a,tf.complex128)
  +tensorflow.python.framework.errors_impl.InvalidArgumentError: Cannot bitcast from float to complex128: shape [3] [Op:Bitcast]
  +>>> equality_cast = tf.cast(a,tf.complex128)
  +>>> print(equality_cast)
  +tf.Tensor([1.+0.j 2.+0.j 3.+0.j], shape=(3,), dtype=complex128)
  +```
  +Example 2:
  +```python
  +>>> tf.bitcast(tf.constant(0xffffffff, dtype=tf.uint32), tf.uint8)
  +<tf.Tensor: ... shape=(4,), dtype=uint8, numpy=array([255, 255, 255, 255], dtype=uint8)>
  +```
  +Example 3:
  +```python
  +>>> 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)
  +>>> print(equality)
  +tf.Tensor([False True True], shape=(3,), dtype=bool)
  +>>> print(equality_cast)
  +tf.Tensor([0. 1. 1.], shape=(3,), dtype=float32)
  +>>> print(equality_bitcast)
  +tf.Tensor(
  +[[ 0 0 0 0]
  + [ 0 0 128 63]
  + [ 0 0 128 63]], shape=(3, 4), dtype=uint8)
  +```
  +
  *NOTE*: Bitcast is implemented as a low-level cast, so machines with different
  endian orderings will give different results.
  END
  