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# tf.raw_ops.BitwiseXor

Elementwise computes the bitwise XOR of `x` and `y`.

The result will have those bits set, that are different in `x` and `y`. The computation is performed on the underlying representations of `x` and `y`.

#### For example:

``````import tensorflow as tf
from tensorflow.python.ops import bitwise_ops
dtype_list = [tf.int8, tf.int16, tf.int32, tf.int64,
tf.uint8, tf.uint16, tf.uint32, tf.uint64]

for dtype in dtype_list:
lhs = tf.constant([0, 5, 3, 14], dtype=dtype)
rhs = tf.constant([5, 0, 7, 11], dtype=dtype)
exp = tf.constant([5, 5, 4, 5],  dtype=tf.float32)

res = bitwise_ops.bitwise_xor(lhs, rhs)
tf.assert_equal(tf.cast(res, tf.float32), exp) # TRUE
``````

`x` A `Tensor`. Must be one of the following types: `int8`, `int16`, `int32`, `int64`, `uint8`, `uint16`, `uint32`, `uint64`.
`y` A `Tensor`. Must have the same type as `x`.
`name` A name for the operation (optional).

A `Tensor`. Has the same type as `x`.

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