/TensorFlow 2.4


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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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.