Elementwise computes the bitwise XOR of x
and y
.
tf.raw_ops.BitwiseXor( x, y, name=None )
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
.
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
Args | |
---|---|
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). |
Returns | |
---|---|
A Tensor . Has the same type as x . |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/raw_ops/BitwiseXor