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Logical XOR function.
tf.math.logical_xor( x, y, name='LogicalXor' )
x ^ y = (x | y) & ~(x & y)
The operation works for the following input types:
bool
tf.Tensor
of type bool
and one single bool
, where the result will be calculated by applying logical XOR with the single element to each element in the larger Tensor.tf.Tensor
objects of type bool
of the same shape. In this case, the result will be the element-wise logical XOR of the two input tensors.a = tf.constant([True]) b = tf.constant([False]) tf.math.logical_xor(a, b) <tf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])>
c = tf.constant([True]) x = tf.constant([False, True, True, False]) tf.math.logical_xor(c, x) <tf.Tensor: shape=(4,), dtype=bool, numpy=array([ True, False, False, True])>
y = tf.constant([False, False, True, True]) z = tf.constant([False, True, False, True]) tf.math.logical_xor(y, z) <tf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, False])>
Args | |
---|---|
x | A tf.Tensor type bool. |
y | A tf.Tensor of type bool. |
name | A name for the operation (optional). |
Returns | |
---|---|
A tf.Tensor of type bool with the same size as that of x or y. |
© 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/math/logical_xor