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|
Logical XOR function.
tf.math.logical_xor(
x, y, name='LogicalXor'
)
x ^ y = (x | y) & ~(x & y)
Requires that x and y have the same shape or have
broadcast-compatible
shapes. For example, x and y can be:
- Two single elements of type
bool - One
tf.Tensorof typebooland one singlebool, where the result will be calculated by applying logical XOR with the single element to each element in the larger Tensor. - Two
tf.Tensorobjects of typeboolof the same shape. In this case, the result will be the element-wise logical XOR of the two input tensors.
Usage:
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.
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View source on GitHub