View source on GitHub |
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.Tensor
of typebool
and 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.Tensor
objects of typebool
of 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.
|