tf.math.logical_xor
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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.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.
- Two
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.
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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Last updated 2024-04-26 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.math.logical_xor\n\n\u003cbr /\u003e\n\n|------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/ops/math_ops.py#L1708-L1757) |\n\nLogical XOR function.\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.logical_xor`](https://www.tensorflow.org/api_docs/python/tf/math/logical_xor), [`tf.compat.v1.math.logical_xor`](https://www.tensorflow.org/api_docs/python/tf/math/logical_xor)\n\n\u003cbr /\u003e\n\n tf.math.logical_xor(\n x, y, name='LogicalXor'\n )\n\nx \\^ y = (x \\| y) \\& \\~(x \\& y)\n\nRequires that `x` and `y` have the same shape or have\n[broadcast-compatible](http://docs.scipy.org/doc/numpy/user/basics.broadcasting.html)\nshapes. For example, `x` and `y` can be:\n\n- Two single elements of type `bool`\n- One [`tf.Tensor`](../../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.\n- Two [`tf.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.\n\n#### Usage:\n\n a = tf.constant([True])\n b = tf.constant([False])\n tf.math.logical_xor(a, b)\n \u003ctf.Tensor: shape=(1,), dtype=bool, numpy=array([ True])\u003e\n\n c = tf.constant([True])\n x = tf.constant([False, True, True, False])\n tf.math.logical_xor(c, x)\n \u003ctf.Tensor: shape=(4,), dtype=bool, numpy=array([ True, False, False, True])\u003e\n\n y = tf.constant([False, False, True, True])\n z = tf.constant([False, True, False, True])\n tf.math.logical_xor(y, z)\n \u003ctf.Tensor: shape=(4,), dtype=bool, numpy=array([False, True, True, False])\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Args ---- ||\n|--------|------------------------------------------------|\n| `x` | A [`tf.Tensor`](../../tf/Tensor) type bool. |\n| `y` | A [`tf.Tensor`](../../tf/Tensor) of type bool. |\n| `name` | A name for the operation (optional). |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A [`tf.Tensor`](../../tf/Tensor) of type bool with the same size as that of x or y. ||\n\n\u003cbr /\u003e"]]
View source on GitHub