# tf.math.logical_xor

Logical XOR function.

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])>`
```

`x` A `tf.Tensor` type bool.
`y` A `tf.Tensor` of type bool.
`name` A name for the operation (optional).

A `tf.Tensor` of type bool with the same size as that of x or y.

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