# tf.math.logical_and

Returns the truth value of x AND y element-wise.

### Used in the notebooks

Used in the tutorials

Logical AND function.

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 AND 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 AND of the two input tensors.

You can also use the `&` operator instead.

#### Usage:

````a = tf.constant([True])`
`b = tf.constant([False])`
`tf.math.logical_and(a, b)`
`<tf.Tensor: shape=(1,), dtype=bool, numpy=array([False])>`
`a & b`
`<tf.Tensor: shape=(1,), dtype=bool, numpy=array([False])>`
```
````c = tf.constant([True])`
`x = tf.constant([False, True, True, False])`
`tf.math.logical_and(c, x)`
`<tf.Tensor: shape=(4,), dtype=bool, numpy=array([False,  True,  True, False````