# relu#

ivy.relu(x, /, *, complex_mode='jax', out=None)[source]#

Apply the rectified linear unit function element-wise.

If the input is complex, then by default each element is set to zero if either its real part is strictly negative or if its real part is zero and its imaginary part is negative. This behaviour can be changed by specifying a different complex_mode.

Parameters:
• x (`Union`[`Array`, `NativeArray`]) – input array

• complex_mode (`Literal`[`'split'`, `'magnitude'`, `'jax'`], default: `'jax'`) – optional specifier for how to handle complex data types. See `ivy.func_wrapper.handle_complex_input` for more detail.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Array`

Returns:

ret – an array containing the rectified linear unit activation of each element in `x`.

Examples

With `ivy.Array` input:

```>>> x = ivy.array([-1., 0., 1.])
>>> y = ivy.relu(x)
>>> print(y)
ivy.array([0., 0., 1.])
```
```>>> x = ivy.array([1.5, 0.7, -2.4])
>>> y = ivy.zeros(3)
>>> ivy.relu(x, out = y)
>>> print(y)
ivy.array([1.5, 0.7, 0.])
```

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([1.0, -1.2]), b=ivy.array([0.4, -0.2]))
>>> x = ivy.relu(x, out=x)
>>> print(x)
{
a: ivy.array([1., 0.]),
b: ivy.array([0.40000001, 0.])
}
```
Array.relu(self, /, *, complex_mode='jax', out=None)[source]#

ivy.Array instance method variant of ivy.relu. This method simply wraps the function, and so the docstring for ivy.relu also applies to this method with minimal changes.

Parameters:
• self (`Array`) – input array.

• complex_mode (`Literal`[`'split'`, `'magnitude'`, `'jax'`], default: `'jax'`) – optional specifier for how to handle complex data types. See `ivy.func_wrapper.handle_complex_input` for more detail.

• out (`Optional`[`Array`], default: `None`) – optional output array, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Array`

Returns:

ret – an array with the relu activation function applied element-wise.

Examples

```>>> x = ivy.array([-1., 0., 1.])
>>> y = x.relu()
>>> print(y)
ivy.array([0., 0., 1.])
```
Container.relu(self, /, *, key_chains=None, to_apply=True, prune_unapplied=False, map_sequences=False, complex_mode='jax', out=None)[source]#

ivy.Container instance method variant of ivy.relu. This method simply wraps the function, and so the docstring for ivy.relu also applies to this method with minimal changes.

Parameters:
• self (`Container`) – input container.

• key_chains (`Optional`[`Union`[`List`[`str`], `Dict`[`str`, `str`], `Container`]], default: `None`) – The key-chains to apply or not apply the method to. Default is `None`.

• to_apply (`Union`[`bool`, `Container`], default: `True`) – If True, the method will be applied to key_chains, otherwise key_chains will be skipped. Default is `True`.

• prune_unapplied (`Union`[`bool`, `Container`], default: `False`) – Whether to prune key_chains for which the function was not applied. Default is `False`.

• map_sequences (`Union`[`bool`, `Container`], default: `False`) – Whether to also map method to sequences (lists, tuples). Default is `False`.

• complex_mode (`Literal`[`'split'`, `'magnitude'`, `'jax'`], default: `'jax'`) – optional specifier for how to handle complex data types. See `ivy.func_wrapper.handle_complex_input` for more detail.

• out (`Optional`[`Container`], default: `None`) – optional output container, for writing the result to. It must have a shape that the inputs broadcast to.

Return type:

`Container`

Returns:

ret – a container with the rectified linear activation unit function applied element-wise.

Examples

```>>> x = ivy.Container(a=ivy.array([1.0, -1.2]), b=ivy.array([0.4, -0.2]))
>>> y = x.relu()
>>> print(y)
{
a: ivy.array([1., 0.]),
b: ivy.array([0.40000001, 0.])
}
```