# gelu#

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

Apply the Gaussian error linear unit (GELU) activation function.

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

• approximate (`bool`, default: `False`) – Whether to approximate, default is `True`. An approximation is always used if the input array is complex.

• 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 – The input array with gelu applied element-wise.

Examples

With `ivy.Array` input:

```>>> x = ivy.array([-1.2, -0.6, 1.5])
>>> y = ivy.gelu(x)
>>> y
ivy.array([-0.138, -0.165, 1.4])
```

With `ivy.NativeArray` input:

```>>> x = ivy.native_array([-1.3, 3.8, 2.1])
>>> y = ivy.gelu(x)
>>> y
ivy.array([-0.126, 3.8, 2.06])
```

With `ivy.Container` input:

```>>> x = ivy.Container(a=ivy.array([1., 2.]), b=ivy.array([-0.9, -1.]))
>>> y = ivy.gelu(x)
>>> y
{
a: ivy.array([0.841, 1.95]),
b: ivy.array([-0.166, -0.159])
}
```
Array.gelu(self, /, *, approximate=False, complex_mode='jax', out=None)[source]#

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

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

• approximate (`bool`, default: `False`) – whether to use the approximate version of the gelu function.

• 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 gelu activation function applied element-wise.

Examples

```>>> x = ivy.array([-1.2, -0.6, 1.5])
>>> y = x.gelu()
>>> print(y)
ivy.array([-0.138, -0.165, 1.4])
```
Container.gelu(self, /, *, approximate=False, 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.gelu. This method simply wraps the function, and so the docstring for ivy.gelu also applies to this method with minimal changes.

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

• approximate (`Union`[`bool`, `Container`], default: `False`) – whether to use the gelu approximation algorithm or exact formulation.

• 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 gelu unit function applied element-wise.

Examples

```>>> x = ivy.Container(a=ivy.array([1., 2.]), b=ivy.array([-0.9, -1.]))
>>> y = x.gelu()
print(y)
{
a: ivy.array([0.841, 1.95]),
b: ivy.array([-0.166, -0.159])
}
```