# activation_gelu: Gelu In tfaddons: Interface to 'TensorFlow SIG Addons'

## Description

Gaussian Error Linear Unit.

## Usage

 `1` ```activation_gelu(x, approximate = TRUE) ```

## Arguments

 `x` A 'Tensor'. Must be one of the following types: 'float16', 'float32', 'float64'. `approximate` bool, whether to enable approximation. Returns: A 'Tensor'. Has the same type as 'x'.

## Details

Computes gaussian error linear: '0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))' or 'x * P(X <= x) = 0.5 * x * (1 + erf(x / sqrt(2)))', where P(X) ~ N(0, 1), depending on whether approximation is enabled. See [Gaussian Error Linear Units (GELUs)](https://arxiv.org/abs/1606.08415) and [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805).

## Value

A 'Tensor'. Has the same type as 'x'.

## Computes gaussian error linear

'0.5 * x * (1 + tanh(sqrt(2 / pi) * (x + 0.044715 * x^3)))' or 'x * P(X <= x) = 0.5 * x * (1 + erf(x / sqrt(2)))', where P(X) ~ N(0, 1), depending on whether approximation is enabled.

## Examples

 ```1 2 3 4 5 6 7 8``` ```## Not run: library(keras) library(tfaddons) model = keras_model_sequential() %>% layer_conv_2d(filters = 10, kernel_size = c(3,3),input_shape = c(28,28,1), activation = activation_gelu) ## End(Not run) ```

tfaddons documentation built on July 2, 2020, 2:12 a.m.