| activation_gelu {tfaddons} | R Documentation |
Gelu
Description
Gaussian Error Linear Unit.
Usage
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
## 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)