--- title: Exponential Linear Unit. type: docs repo: https://github.com/rstudio/keras menu: main: name: Exponential Linear Unit. - keras parent: keras-reference aliases: - /reference/keras/layer_activation_elu.html - /keras/reference/layer_activation_elu.html - /guide/keras/reference/layer_activation_elu.html - /tools/tools/keras/reference/layer_activation_elu.html - /installation/keras/reference/layer_activation_elu.html - /tutorials/keras/reference/layer_activation_elu.html - /guide/tools/keras/reference/layer_activation_elu.html - /deploy/keras/reference/layer_activation_elu.html - /tools/keras/reference/layer_activation_elu.html - /tutorials/tools/keras/reference/layer_activation_elu.html ---
It follows: f(x) = alpha * (exp(x) - 1.0)
for x < 0
, f(x) = x
for x >= 0
.
layer_activation_elu(
object,
alpha = 1,
input_shape = NULL,
batch_input_shape = NULL,
batch_size = NULL,
dtype = NULL,
name = NULL,
trainable = NULL,
weights = NULL
)
| object | Model or layer object |
| alpha | Scale for the negative factor. |
| input_shape | Input shape (list of integers, does not include the samples axis) which is required when using this layer as the first layer in a model. |
| batch_input_shape | Shapes, including the batch size. For instance,
|
| batch_size | Fixed batch size for layer |
| dtype | The data type expected by the input, as a string ( |
| name | An optional name string for the layer. Should be unique in a model (do not reuse the same name twice). It will be autogenerated if it isn't provided. |
| trainable | Whether the layer weights will be updated during training. |
| weights | Initial weights for layer. |
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs).
Other activation layers:
layer_activation_leaky_relu()
,
layer_activation_parametric_relu()
,
layer_activation_relu()
,
layer_activation_selu()
,
layer_activation_softmax()
,
layer_activation_thresholded_relu()
,
layer_activation()