Exponential Linear Unit.
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. |
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()
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