enerzyme.models.activation

Functions

get_activation_fn(key[, activation_params])

Classes

BaseScaledTemperedActivation([dim_feature, ...])
ShiftedSoftplus([dim_feature, ...])
Swish([dim_feature, initial_alpha, ...])	Swish activation function with learnable feature-wise parameters: f(x) = alpha*x * sigmoid(beta*x) sigmoid(x) = 1/(1 + exp(-x)) For beta -> 0 : f(x) -> 0.5*alpha*x For beta -> inf: f(x) -> max(0, alpha*x)