atomistic.Polarizability
- class atomistic.Polarizability(*args: Any, **kwargs: Any)[source]
Predicts polarizability tensor using tensor rank factorization. This requires an equivariant representation, e.g. PaiNN, that provides both scalar and vectorial features.
References:
- Parameters:
n_in – input dimension of representation
n_hidden – size of hidden layers. If an integer, same number of node is used for all hidden layers resulting in a rectangular network. If None, the number of neurons is divided by two after each layer starting n_in resulting in a pyramidal network.
n_layers – number of layers.
activation – activation function
polarizability_key – the key under which the predicted polarizability will be stored