PiNet

pinn.networks.pinet(tensors, pp_nodes=[16, 16], pi_nodes=[16, 16], ii_nodes=[16, 16], en_nodes=[16, 16], depth=4, atom_types=[1, 6, 7, 8], act='tanh', rc=4.0, cutoff_type='f1', basis_type='polynomial', n_basis=4, gamma=3.0, preprocess=False)

Network function for the PiNet neural network

Parameters:

• tensors – input data (nested tensor from dataset).
• atom_types (list) – elements for the one-hot embedding.
• pp_nodes (list) – number of nodes for pp layer.
• pi_nodes (list) – number of nodes for pi layer.
• ii_nodes (list) – number of nodes for ii layer.
• en_nodes (list) – number of nodes for en layer.
• depth (int) – number of interaction blocks.
• rc (float) – cutoff radius.
• basis_type (string) – type of basis function to use, can be “polynomial” or “gaussian”.
• gamma (float) – controls width of gaussian function for gaussian basis.
• n_basis (int) – number of basis functions to use.
• cutoff_type (string) – cutoff function to use with the basis.
• act (string) – activation function to use.
• preprocess (bool) – whether to return the preprocessed tensor.

Returns:

prediction or preprocessed tensor dictionary