pymor.neural_network¶
Module Contents¶
Classes¶
Reduced Basis reductor relying on artificial neural networks. |
- class pymor.neural_network.NeuralNetworkReductor(fom, training_set, validation_set=None, validation_ratio=0.1, basis_size=None, rtol=0.0, atol=0.0, l2_err=0.0, pod_params=None, ann_mse='like_basis')¶
Reduced Basis reductor relying on artificial neural networks.
This is a reductor that constructs a reduced basis using proper orthogonal decomposition and trains a neural network that approximates the mapping from parameter space to coefficients of the full-order solution in the reduced basis. The approach is described in
- reduce(self, hidden_layers='[(N+P)*3, (N+P)*3]', activation_function=torch.tanh, optimizer=optim.LBFGS, epochs=1000, batch_size=20, learning_rate=1.0, restarts=10, seed=0)¶
Reduce by training artificial neural networks.