- a -

• apply_adjoint() : fnn_activation_linear::linearactivation, fnn_activation_nonlinear::nonlinearactivation, fnn_layer::layer, fnn_layer_dense::denselayer, fnn_layer_dropout::dropoutlayer, fnn_layer_normalisation::normalisationlayer, fnn_network_sequential::sequentialneuralnetwork
• apply_forward() : fnn_activation_linear::linearactivation, fnn_activation_relu::reluactivation, fnn_activation_tanh::tanhactivation, fnn_layer::layer, fnn_layer_dense::denselayer, fnn_layer_dropout::dropoutlayer, fnn_layer_normalisation::normalisationlayer, fnn_network_sequential::sequentialneuralnetwork
• apply_tangent_linear() : fnn_activation_linear::linearactivation, fnn_activation_nonlinear::nonlinearactivation, fnn_layer::layer, fnn_layer_dense::denselayer, fnn_layer_dropout::dropoutlayer, fnn_layer_normalisation::normalisationlayer, fnn_network_sequential::sequentialneuralnetwork

- g -

• get_input_size() : fnn_network_sequential::sequentialneuralnetwork
• get_num_parameters() : fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork
• get_output_size() : fnn_network_sequential::sequentialneuralnetwork
• get_parameters() : fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork

- s -

• set_parameters() : fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork

- t -

• tofile() : fnn_activation_linear::linearactivation, fnn_activation_relu::reluactivation, fnn_activation_tanh::tanhactivation, fnn_layer::layer, fnn_layer_dense::denselayer, fnn_layer_dropout::dropoutlayer, fnn_layer_normalisation::normalisationlayer, fnn_network_sequential::sequentialneuralnetwork