Here is a list of all data types members with links to the data types they belong to:

- a -

• activation : fnn_layer::layer
• adjoint_input : fnn_layer::layer
• alpha : fnn_layer_normalisation::normalisationlayer
• 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

- b -

• batch_size : fnn_activation_linear::linearactivation, fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork
• beta : fnn_layer_normalisation::normalisationlayer

- d -

• draws : fnn_layer_dropout::dropoutlayer

- f -

• forward_input : fnn_layer::layer

- 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

- i -

• input_size : fnn_layer::layer
• ip_end : fnn_network_sequential::sequentialneuralnetwork
• ip_start : fnn_network_sequential::sequentialneuralnetwork

- l -

• list_layers : fnn_network_sequential::sequentialneuralnetwork

- n -

• num_layers : fnn_network_sequential::sequentialneuralnetwork
• num_parameters : fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork

- o -

• output_size : fnn_layer::layer

- p -

• parameters : fnn_layer::layer

- r -

• rate : fnn_layer_dropout::dropoutlayer

- s -

• self_size : fnn_activation_linear::linearactivation
• set_parameters() : fnn_layer::layer, fnn_network_sequential::sequentialneuralnetwork

- t -

• tangent_linear_input : fnn_layer::layer
• this_layer : fnn_network_sequential::layercontainer
• 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

- z -

• z_prime : fnn_activation_nonlinear::nonlinearactivation