trainable_network_s Submodule


Uses

  • module~~trainable_network_s~~UsesGraph module~trainable_network_s trainable_network_s module~trainable_network_m trainable_network_m module~trainable_network_s->module~trainable_network_m julienne_m julienne_m module~trainable_network_m->julienne_m module~input_output_pair_m input_output_pair_m module~trainable_network_m->module~input_output_pair_m module~kind_parameters_m kind_parameters_m module~trainable_network_m->module~kind_parameters_m module~mini_batch_m mini_batch_m module~trainable_network_m->module~mini_batch_m module~neural_network_m neural_network_m module~trainable_network_m->module~neural_network_m module~tensor_map_m tensor_map_m module~trainable_network_m->module~tensor_map_m module~training_configuration_m training_configuration_m module~trainable_network_m->module~training_configuration_m module~input_output_pair_m->module~kind_parameters_m module~tensor_m tensor_m module~input_output_pair_m->module~tensor_m module~mini_batch_m->module~input_output_pair_m module~mini_batch_m->module~kind_parameters_m module~neural_network_m->julienne_m module~neural_network_m->module~kind_parameters_m module~neural_network_m->module~mini_batch_m module~neural_network_m->module~tensor_map_m module~activation_m activation_m module~neural_network_m->module~activation_m module~double_precision_file_m double_precision_file_m module~neural_network_m->module~double_precision_file_m module~metadata_m metadata_m module~neural_network_m->module~metadata_m module~neural_network_m->module~tensor_m module~tensor_map_m->julienne_m module~tensor_map_m->module~kind_parameters_m module~double_precision_string_m double_precision_string_m module~tensor_map_m->module~double_precision_string_m module~tensor_map_m->module~tensor_m module~training_configuration_m->module~kind_parameters_m julienne_file_m julienne_file_m module~training_configuration_m->julienne_file_m julienne_string_m julienne_string_m module~training_configuration_m->julienne_string_m module~training_configuration_m->module~activation_m module~training_configuration_m->module~double_precision_file_m module~hyperparameters_m hyperparameters_m module~training_configuration_m->module~hyperparameters_m module~network_configuration_m network_configuration_m module~training_configuration_m->module~network_configuration_m module~tensor_names_m tensor_names_m module~training_configuration_m->module~tensor_names_m module~activation_m->julienne_m iso_c_binding iso_c_binding module~activation_m->iso_c_binding module~double_precision_file_m->julienne_m module~double_precision_file_m->module~double_precision_string_m module~double_precision_string_m->julienne_m module~hyperparameters_m->module~kind_parameters_m module~hyperparameters_m->julienne_string_m module~hyperparameters_m->module~double_precision_string_m module~metadata_m->julienne_string_m module~metadata_m->module~double_precision_string_m module~network_configuration_m->julienne_string_m module~network_configuration_m->module~double_precision_string_m module~tensor_m->module~kind_parameters_m module~tensor_names_m->julienne_string_m

Module Procedures

module procedure /home/runner/work/fiats/fiats/doc/html/module/trainable_network_s.html default_real_map_to_training_ranges elemental module function default_real_map_to_training_ranges(self, input_output_pair) result(normalized_input_output_pair)

Arguments

Type IntentOptional Attributes Name
class(trainable_network_t), intent(in) :: self
type(input_output_pair_t), intent(in) :: input_output_pair

Return Value type(input_output_pair_t)

module procedure /home/runner/work/fiats/fiats/doc/html/module/trainable_network_s.html default_real_network pure module function default_real_network(neural_network) result(trainable_network)

Arguments

Type IntentOptional Attributes Name
type(neural_network_t), intent(in) :: neural_network

Return Value type(trainable_network_t)

module procedure /home/runner/work/fiats/fiats/doc/html/module/trainable_network_s.html default_real_train pure module subroutine default_real_train(self, mini_batches_arr, cost, adam, learning_rate)

Arguments

Type IntentOptional Attributes Name
class(trainable_network_t), intent(inout) :: self
type(mini_batch_t), intent(in) :: mini_batches_arr(:)
real, intent(out), optional, allocatable :: cost(:)
logical, intent(in) :: adam
real, intent(in) :: learning_rate

module procedure /home/runner/work/fiats/fiats/doc/html/module/trainable_network_s.html perturbed_identity_network module function perturbed_identity_network(training_configuration, perturbation_magnitude, metadata, input_map, output_map) result(trainable_network)

Arguments

Type IntentOptional Attributes Name
type(training_configuration_t), intent(in) :: training_configuration
real, intent(in) :: perturbation_magnitude
type(string_t), intent(in) :: metadata(:)
type(tensor_map_t) :: input_map
type(tensor_map_t) :: output_map

Return Value type(trainable_network_t)