training_configuration_m Module


Uses

  • module~~training_configuration_m~~UsesGraph module~training_configuration_m training_configuration_m module~differentiable_activation_strategy_m differentiable_activation_strategy_m module~training_configuration_m->module~differentiable_activation_strategy_m module~hyperparameters_m hyperparameters_m module~training_configuration_m->module~hyperparameters_m module~kind_parameters_m kind_parameters_m module~training_configuration_m->module~kind_parameters_m module~network_configuration_m network_configuration_m module~training_configuration_m->module~network_configuration_m sourcery_file_m sourcery_file_m module~training_configuration_m->sourcery_file_m sourcery_string_m sourcery_string_m module~training_configuration_m->sourcery_string_m module~activation_strategy_m activation_strategy_m module~differentiable_activation_strategy_m->module~activation_strategy_m module~hyperparameters_m->module~kind_parameters_m module~hyperparameters_m->sourcery_string_m module~network_configuration_m->sourcery_string_m module~activation_strategy_m->module~kind_parameters_m module~activation_strategy_m->sourcery_string_m

Used by

  • module~~training_configuration_m~~UsedByGraph module~training_configuration_m training_configuration_m module~inference_engine_m inference_engine_m module~inference_engine_m->module~training_configuration_m module~trainable_engine_m trainable_engine_m module~inference_engine_m->module~trainable_engine_m module~trainable_engine_m->module~training_configuration_m module~training_configuration_s training_configuration_s module~training_configuration_s->module~training_configuration_m module~training_configuration_s->module~inference_engine_m module~addition_m addition_m module~addition_m->module~inference_engine_m module~exponentiation_m exponentiation_m module~exponentiation_m->module~inference_engine_m module~multiply_inputs multiply_inputs module~multiply_inputs->module~inference_engine_m module~power_series power_series module~power_series->module~inference_engine_m module~saturated_mixing_ratio_m saturated_mixing_ratio_m module~saturated_mixing_ratio_m->module~inference_engine_m module~thompson_tensors_m thompson_tensors_m module~thompson_tensors_m->module~inference_engine_m module~trainable_engine_s trainable_engine_s module~trainable_engine_s->module~trainable_engine_m program~concurrent_inferences concurrent_inferences program~concurrent_inferences->module~inference_engine_m program~learn_addition learn_addition program~learn_addition->module~inference_engine_m program~learn_addition->module~addition_m program~learn_exponentiation learn_exponentiation program~learn_exponentiation->module~inference_engine_m program~learn_exponentiation->module~exponentiation_m program~learn_microphysics_procedures learn_microphysics_procedures program~learn_microphysics_procedures->module~inference_engine_m program~learn_microphysics_procedures->module~thompson_tensors_m program~learn_multiplication learn_multiplication program~learn_multiplication->module~inference_engine_m program~learn_multiplication->module~multiply_inputs program~learn_power_series learn_power_series program~learn_power_series->module~inference_engine_m program~learn_power_series->module~power_series program~print_training_configuration print_training_configuration program~print_training_configuration->module~inference_engine_m program~train_and_write train_and_write program~train_and_write->module~inference_engine_m program~train_saturated_mixture_ratio train_saturated_mixture_ratio program~train_saturated_mixture_ratio->module~inference_engine_m program~train_saturated_mixture_ratio->module~saturated_mixing_ratio_m program~write_read_infer write_read_infer program~write_read_infer->module~inference_engine_m

Interfaces

public interface training_configuration_t

interface

interface

interface

  • private elemental module function learning_rate(self) result(rate)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value real(kind=rkind)

interface

  • private elemental module function mini_batches(self) result(num_mini_batches)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value integer

interface

  • private pure module function nodes_per_layer(self) result(nodes)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value integer, allocatable, (:)

interface

  • private elemental module function optimizer_name(self) result(identifier)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value type(string_t)

interface

  • private elemental module function skip_connections(self) result(using_skip)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value logical

interface

  • private pure module function to_json(self) result(json_lines)

    Arguments

    Type IntentOptional Attributes Name
    class(training_configuration_t), intent(in) :: self

    Return Value type(string_t), allocatable, (:)


Derived Types

type, public, extends(file_t) ::  training_configuration_t

Components

Type Visibility Attributes Name Initial
type(hyperparameters_t), private :: hyperparameters_
type(network_configuration_t), private :: network_configuration_

Constructor

private module function from_components (hyperparameters, network_configuration)
private module function from_file (file_object)

Type-Bound Procedures

procedure, public :: differentiable_activation_strategy
procedure, public :: equals
procedure, public :: learning_rate
procedure, public :: mini_batches
procedure, public :: nodes_per_layer
generic, public :: operator(==) => equals
procedure, public :: optimizer_name
procedure, public :: skip_connections
procedure, public :: to_json