tensor_m Module


Uses

  • module~~tensor_m~~UsesGraph module~tensor_m tensor_m module~kind_parameters_m kind_parameters_m module~tensor_m->module~kind_parameters_m

Used by

  • module~~tensor_m~~UsedByGraph module~tensor_m tensor_m module~fiats_m fiats_m module~fiats_m->module~tensor_m module~input_output_pair_m input_output_pair_m module~fiats_m->module~input_output_pair_m module~neural_network_m neural_network_m module~fiats_m->module~neural_network_m module~tensor_map_m tensor_map_m module~fiats_m->module~tensor_map_m module~mini_batch_m mini_batch_m module~fiats_m->module~mini_batch_m module~trainable_network_m trainable_network_m module~fiats_m->module~trainable_network_m module~input_output_pair_m->module~tensor_m module~neural_network_m->module~tensor_m module~neural_network_m->module~tensor_map_m module~neural_network_m->module~mini_batch_m module~tensor_map_m->module~tensor_m module~tensor_s tensor_s module~tensor_s->module~tensor_m module~addition_m addition_m module~addition_m->module~fiats_m module~exponentiation_m exponentiation_m module~exponentiation_m->module~fiats_m module~input_output_pair_s input_output_pair_s module~input_output_pair_s->module~input_output_pair_m module~layer_m layer_m module~layer_m->module~neural_network_m module~layer_m->module~tensor_map_m module~mini_batch_m->module~input_output_pair_m module~multiply_inputs multiply_inputs module~multiply_inputs->module~fiats_m module~neural_network_s neural_network_s module~neural_network_s->module~neural_network_m module~neural_network_s->module~layer_m module~power_series power_series module~power_series->module~fiats_m module~saturated_mixing_ratio_m saturated_mixing_ratio_m module~saturated_mixing_ratio_m->module~fiats_m module~tensor_map_s tensor_map_s module~tensor_map_s->module~tensor_map_m module~trainable_network_m->module~input_output_pair_m module~trainable_network_m->module~neural_network_m module~trainable_network_m->module~tensor_map_m module~trainable_network_m->module~mini_batch_m module~unmapped_network_s unmapped_network_s module~unmapped_network_s->module~neural_network_m module~workspace_s workspace_s module~workspace_s->module~neural_network_m program~concurrent_inferences concurrent_inferences program~concurrent_inferences->module~fiats_m program~learn_addition learn_addition program~learn_addition->module~fiats_m program~learn_addition->module~addition_m program~learn_exponentiation learn_exponentiation program~learn_exponentiation->module~fiats_m program~learn_exponentiation->module~exponentiation_m program~learn_multiplication learn_multiplication program~learn_multiplication->module~fiats_m program~learn_multiplication->module~multiply_inputs program~learn_power_series learn_power_series program~learn_power_series->module~fiats_m program~learn_power_series->module~power_series program~print_training_configuration print_training_configuration program~print_training_configuration->module~fiats_m program~read_query_infer read_query_infer program~read_query_infer->module~fiats_m program~train_and_write train_and_write program~train_and_write->module~fiats_m program~train_saturated_mixture_ratio train_saturated_mixture_ratio program~train_saturated_mixture_ratio->module~fiats_m program~train_saturated_mixture_ratio->module~saturated_mixing_ratio_m program~write_read_infer write_read_infer program~write_read_infer->module~fiats_m module~layer_s layer_s module~layer_s->module~layer_m module~mini_batch_s mini_batch_s module~mini_batch_s->module~mini_batch_m module~trainable_network_s trainable_network_s module~trainable_network_s->module~trainable_network_m

Interfaces

public interface tensor_t

  • private pure module function construct_default_real(values) result(tensor)

    Arguments

    Type IntentOptional Attributes Name
    real, intent(in) :: values(:)

    Return Value type(tensor_t)

  • private pure module function construct_double_precision(values) result(tensor)

    Arguments

    Type IntentOptional Attributes Name
    double precision, intent(in) :: values(:)

    Return Value type(tensor_t(double_precision))

interface

  • private pure module function default_real_num_components(self) result(n)

    Arguments

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

    Return Value integer

interface

  • private pure module function default_real_values(self) result(tensor_values)

    Arguments

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

    Return Value real, allocatable, (:)

interface

  • private pure module function double_precision_num_components(self) result(n)

    Arguments

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

    Return Value integer

interface

  • private pure module function double_precision_values(self) result(tensor_values)

    Arguments

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

    Return Value double precision, allocatable, (:)


Derived Types

type, public ::  tensor_t

Components

Type Visibility Attributes Name Initial
integer, public, kind :: k = default_real
real(kind=k), private, allocatable :: values_(:)

Constructor

private pure, module function construct_default_real (values)
private pure, module function construct_double_precision (values)

Type-Bound Procedures

generic, public :: num_components => default_real_num_components, double_precision_num_components
generic, public :: values => default_real_values, double_precision_values
procedure, private :: default_real_num_components
procedure, private, non_overridable :: default_real_values
procedure, private :: double_precision_num_components
procedure, private, non_overridable :: double_precision_values