swish_m Module


Uses

  • module~~swish_m~~UsesGraph module~swish_m swish_m module~differentiable_activation_strategy_m differentiable_activation_strategy_m module~swish_m->module~differentiable_activation_strategy_m module~kind_parameters_m kind_parameters_m module~swish_m->module~kind_parameters_m sourcery_string_m sourcery_string_m module~swish_m->sourcery_string_m module~activation_strategy_m activation_strategy_m module~differentiable_activation_strategy_m->module~activation_strategy_m module~activation_strategy_m->module~kind_parameters_m module~activation_strategy_m->sourcery_string_m

Used by

  • module~~swish_m~~UsedByGraph module~swish_m swish_m module~inference_engine_m inference_engine_m module~inference_engine_m->module~swish_m module~inference_engine_s inference_engine_s module~inference_engine_s->module~swish_m module~swish_s swish_s module~swish_s->module~swish_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~training_configuration_s training_configuration_s module~training_configuration_s->module~inference_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

interface

  • private elemental module function activation(x) result(y)

    Arguments

    Type IntentOptional Attributes Name
    real(kind=rkind), intent(in) :: x

    Return Value real(kind=rkind)

interface

  • private elemental module function activation_derivative(x) result(y)

    Arguments

    Type IntentOptional Attributes Name
    real(kind=rkind), intent(in) :: x

    Return Value real(kind=rkind)

interface

  • private elemental module function function_name(self) result(string)

    Arguments

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

    Return Value type(string_t)


Derived Types

type, public, extends(differentiable_activation_strategy_t) ::  swish_t

Type-Bound Procedures

procedure, public, nopass :: activation
procedure, public, nopass :: activation_derivative
procedure, public :: function_name