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build(random_init): rm final nagfor workaround #136

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Mar 29, 2024
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build(random_init): rm final nagfor workaround #136

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32efae6
build(random_init): rm final nagfor workaround
rouson Mar 28, 2024
c72c8e0
test(main): no auto preprocessing main test prog
rouson Mar 28, 2024
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3 changes: 0 additions & 3 deletions example/learn-addition.F90
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Expand Up @@ -47,10 +47,7 @@ program learn_addition
type(bin_t), allocatable :: bins(:)
real, allocatable :: cost(:), random_numbers(:)

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

trainable_engine = perturbed_identity_network(perturbation_magnitude=0.05)
call output(trainable_engine%to_inference_engine(), string_t("initial-network.json"))

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3 changes: 0 additions & 3 deletions example/learn-exponentiation.F90
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Expand Up @@ -47,10 +47,7 @@ program learn_exponentiation
type(bin_t), allocatable :: bins(:)
real, allocatable :: cost(:), random_numbers(:)

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

trainable_engine = perturbed_identity_network(perturbation_magnitude=0.05)
call output(trainable_engine%to_inference_engine(), string_t("initial-network.json"))

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3 changes: 0 additions & 3 deletions example/learn-microphysics-procedures.F90
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Expand Up @@ -39,10 +39,7 @@ program learn_microphysics_procedures
integer, parameter :: nodes_per_layer(*) = [2, 72, 2]
real, parameter :: cost_tolerance = 1.E-08

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

open(newunit=network_unit, file=network_file%string(), form='formatted', status='old', iostat=io_status, action='read')

if (io_status == io_success) then
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3 changes: 0 additions & 3 deletions example/learn-multiplication.F90
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Expand Up @@ -47,10 +47,7 @@ program learn_multiplication
type(bin_t), allocatable :: bins(:)
real, allocatable :: cost(:), random_numbers(:)

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

trainable_engine = perturbed_identity_network(perturbation_magnitude=0.05)
call output(trainable_engine%to_inference_engine(), string_t("initial-network.json"))

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3 changes: 0 additions & 3 deletions example/learn-power-series.f90
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Expand Up @@ -47,10 +47,7 @@ program learn_power_series
type(bin_t), allocatable :: bins(:)
real, allocatable :: cost(:), random_numbers(:)

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

trainable_engine = perturbed_identity_network(perturbation_magnitude=0.05)
call output(trainable_engine%to_inference_engine(), string_t("initial-network.json"))

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3 changes: 0 additions & 3 deletions example/learn-saturated-mixing-ratio.F90
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Expand Up @@ -38,10 +38,7 @@ program train_saturated_mixture_ratio
integer, parameter :: nodes_per_layer(*) = [2, 72, 1]
real, parameter :: cost_tolerance = 1.E-08

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

open(newunit=network_unit, file=network_file%string(), form='formatted', status='old', iostat=io_status, action='read')

if (io_status == io_success) then
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3 changes: 0 additions & 3 deletions example/train-and-write.F90
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Expand Up @@ -34,10 +34,7 @@ program train_and_write
type(bin_t), allocatable :: bins(:)
real, allocatable :: cost(:), random_numbers(:)

#ifndef NAGFOR
call random_init(image_distinct=.true., repeatable=.true.)
#endif

trainable_engine = perturbed_identity_network(perturbation_magnitude=0.2)
call output(trainable_engine%to_inference_engine(), string_t("initial-network.json"))

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2 changes: 0 additions & 2 deletions test/main.F90 → test/main.f90
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Expand Up @@ -20,9 +20,7 @@ program main
integer :: passes=0, tests=0

call cpu_time(t_start)
#ifndef NAGFOR
call random_init(repeatable=.true.,image_distinct=.true.)
#endif
call hyperparameters_test%report(passes, tests)
call network_configuration_test%report(passes, tests)
call training_configuration_test%report(passes, tests)
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