! Copyright (c), The Regents of the University of California ! Terms of use are as specified in LICENSE.txt program print_training_configuration !! Demonstrate how to construct and print a training_configuration_t object use fiats_m, only : training_configuration_t, hyperparameters_t, network_configuration_t, tensor_names_t use julienne_m, only : file_t, string_t implicit none #ifndef _CRAYFTN associate(training_configuration => training_configuration_t( & hyperparameters_t(mini_batches=10, learning_rate=1.5, optimizer = "adam") & ,network_configuration_t(skip_connections=.false., nodes_per_layer=[2,72,2], activation_name="sigmoid") & ,tensor_names_t(inputs = [string_t("pressure"), string_t("temperature")], outputs = ([string_t("saturated mixing ratio")])) & )) associate(json_file => file_t(training_configuration%to_json())) call json_file%write_lines() end associate end associate #else block type(training_configuration_t) :: training_configuration type(file_t) :: json_file training_configuration = training_configuration_t( & hyperparameters_t(mini_batches=10, learning_rate=1.5, optimizer = "adam") & ,network_configuration_t(skip_connections=.false., nodes_per_layer=[2,72,2], activation_name="sigmoid") & ,tensorm_names_t(inputs=[string_t("pressure"), string_t("temperature")], outputs([string_t("saturated mixing ratio")])) & ) json_file = file_t(training_configuration%to_json()) call json_file%write_lines() end block #endif end program