write_read_infer Program

Uses

  • program~~write_read_infer~~UsesGraph program~write_read_infer write_read_infer module~inference_engine_m inference_engine_m program~write_read_infer->module~inference_engine_m module~kind_parameters_m kind_parameters_m program~write_read_infer->module~kind_parameters_m sourcery_m sourcery_m program~write_read_infer->sourcery_m module~inference_engine_m->module~kind_parameters_m module~activation_strategy_m activation_strategy_m module~inference_engine_m->module~activation_strategy_m module~differentiable_activation_strategy_m differentiable_activation_strategy_m module~inference_engine_m->module~differentiable_activation_strategy_m module~hyperparameters_m hyperparameters_m module~inference_engine_m->module~hyperparameters_m module~inference_engine_m_ inference_engine_m_ module~inference_engine_m->module~inference_engine_m_ module~input_output_pair_m input_output_pair_m module~inference_engine_m->module~input_output_pair_m module~mini_batch_m mini_batch_m module~inference_engine_m->module~mini_batch_m module~network_configuration_m network_configuration_m module~inference_engine_m->module~network_configuration_m module~relu_m relu_m module~inference_engine_m->module~relu_m module~sigmoid_m sigmoid_m module~inference_engine_m->module~sigmoid_m module~step_m step_m module~inference_engine_m->module~step_m module~swish_m swish_m module~inference_engine_m->module~swish_m module~tensor_m tensor_m module~inference_engine_m->module~tensor_m module~tensor_range_m tensor_range_m module~inference_engine_m->module~tensor_range_m module~trainable_engine_m trainable_engine_m module~inference_engine_m->module~trainable_engine_m module~training_configuration_m training_configuration_m module~inference_engine_m->module~training_configuration_m module~ubounds_m ubounds_m module~inference_engine_m->module~ubounds_m module~activation_strategy_m->module~kind_parameters_m sourcery_string_m sourcery_string_m module~activation_strategy_m->sourcery_string_m module~differentiable_activation_strategy_m->module~activation_strategy_m module~hyperparameters_m->module~kind_parameters_m module~hyperparameters_m->sourcery_string_m module~inference_engine_m_->module~kind_parameters_m module~inference_engine_m_->module~activation_strategy_m module~inference_engine_m_->module~differentiable_activation_strategy_m module~inference_engine_m_->module~tensor_m module~inference_engine_m_->module~tensor_range_m sourcery_file_m sourcery_file_m module~inference_engine_m_->sourcery_file_m module~inference_engine_m_->sourcery_string_m module~input_output_pair_m->module~kind_parameters_m module~input_output_pair_m->module~tensor_m module~mini_batch_m->module~kind_parameters_m module~mini_batch_m->module~input_output_pair_m module~network_configuration_m->sourcery_string_m module~relu_m->module~kind_parameters_m module~relu_m->module~differentiable_activation_strategy_m module~relu_m->sourcery_string_m module~sigmoid_m->module~kind_parameters_m module~sigmoid_m->module~differentiable_activation_strategy_m module~sigmoid_m->sourcery_string_m module~step_m->module~kind_parameters_m module~step_m->module~activation_strategy_m module~step_m->sourcery_string_m module~swish_m->module~kind_parameters_m module~swish_m->module~differentiable_activation_strategy_m module~swish_m->sourcery_string_m module~tensor_m->module~kind_parameters_m module~tensor_range_m->sourcery_m module~tensor_range_m->module~tensor_m module~trainable_engine_m->module~kind_parameters_m module~trainable_engine_m->module~differentiable_activation_strategy_m module~trainable_engine_m->module~inference_engine_m_ module~trainable_engine_m->module~mini_batch_m module~trainable_engine_m->module~tensor_m module~trainable_engine_m->module~tensor_range_m module~trainable_engine_m->module~training_configuration_m module~trainable_engine_m->sourcery_string_m module~training_configuration_m->module~kind_parameters_m module~training_configuration_m->module~differentiable_activation_strategy_m module~training_configuration_m->module~hyperparameters_m module~training_configuration_m->module~network_configuration_m module~training_configuration_m->sourcery_file_m module~training_configuration_m->sourcery_string_m

This program demonstrates how to write a neural network to a JSON file, read the same network from the written file, query the network object for some of its properties, print those properties, and use the network to perform inference. The network performs an identity mapping from any non-negative inputs to the corresponding outputs using a RELU activation function.


Calls

program~~write_read_infer~~CallsGraph program~write_read_infer write_read_infer flag_value flag_value program~write_read_infer->flag_value proc~write_read_query_infer write_read_query_infer program~write_read_infer->proc~write_read_query_infer string string program~write_read_infer->string string_t string_t program~write_read_infer->string_t proc~write_read_query_infer->string file_t file_t proc~write_read_query_infer->file_t interface~activation_function_name inference_engine_t%activation_function_name proc~write_read_query_infer->interface~activation_function_name interface~infer~2 inference_engine_t%infer proc~write_read_query_infer->interface~infer~2 interface~nodes_per_layer~3 inference_engine_t%nodes_per_layer proc~write_read_query_infer->interface~nodes_per_layer~3 interface~num_inputs~3 inference_engine_t%num_inputs proc~write_read_query_infer->interface~num_inputs~3 interface~num_outputs~2 inference_engine_t%num_outputs proc~write_read_query_infer->interface~num_outputs~2 interface~to_json~5 inference_engine_t%to_json proc~write_read_query_infer->interface~to_json~5 interface~values tensor_t%values proc~write_read_query_infer->interface~values proc~identity_network identity_network proc~write_read_query_infer->proc~identity_network write_lines write_lines proc~write_read_query_infer->write_lines proc~identity_network->string_t

Variables

Type Attributes Name Initial
type(command_line_t) :: command_line
type(string_t) :: file_name

Functions

function identity_network() result(inference_engine)

Arguments

None

Return Value type(inference_engine_t)


Subroutines

subroutine write_read_query_infer(output_file_name)

Arguments

Type IntentOptional Attributes Name
type(string_t), intent(in) :: output_file_name