concurrent_inferences Program

Uses

  • program~~concurrent_inferences~~UsesGraph program~concurrent_inferences concurrent_inferences assert_m assert_m program~concurrent_inferences->assert_m iso_fortran_env iso_fortran_env program~concurrent_inferences->iso_fortran_env module~inference_engine_m inference_engine_m program~concurrent_inferences->module~inference_engine_m sourcery_m sourcery_m program~concurrent_inferences->sourcery_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~kind_parameters_m kind_parameters_m module~inference_engine_m->module~kind_parameters_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~activation_strategy_m module~inference_engine_m_->module~differentiable_activation_strategy_m module~inference_engine_m_->module~kind_parameters_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~input_output_pair_m module~mini_batch_m->module~kind_parameters_m module~network_configuration_m->sourcery_string_m module~relu_m->module~differentiable_activation_strategy_m module~relu_m->module~kind_parameters_m module~relu_m->sourcery_string_m module~sigmoid_m->module~differentiable_activation_strategy_m module~sigmoid_m->module~kind_parameters_m module~sigmoid_m->sourcery_string_m module~step_m->module~activation_strategy_m module~step_m->module~kind_parameters_m module~step_m->sourcery_string_m module~swish_m->module~differentiable_activation_strategy_m module~swish_m->module~kind_parameters_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~differentiable_activation_strategy_m module~trainable_engine_m->module~inference_engine_m_ module~trainable_engine_m->module~kind_parameters_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~differentiable_activation_strategy_m module~training_configuration_m->module~hyperparameters_m module~training_configuration_m->module~kind_parameters_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 read a neural network from a JSON file and use the network to perform concurrent inferences.


Calls

program~~concurrent_inferences~~CallsGraph program~concurrent_inferences concurrent_inferences assert assert program~concurrent_inferences->assert file_t file_t program~concurrent_inferences->file_t flag_value flag_value program~concurrent_inferences->flag_value infer infer program~concurrent_inferences->infer input_components input_components program~concurrent_inferences->input_components inputs inputs program~concurrent_inferences->inputs num_inputs num_inputs program~concurrent_inferences->num_inputs outputs outputs program~concurrent_inferences->outputs string string program~concurrent_inferences->string string_t string_t program~concurrent_inferences->string_t

Variables

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