681ba0538258bacd75c54b83d383ef1c7057a759,main.py,,run_training,#,40

Before Change

    data_sets = input_data.read_data_sets(FLAGS.train_dir, FLAGS.fake_data)
    best_geometry = brute_force_optimal_network_geometry(data_sets, FLAGS.training_precision)
    print(best_geometry)
    start_time = time.time()
    with tf.Graph().as_default():
        graph = MNISTGraph(
            learning_rate=FLAGS.learning_rate,
            hidden1=best_geometry[3][0], hidden2=best_geometry[3][1], hidden3=best_geometry[3][2],
            batch_size=FLAGS.batch_size, train_dir=FLAGS.train_dir
        )
        graph.train(data_sets, FLAGS.max_steps, precision=FLAGS.desired_precision)
        print(time.time()-start_time, graph.precision, graph.step)

def brute_force_optimal_network_geometry(data_sets, desired_precision, max_steps=10000):
    results = []

After Change

    best_geometry = brute_force_optimal_network_geometry(data_sets, FLAGS.training_precision)
    print(best_geometry)

    graph, timing_info = timed_run(run_final_training, best_geometry, data_sets)

    print(timing_info, graph.precision, graph.step)

Instances