def test(name, words, files): class_count = len(files) x, y, y_ = th.setup((len(words)), class_count) saver = tf.train.Saver() with tf.Session() as sess: sess.run(tf.initialize_all_variables()) saver.restore(sess, name) print("Model restored") lines, inputs = load.load_test_data(words) for i in range(len(lines)): line = lines[i] inp = inputs[i] result = sess.run(y, feed_dict={x: inp}) m = 0.0 class_index = 0 for i in range(len(result[0])): r = result[0][i] if r > m: m = r class_index = i print("Test data " + line + " : " + files[class_index] + " : " + str(result) + " : ")
import sys print("Init..") model_name = "model.ckpt" epochs = 2 if "e" in sys.argv: epochs = int(sys.argv[sys.argv.index("e")+1]) files = [] files.append("mute") files.append("volume") files.append("channel") print("Files: " + ", ".join(files)) print("Loading data..") inputs, outputs, words = load.load_data(files) if "t" in sys.argv: print("Setup train..") sess = tf.InteractiveSession() x, y, y_ = th.setup(len(words), len(files)) train_step, writer, merged, accuracy = th.trainSetup(y, y_, sess) print("Train..") th.train(inputs, outputs, x, y_, train_step, sess, epochs, writer, merged, accuracy) print("Save..") th.save(sess, model_name) else: print("Test..") test.test(model_name, words, files)