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)
