def main(_):
global TOTAL, ID_LENGTH
if not os.path.exists(TRAIN_FILE):
music.main()
# Import data
with open(TRAIN_FILE, 'r') as file:
data = json.load(file)
data_train = data["train"]
data_test = data["test"]
iddict = data["keys"]
# Length of input
TOTAL = len(data_train[0][0])
# Length of output
ID_LENGTH = len(data_train[0][1])
# Create the model
x = tf.placeholder(tf.float32, [None, TOTAL])
# Define loss and optimizer
y_ = tf.placeholder(tf.float32, [None, ID_LENGTH])
# Build the graph for the deep net
y_conv = deepnn(x)
with tf.name_scope('loss'):
cross_entropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_,
logits=y_conv)
cross_entropy = tf.reduce_mean(cross_entropy)
with tf.name_scope('adam_optimizer'):
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
with tf.name_scope('accuracy'):
correct_prediction = tf.equal(tf.argmax(y_conv, 1), tf.argmax(y_, 1))
correct_prediction = tf.cast(correct_prediction, tf.float32)
accuracy = tf.reduce_mean(correct_prediction)
graph_location = tempfile.mkdtemp()
print('Saving graph to: %s' % graph_location)
train_writer = tf.summary.FileWriter(graph_location)
train_writer.add_graph(tf.get_default_graph())
with tf.Session() as sess:
sess.run(tf.global_variables_initializer())
for i in range(10000):
inds = npr.randint(len(data_train), size=10)
batch = [data_train[i] for i in inds]
left = [entry[0] for entry in batch]
right = [entry[1] for entry in batch]
if i % 100 == 0:
train_accuracy = accuracy.eval(feed_dict={x: left, y_: right})
print('step %d, training accuracy %g' % (i, train_accuracy))
train_step.run(feed_dict={x: left, y_: right})
left = [entry[0] for entry in data_test]
right = [entry[1] for entry in data_test]
print('test accuracy: ', accuracy.eval(feed_dict={x: left, y_: right}))
def music_recs():
music.main()
def ya_music(user_id, body, counter):
track = music.main(body)
if track == "YmdlWrongUrlError":
write(user_id, "Неправильный url.")
else:
file_send(user_id, track, counter, music=True)
def exit():
with open('working.pcl', 'wb') as f:
pickle.dump(finalList, f)
f.close()
root.destroy()
main()
def doMenuItem(current):
#menuList = ["About", "Snake", "Flappy Bird", "Simon", "Breakout", "Music Box", "2048", "LED Fun", "Test All", Files]
if current == 0:
about()
elif current == 1:
import snake
snake.main(gg)
del sys.modules['snake']
gc.collect()
drawMenu(current)
elif current == 2:
import flappy
flappy.main(gg)
del sys.modules['flappy']
gc.collect()
drawMenu(2)
elif current == 3:
import simon
simon.main(gg)
del sys.modules['simon']
gc.collect()
drawMenu(3)
elif current == 4:
import AnimeBreakout
AnimeBreakout.main(gg)
del sys.modules['AnimeBreakout']
gc.collect()
drawMenu(current)
elif current == 5:
import music
music.main(gg)
del sys.modules['music']
gc.collect()
drawMenu(current)
elif current == 6:
import g2048
g2048.main(gg)
del sys.modules['g2048']
gc.collect()
drawMenu(current)
elif current == 7:
testLEDs()
elif current == 8:
testAll()
elif current == 9:
showFiles()
elif current == 10:
showOS()
elif current == 11:
import machine
machine.reset()
elif current == 12:
utime.sleep_ms(200)
if gg.playSound:
menuList[12] = "Sound: Off"
gg.playSound = False
else:
menuList[12] = "Sound: On"
gg.playSound = True
gg.beep()
utime.sleep_ms(25)
gg.lowBeep()
utime.sleep_ms(25)
gg.beep()
utime.sleep_ms(200)
drawMenu(current)
gc.collect()