def _finish_setting(self) -> [[int]]:
'''when the user input the necessary value for the game, store all the values and draw the game board'''
dialog = settings.Setting()
dialog.show()
if dialog.was_ok_clicked():
# get settings of the game
self._rows = dialog.get_rows()
self._columns = dialog.get_columns()
self._whose_turn = dialog.get_whose_turn()
self._tp_position = dialog.get_tp_position()
self._win_rule = dialog.get_win_rule()
# now layout the game board
self._remind_text.set('You can play now !')
self._turn_text.set('TURN: {}'.format(self._whose_turn))
self._lines = self._all_lines(self._columns, self._rows)
self._p = discs_model.Position(self._rows, self._columns, HEIGHT,
WIDTH,
transfer_str(self._tp_position))
self._board = discs_model.new_board(self._p)
self._state = discs_model.build_new_state(
self._p, transfer_str(self._whose_turn))
self._amount_text.set('Black: {} White: {}'.format(
self._state.find_black(), self._state.find_white()))
self._redraw_all_discs()
def test_Load(self):
# Ensure we can enumerate the keys from the settings
self.assertGreater(len(settings.Setting.Keys._keys()), 0,
"Enumerating all keys returns non-zero list")
# Assert loading settings-default.json works
self.assertEqual(settings.Setting.Filename(), 'settings-default.json')
# Ensure all settings-default.json keys are in default keys
defaults = settings.Setting.Defaults()
defaultPrefsJson = json.load(open(settings.Setting.Filename()))
for jsonKey, v in defaultPrefsJson.iteritems():
self.assertTrue(jsonKey in defaults)
# Check that loading a file and converging work
converged = settings.Setting().ConvergedDefaults()
for covKey, covVal in converged.iteritems():
self.assertTrue(covKey in defaults)
# Check that no defaults were dropped off
for dKey, dVal in defaults.iteritems():
self.assertTrue(dKey in converged)
# And now ensure thre are no extra keys
self.assertEqual(len(converged), len(defaults))
model.compile(optimizer=self.optimizer, loss=['categorical_crossentropy'], metrics=['accuracy'])
checkpoint_dir = "models/" + str(int(time.time())) + '/'
if not os.path.exists(checkpoint_dir):
os.makedirs(checkpoint_dir)
STAMP = 'lstm_%d_%d_%.1f' % (self.lstm_dim, self.dense_dim, self.drop_prob)
filepath= checkpoint_dir + STAMP + "_%s_{val_acc:.2f}.h5"%source_language
checkpoint = ModelCheckpoint(filepath, monitor='val_acc', verbose=1, save_best_only=True, save_weights_only=True, mode='max')
lr_sched = ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=1, cooldown=1, verbose=1)
early_stopping = EarlyStopping(monitor='val_acc', patience=10)
model.fit([train_X, train_Y], [train_Z],
validation_data = ([val_X, val_Y], [val_Z]),
epochs=self.epochs, batch_size = self.batch_size, shuffle = True,
callbacks=[checkpoint, lr_sched, early_stopping])
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--source_language', type=str, default='es', help='source_language')
params = parser.parse_args()
setting = settings.Setting()
Tars = NLImodel(setting)
Tars.train_model(params.source_language)
def __init__(self):
self.settings = settings.Setting().ConvergedDefaults()
self.settings['consoletitle'] = True
def method(method, color, color2):
setting = settings.Setting()
setting.setColors(color, color2)
setting.setSetting(method)
return "Empty"
def __init__(self):
self.settings = settings.Setting().ConvergedDefaults()