def do_continue(self, line): ''' Will continue the training of the currently selected model ''' if not self.has_model_selected(): print 'please select or create a model' return False m = ModelManager(self.prompt[:-1]) state = m.load_current_state(add_hidden=True) model = m.load_currently_selected_model() train.train2(m, state, model)
def do_train(self, line): ''' Will start the training using the configuration stored in state.txt ''' if not self.has_model_selected(): print 'please select or create a model' return False parser = argparse.ArgumentParser() parser.add_argument('-gui', action='store_true', help='The size of the training set given by a floating point number between 0 and 1.', default=False) args = parser.parse_args(line) m = ModelManager(self.prompt[:-1]) state = m.load_current_state(add_hidden=True) train.train2(m, state, None) print