os.environ['PYTHONHASHSEED'] = '0' # necessary for py3 tf.set_random_seed(100) session_conf = tf.ConfigProto(intra_op_parallelism_threads=1, inter_op_parallelism_threads=1) session_conf.gpu_options.allow_growth = True session_conf.gpu_options.visible_device_list = '2' sess = tf.Session(graph=tf.get_default_graph(), config=session_conf) K.set_session(sess) ################################################################### if __name__ == '__main__': mkdir(PATH) currentPython = sys.argv[0] shutil.copy2(currentPython, PATH) shutil.copy2('DeepSTN_net.py', PATH) shutil.copy2('load_data_DSTN.py', PATH) shutil.copy2('Param_DSTN_flow.py', PATH) StartTime = datetime.datetime.now().strftime('%Y%m%d_%H%M%S') print('#' * 50) print('start running at {}'.format(StartTime)) print('model name: {}'.format(MODELNAME)) print('#' * 50, '\n') X_train, Y_train, X_test, Y_test = load_data(len_closeness, len_period, len_trend, T_closeness, T_period, T_trend) model = train_model(X_train, Y_train) test_model(X_test, Y_test, model)
np.random.seed(100) random.seed(100) os.environ['PYTHONHASHSEED'] = '0' # necessary for py3 tf.set_random_seed(100) session_conf = tf.ConfigProto(intra_op_parallelism_threads=1, inter_op_parallelism_threads=1) session_conf.gpu_options.allow_growth = True session_conf.gpu_options.visible_device_list = '1' sess = tf.Session(graph=tf.get_default_graph(), config=session_conf) K.set_session(sess) ################################################################### if __name__ == '__main__': mkdir(PATH) currentPython = sys.argv[0] shutil.copy2(currentPython, PATH) shutil.copy2('DeepSTN_net.py', PATH) shutil.copy2('load_data_DSTN.py', PATH) shutil.copy2('Param_DSTN_flow.py', PATH) StartTime = datetime.datetime.now().strftime('%Y%m%d_%H%M%S') print('#' * 50) print('start running at {}'.format(StartTime)) print('model name: {}'.format(MODELNAME)) print('#' * 50, '\n') X_train, Y_train, X_test, Y_test = load_data() model = train_model(X_train, Y_train) test_model(X_test, Y_test, model)