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)