python使用loaddata_Python data.load_data方法代码示例

# 需要导入模块: import data [as 别名]

# 或者: from data import load_data [as 别名]

def run_lstm(model, sequence_length, prediction_steps):

data = None

global_start_time = time.time()

epochs = 1

ratio_of_data = 1 # ratio of data to use from 2+ million data points

path_to_dataset = 'data/household_power_consumption.txt'

if data is None:

print('Loading data... ')

x_train, y_train, x_test, y_test, result_mean = load_data(path_to_dataset, sequence_length,

prediction_steps, ratio_of_data)

else:

x_train, y_train, x_test, y_test = data

print('\nData Loaded. Compiling...\n')

if model is None:

model = build_model(prediction_steps)

try:

model.fit(x_train, y_train, batch_size=128, epochs=epochs, validation_split=0.05)

predicted = model.predict(x_test)

# predicted = np.reshape(predicted, (predicted.size,))

model.save('LSTM_power_consumption_model.h5') # save LSTM model

except KeyboardInterrupt: # save model if training interrupted by user

print('Duration of training (s) : ', time.time() - global_start_time)

model.save('LSTM_power_consumption_model.h5')

return model, y_test, 0

else: # previously trained mode is given

print('Loading model...')

predicted = model.predict(x_test)

plot_predictions(result_mean, prediction_steps, predicted, y_test, global_start_time)

return None