def create_model():
# the data, shuffled and split between tran and test sets
(X_train, y_train), (X_test, y_test) = load_data()
print('X_train shape:', X_train.shape)
print(X_train.shape[0], 'train samples')
print(X_test.shape[0], 'test samples')
# convert class vectors to binary class matrices
Y_train = np_utils.to_categorical(y_train, nb_classes)
Y_test = np_utils.to_categorical(y_test, nb_classes)
print("starting model")
model.save_weights(temp_file_name,overwrite=True)
with open(temp_file_name) as f:
store_to_s3(str(int(time.time())), f.read())
def save_data():
model.save_weights(temp_file_name, overwrite=True)
with open(temp_file_name, 'r') as f:
store_to_s3(str(int(time.time())),f.read())
