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())