import tensorflow as tf

    def standardization(x):
        x_reshaped = x.reshape([x.shape[0], -1])
        result = (x_reshaped - train_X_means) / (train_X_stds + 1e-9)
        return result.reshape(x.shape)

    normalized_test_X = standardization(test_X)

    with tf.Session() as sess, tf.summary.FileWriter(
            "./tf_logs/fashion_minst_multi_task_learning/" + str(datetime.now().timestamp()),
            graph=tf.get_default_graph()) as f:
        sess.run(tf.global_variables_initializer())

        # similar logic as mnist's next_batch()
        epoch = 0
