使用lstm做时间序列预测时，我的数据得timestep为50，每个样例的特征是6维，在数据定义时fluid.layers.data(name='x', shape=[1], dtype='float32', lod_level=1)，我想根据这个序列数据预测一个类别，因此标签定义为fluid.layers.data(name='y', shape=[1], dtype='int64') ， 但是提示错误

InvalidArgumentError: After flatten the input tensor X and Y to 2-D dimensions matrix X1 and Y1, the matrix X1's width must be equal with matrix Y1's height. But received X's shape = [25600, 6], X1's shape = [25600, 6], X1's width = 6; Y's shape = [1, 200], Y1's shape = [1, 200], Y1's height = 1.
[Hint: Expected x_mat_dims[1] == y_mat_dims[0], but received x_mat_dims[1]:6 != y_mat_dims[0]:1.] at (/paddle/paddle/fluid/operators/mul_op.cc:83)

我得batch_size设置的是512，想请问是哪有问题？