尝试改了全连接的输出，发现不能解决

ValueError: Target(Tensor(shape=[1], dtype=int64, place=CPUPlace, stop_gradient=True,
[1])) is out of class_dimension's upper bound(0)

ValueError Traceback (most recent call last)
/tmp/ipykernel_6118/2013954757.py in
158 val_loader = paddle.io.DataLoader(val_dataset, batch_size=20, shuffle=True)
159 # 启动训练过程
--> 160 train(model, opt, train_loader, val_loader)

/tmp/ipykernel_6118/2013954757.py in train(model, opt, train_loader, val_loader)
99 # 计算损失函数
100 loss_func = paddle.nn.CrossEntropyLoss(reduction='none')
--> 101 loss = loss_func(logits, label)
102 avg_loss = paddle.mean(loss)
103

/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/fluid/dygraph/layers.py in __call__(self, *inputs, **kwargs)
912 self._built = True
913
--> 914 outputs = self.forward(*inputs, **kwargs)
915
916 for forward_post_hook in self._forward_post_hooks.values():

/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/layer/loss.py in forward(self, input, label)
404 axis=self.axis,
405 use_softmax=self.use_softmax,
--> 406 name=self.name)
407
408 return ret

/opt/conda/envs/python35-paddle120-env/lib/python3.7/site-packages/paddle/nn/functional/loss.py in cross_entropy(input, label, weight, ignore_index, reduction, soft_label, axis, use_softmax, name)
1669 raise ValueError(
1670 "Target({}) is out of class_dimension's upper bound({})".
-> 1671 format(invalid_label[0], input.shape[axis] - 1))
1672
1673 _, out = _C_ops.softmax_with_cross_entropy(

ValueError: Target(Tensor(shape=[1], dtype=int64, place=CPUPlace, stop_gradient=True,
[1])) is out of class_dimension's upper bound(0)