encounter an unknown error, please verify the input model file or build the debug version

from mindspore import Tensor, nn
import mindspore
import numpy as np

class Network(nn.Cell):

    def __init__(self):
        super().__init__()
        self.fc1 = nn.Dense(in_channels=10, out_channels=10, activation='relu')
        self.fc2 = nn.Dense(in_channels=10, out_channels=5, activation='relu')

    def construct(self, x: Tensor):
        x = self.fc1(x)
        x = self.fc2(x)
        return x
    

model = Network()

# Instantiate loss function and optimizer
loss_fn = nn.CrossEntropyLoss()
optimizer = nn.SGD(model.trainable_params(), 1e-2, momentum=0.9)

example_input = Tensor(np.ones((1, 10), dtype=np.float32))
model.set_train(False)
mindspore.export(model,
                 example_input,
                 file_format='MINDIR',
                 file_name='debug_predict')
# export trainable model
model.set_train(True)
example_label = Tensor(np.ones((1), dtype=np.int32))
loss_net = nn.WithLossCell(backbone=model, loss_fn=loss_fn)
train_net = nn.TrainOneStepCell(network=loss_net, optimizer=optimizer)
mindspore.export(train_net,
                 example_input, example_label,
                 file_format='MINDIR',
                 file_name='debug_train')
print('导出模型完成')