您好！
我是的代码是在案例“混合量子经典神经网络模型”的基础上进行修改的。修改的代码如下：
`
x_train, y_train, x_test, y_test = data_select(1000, 100)
model = Net().toGPU()
optimizer = Adam(model.parameters(), lr=0.005)
#分类任务使用交叉熵函数
loss_func = CategoricalCrossEntropy()
#训练次数
epochs = 10
train_loss_list = []
val_loss_list = []
train_acc_list =[]
val_acc_list = []
for epoch in range(1, epochs):
total_loss = []
model.train()
batch_size = 1
correct = 0
n_train = 0
for x, y in data_generator(x_train, y_train, batch_size=1, shuffle=True):
x = x.reshape(-1, 1, 28, 28)
x = QTensor(x)
y = QTensor(y)
x = x.to_gpu(DEV_GPU_0)
y = y.to_gpu(DEV_GPU_0)
optimizer.zero_grad()
output = model(x)
loss = loss_func(y, output)
loss_np = np.array(loss.data)
np_output = np.array(output.data, copy=False)
mask = (np_output.argmax(1) == y.argmax(1))
correct += np.sum(np.array(mask))
n_train += batch_size
loss.backward()
optimizer._step()
total_loss.append(loss_np)
train_loss_list.append(np.sum(total_loss) / len(total_loss))
train_acc_list.append(np.sum(correct) / n_train)
print("{:.0f} loss is : {:.10f}".format(epoch, train_loss_list[-1]))
`
但是出现下面的问题：
terminate called after throwing an instance of 'std::invalid_argument' what(): tensor --> numpy device not supported, toCPU() first. Aborted (core dumped)
请问这是哪里出了问题？谢谢！
您好！
我是的代码是在案例“混合量子经典神经网络模型”的基础上进行修改的。修改的代码如下：
`
x_train, y_train, x_test, y_test = data_select(1000, 100)
model = Net().toGPU()
optimizer = Adam(model.parameters(), lr=0.005)
#分类任务使用交叉熵函数
loss_func = CategoricalCrossEntropy()
#训练次数
epochs = 10
train_loss_list = []
val_loss_list = []
train_acc_list =[]
val_acc_list = []
for epoch in range(1, epochs):
`
但是出现下面的问题：
terminate called after throwing an instance of 'std::invalid_argument' what(): tensor --> numpy device not supported, toCPU() first. Aborted (core dumped)请问这是哪里出了问题？谢谢！