output_1, output_2 = model(x)
loss = cross_entropy_loss(output_1, target_1)
loss.backward()
optimizer.step()
loss = cross_entropy_loss(output_2, target_2)
loss.backward()
optimizer.step()
但是，当我运行这段代码时，出现以下错误：
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [1, 4]], which is output 0 of TBackward, is at version 2; expected version 1 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).
然后，我真的想知道我应该做什么来训练具有 2 个或更多输出的模型
python machine-learning neural-network deep-learning pytorch