RuntimeError: element0 of tensorsdoes not requiregrad and does not have a grad_fnmodel= model(x)
loss.backward() <----- Error here
print(model.weight.gra
: element0 of tensorsdoes not requiregrad and does not have a grad_fn 有什么好方法可以将我的预测转换为标签吗?完整的错误回溯: RuntimeError Traceback (most recent call last)
<ipython-input-53, grad</
(Linear(6, 6)(Variable(torch.zeros([10, 6]))) - Variable(torch.zeros([10, 6]))).backward(){RuntimeError}element0 of variables does not requiregrad and does not have a grad_fn
我在代码中做错了什么来创建这个问题?
=<AddmmBackward0>),actual_loes_score_g是tensor([20.], dtype=torch.float64)。Please ensure they have the same size. predicted_loes_score = predicted_loes_score_g.detach()[0]Runti
例如,下面是起作用的普通实现:my_tensor = torch.rand(3, 5, requires_grad=True) #问题是Pytorch无法自动区分这一点,而且我的错误与缺乏毕业生有关,因为我有非原始的火炬操作:
RuntimeError: element0 of tensorsdoes not requiregrad and does not <