for epoch in range(Epochs):
q =torch.Tensor(q).float()
loss = loss_fn(X, U, p, q)
optim.zero_grad()
loss.backward()
optim.step()
print('*'*10)
print('epoch {}'.format(epoch+1)) #误差
print('loss is {:.4f}'.format(loss))
X和U为自变量,p和q为对应的y值
**********
epoch 1
loss is 52.6023
**********
epoch 2
loss is 52.6023
**********
epoch 3
loss is 52.6023
**********
epoch 4
loss is 52.6022
**********
epoch 5
loss is 52.6022
**********
epoch 6
loss is 52.6122
**********
epoch 7
loss is 52.6021
**********
epoch 8
loss is 52.6021
**********
epoch 9
loss is 52.6121
**********
epoch 10
loss is 52.6120
**********
epoch 11
loss is 52.6120
**********
epoch 12
loss is 52.6219
**********
epoch 13
loss is 52.6218
**********
epoch 14
loss is 52.6118
**********
epoch 15
loss is 52.6217
**********
epoch 16
loss is 52.6117
**********
epoch 17
loss is 52.6016
**********
epoch 18
loss is 52.5715
**********
epoch 19
loss is 52.5615
**********
epoch 20
loss is 52.5414
希望路过的各位大佬能给小白一些建议,蟹蟹~