I try to implement network with Higher order gradient.

```
torch.manual_seed(48)
for epoch in range(100):
for i, (train_x,train_y) in enumerate(train_loader):
train_x = train_x.to(device)
train_y = train_y.to(device)
mypredict = my_model(train_x)
loss = myloss(mypredict,train_y)
grad_norm = 0
grad_params = torch.autograd.grad(loss, my_model.parameters(), create_graph=True)
for grad in grad_params:
grad_norm += grad.pow(2).sum()
grad_norm = grad_norm.sqrt()
# take the gradients wrt grad_norm. backward() will accumulate
# the gradients into the .grad attributes
# do an optimization step
optim.zero_grad()
grad_norm.backward()
optim.step()
print("Loss in Epoch {}/100 = {}".format(epoch+1,loss.item()))
```

but when I plot loss

Loss value is fluctuate

What should I do? Thank you