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for g, ig in zip(dalpha, implicit_grads):
g.data.sub_(eta, ig.data)
for v, g in zip(self.model.arch_parameters(), dalpha):
if v.grad is None:
v.grad = Variable(g.data)
else:
v.grad.data.copy_(g.data)
I think first loop is for Eq. 7, then we got Eq. 6 value.
After that, to update alpha, I think gradient descent is needed.
But in the code, there is just copy operation. (second loop)
What is wrong with my opinion?
The text was updated successfully, but these errors were encountered:
Hi, I'm confused code details in alpha update.
I think first loop is for Eq. 7, then we got Eq. 6 value.
After that, to update alpha, I think gradient descent is needed.
But in the code, there is just copy operation. (second loop)
What is wrong with my opinion?
The text was updated successfully, but these errors were encountered: