Trouble computing gradient of constraint function in PyTorch for SQUAT adversarial attack algorithm implementation
I am implementing the SQUAT algorithm from a research paper on adversarial attacks using Sequential Quadratic Programming (SQP). My current task involves calculating the Gradient (∇g) of a constraint function ????(????_????) = (????_???? − 1_????.???? * ????_????)*????(????_????) ≤ 0 where C(x k) represents the classifier’s output (a vector torch.FloatTensor torch.Size([10])), and ????_j is the canonical basis vector for class j.