gradient d sent us and how it compares to to what to do this so gradient descent on watch loss which loss functions so corresponding to the phase retrieval the natural loss function is the one i write here that would correspond to in a sense to to to neural network with no hidden variable one hidden variable with quadratic activation function so that's an actual you know i just square the label sends instead of putting absolute value i put a square here and then i'm looking at the the performance of the gradient flow