You have been introduced to angular margin losses in class that imposes a constraint of the embedding vector and the entries in the weight matrix of the last layer to be unit-norm. Recall that the actual loss function is still the negative log of the predicted probability for the ground truth class. You are required to modify this loss function to impose a margin on the usual softmax loss function without imposing any constraints on the embedding vector and the weight matrix.