Deep Learning, Regularization Techniques, Python Programming, Data Science, Technology.
targets) # Compute l2 loss component l2_weight = 1.0 l2_parameters = [] for parameter in mlp.parameters(): l2_parameters.append(parameter.view(-1)) l2 = l2_weight * mlp.compute_l2_loss(torch.cat(l2_parameters)) # Add l2 loss component loss += l2 # Perform backward pass loss.backward() # Perform