Deep Learning, Regularization Techniques, Python Programming, Data Science, Technology.
the gradients optimizer.zero_grad() # Perform forward pass outputs = mlp(inputs) # Compute loss loss = loss_function(outputs, targets) # Compute L1 loss component l1_weight = 1.0 l1_parameters = [] for parameter in mlp.parameters(): l1_parameters.append(parameter.view(-1)) l1 = l1_weight *