#SET CONDITIONAL LEARNING RATES IF NECESSARY   
    model_parameters = []
    for n,p in model.named_parameters():
        if n.find('drn_model') != -1:
             model_parameters.append({'params': p, 'lr': LR})

        else:
            model_parameters.append({'params': p, 'lr': LR})

           
    optimizer = torch.optim.SGD(model_parameters,lr=LR, weight_decay=WEIGTH_DECAY)