initial_backbone, rpn, head = frcnn_split(frcnn_model)
compressed_backbone = copy.deepcopy(initial_backbone)


device = 'cpu'
train_iters = 10
val_iters = 10

for ft_iter in range(1):

    layer_names = get_layer_names(MODEL_NAME, initial_backbone)
    ranks = [None]*len(layer_names)

    # compress backbone
    compressed_backbone = get_compressed_model(compressed_backbone, MODEL_NAME,
                                   ranks=ranks, layer_names = layer_names,
                                    decomposition = decomposition,
                                    vbmf_weaken_factor = 0.7)

    # add new backbone to od model
    compressed_frcnn_model = frcnn_glue(compressed_backbone, rpn, head, device)

    # finetune od model
    compressed_frcnn_model = fine_tune(compressed_model, loaders, device, save_dir,
              train_iters = train_iters, val_iters = val_iters)

    # get backbone for the next iteration
    compressed_backbone, rpn, head = frcnn_split(compressed_frcnn_model)