def METHOD_NAME(model_name) -> Tuple[NNCFNetwork, ProgressiveShrinkingController, Callable]:
    model = NAS_MODEL_DESCS[model_name][0]()
    nncf_config = get_empty_config(input_sample_sizes=NAS_MODEL_DESCS[model_name][1])
    nncf_config["bootstrapNAS"] = {"training": {"algorithm": "progressive_shrinking"}}
    nncf_config["input_info"][0].update({"filler": "random"})
    input_info_list = create_input_infos(nncf_config)
    dummy_forward = create_dummy_forward_fn(input_info_list)
    compressed_model, training_ctrl = create_bootstrap_training_model_and_ctrl(model, nncf_config)
    return compressed_model, training_ctrl, dummy_forward