def METHOD_NAME():
    np.random.seed(42)
    config = create_default_legr_config()
    train_loader = create_ones_mock_dataloader(config)
    val_loader = create_ones_mock_dataloader(config)
    train_steps_fn = lambda *x: None
    validate_fn = lambda *x: (0, np.random.random())
    nncf_config = register_default_init_args(
        config, train_loader=train_loader, train_steps_fn=train_steps_fn, val_loader=val_loader, validate_fn=validate_fn
    )
    model_1 = PruningTestModel()
    _, compression_ctrl_1 = create_compressed_model_and_algo_for_test(model_1, nncf_config)
    model_2 = PruningTestModel()
    _, compression_ctrl_2 = create_compressed_model_and_algo_for_test(model_2, config)
    assert compression_ctrl_1.ranking_coeffs == compression_ctrl_2.ranking_coeffs