def METHOD_NAME(caplog, do_stitch, return_fitted_val):
    pyhf.set_backend("jax", "scipy", precision="64b")
    pdf = pyhf.simplemodels.uncorrelated_background([50.0], [100.0], [10.0])
    data = pyhf.tensorlib.astensor([125.0] + pdf.config.auxdata)
    with caplog.at_level(logging.DEBUG, 'pyhf.optimize.opt_jax'):
        pyhf.infer.mle.fixed_poi_fit(
            1.0,
            data,
            pdf,
            do_grad=False,
            do_stitch=do_stitch,
            return_fitted_val=return_fitted_val,
        )  # jit
        assert 'jitting function' in caplog.text
        caplog.clear()
    with caplog.at_level(logging.DEBUG, 'pyhf.optimize.opt_jax'):
        pyhf.infer.mle.fixed_poi_fit(
            1.0,
            data,
            pdf,
            do_grad=True,
            do_stitch=do_stitch,
            return_fitted_val=return_fitted_val,
        )  # jit
        assert 'jitting function' in caplog.text
        caplog.clear()