Define weights in qehvi

[A-ep93]

Hello all,
How can we define weights for each output while using qehvi?
Considering the following functions:

def optimize_qehvi_and_get_observation(model, train_obj, sampler):
    """Optimizes the qEHVI acquisition function, and returns a new candidate and observation."""
    # partition non-dominated space into disjoint rectangles
    partitioning = NondominatedPartitioning(ref_point=ref, Y=train_obj)
    acq_func = qExpectedHypervolumeImprovement(
        model=model,
        ref_point=ref.tolist(),  # use known reference point 
        partitioning=partitioning,
        sampler=sampler,
    )
    # optimize
    candidates, _ = optimize_acqf(
        acq_function=acq_func,
        bounds=bounds,
        q=BATCH_SIZE,
        num_restarts=NUM_RESTARTS,
        raw_samples=RAW_SAMPLES,  # used for intialization heuristic
        options={"batch_limit": 5, "maxiter": 200, "nonnegative": True},
        sequential=True,
    )
    # observe new values 
    new_x = candidates.detach()
    new_obj = problem(new_x)
    return new_x, new_obj

How should we modify it to define weights for each of the outputs of the black-box function?

[Balandat]

@A-ep93 can you take at the (very pertinent) discussion in #1004 ?