Example of parameter Constraints?

[jacktang]

Hello, is there any example or tutorial on parameter constrained problem optimization?

[Balandat]

Hmm looks like we don't have a tutorial on this currently.

This unit test shows how to use parameter constraints:

botorch/test/optim/test_optimize.py

Lines 652 to 689 in d3d3c6f

	def test_optimize_acqf_runs_given_batch_initial_conditions(self):
	num_restarts, raw_samples, dim = 1, 2, 3
	opt_x = 2 / np.pi
	# -x[i] * 1 >= -opt_x * 1.01 => x[i] <= opt_x * 1.01
	inequality_constraints = [
	(torch.tensor([i]), -torch.tensor([1]), -opt_x * 1.01) for i in range(dim)
	] + [
	# x[i] * 1 >= opt_x * .99
	(torch.tensor([i]), torch.tensor([1]), opt_x * 0.99)
	for i in range(dim)
	]
	q = 1
	ic_shapes = [(1, 2, dim), (1, dim)]
	torch.manual_seed(0)
	for shape in ic_shapes:
	with self.subTest(shape=shape):
	# start near one (of many) optima
	initial_conditions = (opt_x * 1.01) * torch.ones(shape)
	batch_candidates, acq_value_list = optimize_acqf(
	acq_function=SinOneOverXAcqusitionFunction(),
	bounds=torch.stack([-1 * torch.ones(dim), torch.ones(dim)]),
	q=q,
	num_restarts=num_restarts,
	raw_samples=raw_samples,
	batch_initial_conditions=initial_conditions,
	inequality_constraints=inequality_constraints,
	)
	self.assertAllClose(
	batch_candidates,
	opt_x * torch.ones_like(batch_candidates),
	# must be at least 50% closer to the optimum than it started
	atol=0.004,
	rtol=0.005,
	)
	self.assertAlmostEqual(acq_value_list.item(), 1, places=3)