Skip to content

Fix unit tests broken by upstream gpytorch changes #1055

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
wants to merge 1 commit into from
Closed

Fix unit tests broken by upstream gpytorch changes #1055

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
6 changes: 3 additions & 3 deletions ax/models/tests/test_alebo.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def testALEBOGP(self):

# Batch
Uvec_b = m.covar_module.base_kernel.Uvec.repeat(5, 1)
mean_b = m.mean_module.constant.repeat(5, 1)
mean_b = m.mean_module.constant.repeat(5)
output_scale_b = m.covar_module.raw_outputscale.repeat(5)
m_b = get_batch_model(
B=B,
Expand Down Expand Up @@ -132,7 +132,7 @@ def testALEBOGP(self):
{
"covar_module.base_kernel.Uvec",
"covar_module.raw_outputscale",
"mean_module.constant",
"mean_module.raw_constant",
"covar_module.raw_outputscale_constraint.lower_bound",
"covar_module.raw_outputscale_constraint.upper_bound",
},
Expand All @@ -151,7 +151,7 @@ def testALEBOGP(self):
{
"covar_module.base_kernel.Uvec",
"covar_module.raw_outputscale",
"mean_module.constant",
"mean_module.raw_constant",
"covar_module.raw_outputscale_constraint.lower_bound",
"covar_module.raw_outputscale_constraint.upper_bound",
},
Expand Down
4 changes: 2 additions & 2 deletions ax/models/tests/test_botorch_model.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -457,7 +457,7 @@ def test_BotorchModel(self, dtype=torch.float, cuda=False):

# Test loading state dict
true_state_dict = {
"mean_module.constant": [3.5004],
"mean_module.raw_constant": 3.5004,
"covar_module.raw_outputscale": 2.2438,
"covar_module.base_kernel.raw_lengthscale": [
[-0.9274, -0.9274, -0.9274]
Expand Down Expand Up @@ -489,7 +489,7 @@ def test_BotorchModel(self, dtype=torch.float, cuda=False):
self.assertTrue(torch.equal(true_state_dict[k], v))

# Test for some change in model parameters & buffer for refit_model=True
true_state_dict["mean_module.constant"] += 0.1
true_state_dict["mean_module.raw_constant"] += 0.1
true_state_dict["covar_module.raw_outputscale"] += 0.1
true_state_dict["covar_module.base_kernel.raw_lengthscale"] += 0.1
model = get_and_fit_model(
Expand Down
10 changes: 4 additions & 6 deletions ax/models/tests/test_fully_bayesian.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -348,7 +348,7 @@ def test_FullyBayesianBotorchModel(self, dtype=torch.float, cuda=False):
self.assertEqual(len(model.model.models), 2)
m1, m2 = model.model.models[0], model.model.models[1]
# Mean
self.assertEqual(m1.mean_module.constant.shape, (4, 1))
self.assertEqual(m1.mean_module.constant.shape, (4,))
self.assertFalse(
torch.isclose(
m1.mean_module.constant, m2.mean_module.constant
Expand Down Expand Up @@ -376,11 +376,9 @@ def test_FullyBayesianBotorchModel(self, dtype=torch.float, cuda=False):
device = torch.device("cuda") if cuda else torch.device("cpu")
objective_weights = torch.tensor([1.0, 0.0], dtype=dtype, device=device)
objective_transform = get_objective_weights_transform(objective_weights)
infeasible_cost = torch.tensor(
get_infeasible_cost(
infeasible_cost = get_infeasible_cost(
X=Xs1[0], model=model.model, objective=objective_transform
)
)
).detach().clone()
expected_infeasible_cost = -1 * torch.min(
objective_transform(
model.model.posterior(Xs1[0]).mean
Expand Down Expand Up @@ -841,7 +839,7 @@ def test_FullyBayesianBotorchModelPyro(self, dtype=torch.double, cuda=False):
)
self.assertEqual(
m.mean_module.constant.shape,
torch.Size([4, 1]),
torch.Size([4]),
)
if use_input_warping:
self.assertTrue(hasattr(m, "input_transform"))
Expand Down
12 changes: 6 additions & 6 deletions ax/models/torch/alebo.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -331,7 +331,7 @@ def f(x):

# Sample only Uvec; leave mean and output scale fixed.
assert list(property_dict.keys()) == [
"model.mean_module.constant",
"model.mean_module.raw_constant",
"model.covar_module.raw_outputscale",
"model.covar_module.base_kernel.Uvec",
]
Expand All @@ -347,7 +347,7 @@ def f(x):
nsamp, *attrs.shape
)
# Get the other properties into batch mode
mean_constant_batch = mll.model.mean_module.constant.repeat(nsamp, 1)
mean_constant_batch = mll.model.mean_module.constant.repeat(nsamp)
output_scale_batch = mll.model.covar_module.raw_outputscale.repeat(nsamp)
return Uvec_batch, mean_constant_batch, output_scale_batch

Expand Down Expand Up @@ -383,10 +383,10 @@ def get_batch_model(
)
m_b.train()
# Set mean constant
# pyre-fixme[16]: `Optional` has no attribute `constant`.
m_b.mean_module.constant.requires_grad_(False)
m_b.mean_module.constant.copy_(mean_constant_batch)
m_b.mean_module.constant.requires_grad_(True)
# pyre-fixme[16]: `Optional` has no attribute `raw_constant`.
m_b.mean_module.raw_constant.requires_grad_(False)
m_b.mean_module.raw_constant.copy_(mean_constant_batch)
m_b.mean_module.raw_constant.requires_grad_(True)
# Set output scale
m_b.covar_module.raw_outputscale.requires_grad_(False)
m_b.covar_module.raw_outputscale.copy_(output_scale_batch)
Expand Down