def testTorchModelCrossValidate(self):
torch_model = TorchModel()
with self.assertRaises(NotImplementedError):
torch_model.cross_validate(
Xs_train=[np.array([1])],
Ys_train=[np.array([1])],
Yvars_train=[np.array([1])],
X_test=np.array([1]),
)
def testTorchModelCrossValidate(self):
torch_model = TorchModel()
with self.assertRaises(NotImplementedError):
torch_model.cross_validate(
Xs_train=[np.array([1])],
Ys_train=[np.array([1])],
Yvars_train=[np.array([1])],
X_test=np.array([1]),
search_space_digest=SearchSpaceDigest(feature_names=[],
bounds=[]),
metric_names=[],
)
def testTorchModelCrossValidate(self):
torch_model = TorchModel()
with self.assertRaises(NotImplementedError):
torch_model.cross_validate(
Xs_train=[np.array([1])],
Ys_train=[np.array([1])],
Yvars_train=[np.array([1])],
X_test=np.array([1]),
bounds=[],
task_features=[],
fidelity_features=[],
feature_names=[],
metric_names=[],
)
