Allow monotonic rejection GP to initialize its inducing point allocat…

…or from config. (facebookresearch#485)

Summary:
Pull Request resolved: facebookresearch#485

Monotonic rejection GP used to completely ignore any inducing point config, now it follows other models.

Differential Revision: D67225873

aepsych/models/monotonic_rejection_gp.py

@@ -96,12 +96,9 @@ def __init__(
             dim=self.dim
         )
 
-        # TODO: This allocator *must* be SobolAllocator and not the set one. This
-        # suggests that this model doesn't actually properly use data for inducing
-        # points properly.
-        inducing_points = SobolAllocator(
-            bounds=torch.stack([lb, ub]), dim=self.dim
-        ).allocate_inducing_points(num_inducing=self.inducing_size)
+        inducing_points = self.inducing_point_method.allocate_inducing_points(
+            num_inducing=self.inducing_size
+        )
 
         inducing_points_aug = self._augment_with_deriv_index(inducing_points, 0)
         variational_distribution = CholeskyVariationalDistribution(
@@ -169,7 +166,7 @@ def fit(self, train_x: torch.Tensor, train_y: torch.Tensor, **kwargs) -> None:
         self.inducing_points = self.inducing_point_method.allocate_inducing_points(
             num_inducing=self.inducing_size,
             covar_module=self.covar_module,
-            inputs=self._augment_with_deriv_index(self.train_inputs[0], 0),
+            X=self._augment_with_deriv_index(self.train_inputs[0], 0),
         )
         self._set_model(train_x, train_y)