Move infinite interval bounds check into Internval constructor

Addresses #2258, avoids repeatedly checking the same condition in each forward pass. Avoids forcing GPU synchronization.

Author: Balandat

gpytorch/constraints/constraints.py

@@ -1,5 +1,7 @@
 #!/usr/bin/env python3
 
+from __future__ import annotations
+
 import math
 
 import torch
@@ -23,11 +25,21 @@ def __init__(self, lower_bound, upper_bound, transform=sigmoid, inv_transform=in
             lower_bound (float or torch.Tensor): The lower bound on the parameter.
             upper_bound (float or torch.Tensor): The upper bound on the parameter.
         """
-        lower_bound = torch.as_tensor(lower_bound).float()
-        upper_bound = torch.as_tensor(upper_bound).float()
+        dtype = torch.get_default_dtype()
+        lower_bound = torch.as_tensor(lower_bound).to(dtype)
+        upper_bound = torch.as_tensor(upper_bound).to(dtype)
 
         if torch.any(torch.ge(lower_bound, upper_bound)):
-            raise RuntimeError("Got parameter bounds with empty intervals.")
+            raise ValueError("Got parameter bounds with empty intervals.")
+
+        if type(self) == Interval:
+            max_bound = torch.max(upper_bound)
+            min_bound = torch.min(lower_bound)
+            if max_bound == math.inf or min_bound == -math.inf:
+                raise ValueError(
+                    "Cannot make an Interval directly with non-finite bounds. Use a derived class like "
+                    "GreaterThan or LessThan instead."
+                )
 
         super().__init__()
 
@@ -111,16 +123,6 @@ def transform(self, tensor):
         if not self.enforced:
             return tensor
 
-        if settings.debug.on():
-            max_bound = torch.max(self.upper_bound)
-            min_bound = torch.min(self.lower_bound)
-
-            if max_bound == math.inf or min_bound == -math.inf:
-                raise RuntimeError(
-                    "Cannot make an Interval directly with non-finite bounds. Use a derived class like "
-                    "GreaterThan or LessThan instead."
-                )
-
         transformed_tensor = (self._transform(tensor) * (self.upper_bound - self.lower_bound)) + self.lower_bound
 
         return transformed_tensor

test/constraints/test_constraints.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python3
 
+import math
 import unittest
 
 import torch
@@ -69,6 +70,13 @@ def test_initial_value(self):
         lkhd = gpytorch.likelihoods.GaussianLikelihood(noise_constraint=constraint)
         self.assertEqual(lkhd.noise.item(), 3.0)
 
+    def test_error_on_infinite(self):
+        err_msg = "Cannot make an Interval directly with non-finite bounds"
+        with self.assertRaisesRegex(ValueError, err_msg):
+            gpytorch.constraints.Interval(0.0, math.inf)
+        with self.assertRaisesRegex(ValueError, err_msg):
+            gpytorch.constraints.Interval(-math.inf, 0.0)
+
 
 class TestGreaterThan(unittest.TestCase, BaseTestCase):
     def test_transform_float_greater_than(self):