Reorganize runner tests following previous class renaming

Summary:
See D64969707 for context.

This diff:
* Moves the parts of `tests/runners/test_botorch_test_problem` that pertain to the runner into `tests/test_benchmark_runner.py`
* Moves the parts that pertain to `BoTorchTestFunction` to `tests/benchmark_test_functions/test_botorch_test_function.py`
* Moves `tests/runners/test_surrogate_runner.py` to `tests/benchmark_test_functions/test_surrogate_test_function.py`

Differential Revision: D65090663

ax/benchmark/tests/benchmark_test_functions/test_botorch_test_function.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python3
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+#
+# This source code is licensed under the MIT license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-strict
+
+
+import torch
+from ax.benchmark.benchmark_test_functions.botorch_test import BoTorchTestFunction
+from ax.utils.common.testutils import TestCase
+from botorch.test_functions.multi_objective import BraninCurrin
+from botorch.test_functions.synthetic import ConstrainedHartmann, Hartmann
+
+
+class TestBoTorchTestFunction(TestCase):
+    def setUp(self) -> None:
+        super().setUp()
+        botorch_base_test_functions = {
+            "base Hartmann": Hartmann(dim=6),
+            "negated Hartmann": Hartmann(dim=6, negate=True),
+            "constrained Hartmann": ConstrainedHartmann(dim=6),
+            "negated constrained Hartmann": ConstrainedHartmann(dim=6, negate=True),
+        }
+        self.botorch_test_problems = {
+            k: BoTorchTestFunction(botorch_problem=v)
+            for k, v in botorch_base_test_functions.items()
+        }
+
+    def test_negation(self) -> None:
+        params = {f"x{i}": 0.5 for i in range(6)}
+        evaluate_true_results = {
+            k: v.evaluate_true(params) for k, v in self.botorch_test_problems.items()
+        }
+        self.assertEqual(
+            evaluate_true_results["base Hartmann"],
+            evaluate_true_results["constrained Hartmann"][0],
+        )
+        self.assertEqual(
+            evaluate_true_results["base Hartmann"],
+            -evaluate_true_results["negated Hartmann"],
+        )
+        self.assertEqual(
+            evaluate_true_results["negated Hartmann"],
+            evaluate_true_results["negated constrained Hartmann"][0],
+        )
+        self.assertEqual(
+            evaluate_true_results["constrained Hartmann"][1],
+            evaluate_true_results["negated constrained Hartmann"][1],
+        )
+
+    def test_raises_for_botorch_attrs(self) -> None:
+        msg = "noise should be set on the `BenchmarkRunner`, not the test function."
+        with self.assertRaisesRegex(ValueError, msg):
+            BoTorchTestFunction(botorch_problem=Hartmann(dim=6, noise_std=0.1))
+        with self.assertRaisesRegex(ValueError, msg):
+            BoTorchTestFunction(
+                botorch_problem=ConstrainedHartmann(dim=6, constraint_noise_std=0.1)
+            )
+
+    def test_tensor_shapes(self) -> None:
+        params = {f"x{i}": 0.5 for i in range(6)}
+        evaluate_true_results = {
+            k: v.evaluate_true(params) for k, v in self.botorch_test_problems.items()
+        }
+        evaluate_true_results["BraninCurrin"] = BoTorchTestFunction(
+            botorch_problem=BraninCurrin()
+        ).evaluate_true(params)
+        expected_len = {
+            "base Hartmann": 1,
+            "constrained Hartmann": 2,
+            "negated Hartmann": 1,
+            "negated constrained Hartmann": 2,
+            "BraninCurrin": 2,
+        }
+        for name, result in evaluate_true_results.items():
+            with self.subTest(name=name):
+                self.assertEqual(result.dtype, torch.double)
+                self.assertEqual(result.shape, torch.Size([expected_len[name]]))

ax/benchmark/tests/runners/test_botorch_test_problem.py → ax/benchmark/tests/test_benchmark_runner.py

@@ -29,83 +29,16 @@
     DummyTestFunction,
     get_soo_surrogate_test_function,
 )
-from botorch.test_functions.multi_objective import BraninCurrin
 from botorch.test_functions.synthetic import Ackley, ConstrainedHartmann, Hartmann
 from botorch.utils.transforms import normalize
 
 
-class TestBoTorchTestFunction(TestCase):
-    def setUp(self) -> None:
-        super().setUp()
-        botorch_base_test_functions = {
-            "base Hartmann": Hartmann(dim=6),
-            "negated Hartmann": Hartmann(dim=6, negate=True),
-            "constrained Hartmann": ConstrainedHartmann(dim=6),
-            "negated constrained Hartmann": ConstrainedHartmann(dim=6, negate=True),
-        }
-        self.botorch_test_problems = {
-            k: BoTorchTestFunction(botorch_problem=v)
-            for k, v in botorch_base_test_functions.items()
-        }
-
-    def test_negation(self) -> None:
-        params = {f"x{i}": 0.5 for i in range(6)}
-        evaluate_true_results = {
-            k: v.evaluate_true(params) for k, v in self.botorch_test_problems.items()
-        }
-        self.assertEqual(
-            evaluate_true_results["base Hartmann"],
-            evaluate_true_results["constrained Hartmann"][0],
-        )
-        self.assertEqual(
-            evaluate_true_results["base Hartmann"],
-            -evaluate_true_results["negated Hartmann"],
-        )
-        self.assertEqual(
-            evaluate_true_results["negated Hartmann"],
-            evaluate_true_results["negated constrained Hartmann"][0],
-        )
-        self.assertEqual(
-            evaluate_true_results["constrained Hartmann"][1],
-            evaluate_true_results["negated constrained Hartmann"][1],
-        )
-
-    def test_raises_for_botorch_attrs(self) -> None:
-        msg = "noise should be set on the `BenchmarkRunner`, not the test function."
-        with self.assertRaisesRegex(ValueError, msg):
-            BoTorchTestFunction(botorch_problem=Hartmann(dim=6, noise_std=0.1))
-        with self.assertRaisesRegex(ValueError, msg):
-            BoTorchTestFunction(
-                botorch_problem=ConstrainedHartmann(dim=6, constraint_noise_std=0.1)
-            )
-
-    def test_tensor_shapes(self) -> None:
-        params = {f"x{i}": 0.5 for i in range(6)}
-        evaluate_true_results = {
-            k: v.evaluate_true(params) for k, v in self.botorch_test_problems.items()
-        }
-        evaluate_true_results["BraninCurrin"] = BoTorchTestFunction(
-            botorch_problem=BraninCurrin()
-        ).evaluate_true(params)
-        expected_len = {
-            "base Hartmann": 1,
-            "constrained Hartmann": 2,
-            "negated Hartmann": 1,
-            "negated constrained Hartmann": 2,
-            "BraninCurrin": 2,
-        }
-        for name, result in evaluate_true_results.items():
-            with self.subTest(name=name):
-                self.assertEqual(result.dtype, torch.double)
-                self.assertEqual(result.shape, torch.Size([expected_len[name]]))
-
-
-class TestSyntheticRunner(TestCase):
+class TestBenchmarkRunner(TestCase):
     def setUp(self) -> None:
         super().setUp()
         self.maxDiff = None
 
-    def test_synthetic_runner(self) -> None:
+    def test_runner(self) -> None:
         botorch_cases = [
             (
                 BoTorchTestFunction(
@@ -297,7 +230,7 @@ def test_synthetic_runner(self) -> None:
                 ):
                     BenchmarkRunner.deserialize_init_args({})
 
-    def test_botorch_test_problem_runner_heterogeneous_noise(self) -> None:
+    def test_heterogeneous_noise(self) -> None:
         for noise_std in [[0.1, 0.05], {"objective": 0.1, "constraint": 0.05}]:
             runner = BenchmarkRunner(
                 test_function=BoTorchTestFunction(