Reap get_sequential_optimization_scheduler_options (facebook#2335)

Summary: Pull Request resolved: facebook#2335

Reviewed By: sdaulton

Differential Revision: D55875116

ax/benchmark/benchmark_method.py

@@ -105,18 +105,6 @@ def get_benchmark_scheduler_options(
     )
 
 
-def get_sequential_optimization_scheduler_options(
-    timeout_hours: int = 4,
-) -> SchedulerOptions:
-    """The typical SchedulerOptions used in benchmarking.
-
-    Args:
-        timeout_hours: The maximum amount of time (in hours) to run each
-            benchmark replication. Defaults to 4 hours.
-    """
-    return get_benchmark_scheduler_options(timeout_hours=timeout_hours)
-
-
 def _assign_frozen_attr(obj: Any, name: str, value: Any) -> None:  # pyre-ignore [2]
     """Assign a new value to an attribute of a frozen dataclass.
     This is an ugly hack and shouldn't be used broadly.

ax/benchmark/methods/modular_botorch.py

@@ -9,7 +9,7 @@
 
 from ax.benchmark.benchmark_method import (
     BenchmarkMethod,
-    get_sequential_optimization_scheduler_options,
+    get_benchmark_scheduler_options,
 )
 from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy
 from ax.modelbridge.registry import Models
@@ -89,7 +89,6 @@ def get_sobol_botorch_modular_acquisition(
     return BenchmarkMethod(
         name=generation_strategy.name,
         generation_strategy=generation_strategy,
-        scheduler_options=scheduler_options
-        or get_sequential_optimization_scheduler_options(),
+        scheduler_options=scheduler_options or get_benchmark_scheduler_options(),
         distribute_replications=distribute_replications,
     )

ax/benchmark/methods/sobol.py

@@ -9,7 +9,7 @@
 
 from ax.benchmark.benchmark_method import (
     BenchmarkMethod,
-    get_sequential_optimization_scheduler_options,
+    get_benchmark_scheduler_options,
 )
 from ax.modelbridge.generation_strategy import GenerationStep, GenerationStrategy
 from ax.modelbridge.registry import Models
@@ -28,7 +28,6 @@ def get_sobol_benchmark_method(
     return BenchmarkMethod(
         name=generation_strategy.name,
         generation_strategy=generation_strategy,
-        scheduler_options=scheduler_options
-        or get_sequential_optimization_scheduler_options(),
+        scheduler_options=scheduler_options or get_benchmark_scheduler_options(),
         distribute_replications=distribute_replications,
     )

ax/benchmark/tests/test_benchmark.py

@@ -18,7 +18,7 @@
 )
 from ax.benchmark.benchmark_method import (
     BenchmarkMethod,
-    get_sequential_optimization_scheduler_options,
+    get_benchmark_scheduler_options,
 )
 from ax.benchmark.benchmark_problem import SingleObjectiveBenchmarkProblem
 from ax.benchmark.benchmark_result import BenchmarkResult
@@ -302,7 +302,7 @@ def test_replication_mbm(self) -> None:
                 get_sobol_botorch_modular_acquisition(
                     model_cls=SingleTaskGP,
                     acquisition_cls=qLogNoisyExpectedImprovement,
-                    scheduler_options=get_sequential_optimization_scheduler_options(),
+                    scheduler_options=get_benchmark_scheduler_options(),
                     distribute_replications=False,
                 ),
                 get_single_objective_benchmark_problem(

ax/benchmark/tests/test_benchmark_method.py

@@ -7,7 +7,7 @@
 
 from ax.benchmark.benchmark_method import (
     BenchmarkMethod,
-    get_sequential_optimization_scheduler_options,
+    get_benchmark_scheduler_options,
 )
 from ax.modelbridge.generation_strategy import (
     GenerationNode,
@@ -26,7 +26,7 @@ def test_benchmark_method(self) -> None:
             steps=[GenerationStep(model=Models.SOBOL, num_trials=10)],
             name="SOBOL",
         )
-        options = get_sequential_optimization_scheduler_options()
+        options = get_benchmark_scheduler_options()
         method = BenchmarkMethod(
             name="Sobol10", generation_strategy=gs, scheduler_options=options
         )
@@ -41,7 +41,7 @@ def test_benchmark_method(self) -> None:
         self.assertEqual(options.min_seconds_before_poll, 0)
         self.assertEqual(options.timeout_hours, 4)
 
-        options = get_sequential_optimization_scheduler_options(timeout_hours=10)
+        options = get_benchmark_scheduler_options(timeout_hours=10)
         method = BenchmarkMethod(
             name="Sobol10", generation_strategy=gs, scheduler_options=options
         )