def generation_strategy_from_json(
generation_strategy_json: Dict[str, Any]) -> GenerationStrategy:
"""Load generation strategy from JSON."""
steps = object_from_json(generation_strategy_json.pop("steps"))
gs = GenerationStrategy(steps=steps,
name=generation_strategy_json.pop("name"))
gs._db_id = object_from_json(generation_strategy_json.pop("db_id"))
gs._experiment = object_from_json(
generation_strategy_json.pop("experiment"))
gs._generated = generation_strategy_json.pop("generated")
gs._observed = generation_strategy_json.pop("observed")
gs._data = object_from_json(generation_strategy_json.pop("data"))
gs._curr = gs._steps[generation_strategy_json.pop("curr_index")]
gs._generator_runs = object_from_json(
generation_strategy_json.pop("generator_runs"))
if generation_strategy_json.pop(
"had_initialized_model"): # pragma: no cover
# If model in the current step was not directly from the `Models` enum,
# pass its type to `restore_model_from_generator_run`, which will then
# attempt to use this type to recreate the model.
if type(gs._curr.model) != Models:
models_enum = type(gs._curr.model)
assert issubclass(models_enum, Models)
# pyre-ignore[6]: `models_enum` typing hackiness
gs._restore_model_from_generator_run(models_enum=models_enum)
return gs
gs._restore_model_from_generator_run()
return gs
def generation_strategy_from_json(
generation_strategy_json: Dict[str, Any]
) -> GenerationStrategy:
"""Load generation strategy from JSON."""
steps = object_from_json(generation_strategy_json.pop("steps"))
gs = GenerationStrategy(steps=steps, name=generation_strategy_json.pop("name"))
gs._experiment = object_from_json(generation_strategy_json.pop("experiment"))
gs._generated = generation_strategy_json.pop("generated")
gs._observed = generation_strategy_json.pop("observed")
gs._data = object_from_json(generation_strategy_json.pop("data"))
gs._curr = gs._steps[generation_strategy_json.pop("current_step_index")]
gs._generator_runs = object_from_json(
generation_strategy_json.pop("generator_runs")
)
if generation_strategy_json.pop("had_initialized_model"): # pragma: no cover
gs._restore_model_from_generator_run()
return gs
def generation_strategy_from_json(
experiment: Experiment, generation_strategy_json: Dict[str, Any]
) -> GenerationStrategy:
"""Load generation strategy from JSON."""
gs = GenerationStrategy(
steps=object_from_json(generation_strategy_json.pop("steps")),
name=generation_strategy_json.pop("name"),
)
gs._generated = generation_strategy_json.pop("generated")
gs._observed = generation_strategy_json.pop("observed")
gs._data = object_from_json(generation_strategy_json.pop("data"))
gs._curr = object_from_json(generation_strategy_json.pop("curr"))
gs._last_generator_run = object_from_json(
generation_strategy_json.pop("last_generator_run")
)
if generation_strategy_json.pop("had_initialized_model"): # pragma: no cover
gs._restore_model_from_generator_run(experiment=experiment)
return gs
def generation_strategy_from_sqa(
self, gs_sqa: SQAGenerationStrategy) -> GenerationStrategy:
"""Convert SQALchemy generation strategy to Ax `GenerationStrategy`."""
steps = object_from_json(gs_sqa.steps)
gs = GenerationStrategy(name=gs_sqa.name, steps=steps)
gs._generated = list(gs_sqa.generated)
gs._observed = list(gs_sqa.observed)
gs._curr = gs._steps[gs_sqa.curr_index]
# There is just one data object on generation strategy.
gs._data = self.data_from_sqa(gs_sqa.data)
gs._generator_runs = [
self.generator_run_from_sqa(gr) for gr in gs_sqa.generator_runs
]
if len(gs._generator_runs) > 0:
# Generation strategy had an initialized model.
# pyre-ignore[16]: SQAGenerationStrategy does not have `experiment` attr.
gs._experiment = self.experiment_from_sqa(gs_sqa.experiment)
gs._restore_model_from_generator_run()
gs._db_id = gs_sqa.id
return gs
def test_equality(self):
gs1 = GenerationStrategy(steps=[
GenerationStep(model=Models.SOBOL, num_arms=5),
GenerationStep(model=Models.GPEI, num_arms=-1),
])
gs2 = gs1.clone_reset()
self.assertEqual(gs1, gs2)
gs1._data = get_data()
self.assertNotEqual(gs1, gs2)
gs2._data = get_data()
self.assertEqual(gs1, gs2)
gs1 = gs1.clone_reset()
gs2 = gs2.clone_reset()
gs1.gen(experiment=get_branin_experiment())
self.assertNotEqual(gs1, gs2)
gs2.gen(experiment=get_branin_experiment())
# Each generation strategy generated a different arm, so they are not
# equal even though they have the same setup and generated the same
# number of arms.
self.assertNotEqual(gs1, gs2)