def generation_step_from_json(generation_step_json: Dict[str, Any]) -> GenerationStep:
"""Load generation step from JSON."""
generation_step_json = _convert_generation_step_keys_for_backwards_compatibility(
generation_step_json
)
kwargs = generation_step_json.pop("model_kwargs", None)
gen_kwargs = generation_step_json.pop("model_gen_kwargs", None)
return GenerationStep(
model=object_from_json(generation_step_json.pop("model")),
num_trials=generation_step_json.pop("num_trials"),
min_trials_observed=generation_step_json.pop("min_trials_observed", 0),
max_parallelism=(generation_step_json.pop("max_parallelism", None)),
use_update=generation_step_json.pop("use_update", False),
enforce_num_trials=generation_step_json.pop("enforce_num_trials", True),
model_kwargs=_decode_callables_from_references(object_from_json(kwargs))
if kwargs
else None,
model_gen_kwargs=_decode_callables_from_references(object_from_json(gen_kwargs))
if gen_kwargs
else None,
index=generation_step_json.pop("index", -1),
should_deduplicate=generation_step_json.pop("should_deduplicate")
if "should_deduplicate" in generation_step_json
else False,
)
def generation_step_from_json(
generation_step_json: Dict[str, Any]) -> GenerationStep:
"""Load generation step from JSON."""
return GenerationStep(
model=object_from_json(generation_step_json.pop("model")),
num_trials=generation_step_json.pop("num_trials"),
min_trials_observed=generation_step_json.pop("min_trials_observed"),
max_parallelism=generation_step_json.pop("max_parallelism"),
use_update=generation_step_json.pop("use_update"),
enforce_num_trials=generation_step_json.pop("enforce_num_trials"),
model_kwargs=_decode_callables_from_references(
object_from_json(generation_step_json.pop("model_kwargs")))
or None,
model_gen_kwargs=_decode_callables_from_references(
object_from_json(generation_step_json.pop("model_gen_kwargs")))
or None,
index=generation_step_json.pop("index"),
)