Remove _check_previous_required_observation method (facebook#1999)

Summary:
Pull Request resolved: facebook#1999

This method is redundant and checks for a state that we should never reach. In the process of updating to GenerationNode based GS, maintaining this method would entail keeping track of previous nodes. The tech debt of doing so outweighs the potential reward of keeping the function. Also I think since use_update has been deprecated this function is also less relevant.

Reviewed By: lena-kashtelyan

Differential Revision: D51420534

fbshipit-source-id: a17a48acc811579d15012cb44c1ee8aca2941428

ax/modelbridge/generation_strategy.py

@@ -17,7 +17,7 @@
 from ax.core.generator_run import GeneratorRun
 from ax.core.observation import ObservationFeatures
 from ax.core.utils import extend_pending_observations
-from ax.exceptions.core import DataRequiredError, NoDataError, UserInputError
+from ax.exceptions.core import DataRequiredError, UserInputError
 from ax.exceptions.generation_strategy import GenerationStrategyCompleted
 
 from ax.modelbridge.base import ModelBridge
@@ -457,7 +457,6 @@ def _fit_current_model(self, data: Optional[Data]) -> None:
 
         self._curr.fit(experiment=self.experiment, data=data, **model_state_on_lgr)
         self._model = self._curr.model_spec.fitted_model
-        self._check_previous_required_observation(data=data)
 
     def _maybe_move_to_next_step(self, raise_data_required_error: bool = True) -> bool:
         """Moves this generation strategy to next step if the current step is completed,
@@ -530,21 +529,3 @@ def _get_model_state_from_last_generator_run(self) -> Dict[str, Any]:
                 )
 
         return model_state_on_lgr
-
-    def _check_previous_required_observation(self, data: Data) -> None:
-        previous_step_req_observations = (
-            self._curr.index > 0
-            and self._steps[self._curr.index - 1].min_trials_observed > 0
-        )
-        # If previous step required observed data, we should raise an error even if
-        # enough trials were completed. Such an empty data case does indicate an
-        # invalid state; this check is to improve the experience of detecting and
-        # debugging the invalid state that led to this.
-        if data.df.empty and previous_step_req_observations:
-            raise NoDataError(
-                f"Observed data is required for generation node {self._curr.node_name},"
-                f"(model {self._curr.model_to_gen_from_name}), but fetched data was "
-                "empty. Something is wrong with experiment setup -- likely metrics "
-                "do not implement fetching logic (check your metrics) or no data "
-                "was attached to experiment for completed trials."
-            )