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WIP: Introduce TrialRunner Abstraction #720
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…nit test for bench (not tested)
…e bulk registration (check for is_warm_up)
@@ -46,6 +46,16 @@ def __init__( # pylint: disable=too-many-arguments | |||
self._engine = engine | |||
self._schema = schema | |||
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def _save_new_config_data(self, new_config_data: Dict[str, Union[int, float, str]]) -> None: |
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Needs tests
@@ -145,6 +161,7 @@ def get_results_df( | |||
"tunable_config_id", | |||
"tunable_config_trial_group_id", | |||
"status", | |||
"trial_runner_id", |
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Needs tests
"""ID of the TrialRunner.""" | ||
if not self._trial_runner_id: | ||
self._trial_runner_id = self.metadata_dict.get("trial_runner_id") | ||
return self._trial_runner_id |
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Needs tests
Refactors tests in preparation for testing for #720. Adds `status()` output for MockEnv as well, though with a pending FIXME on improving the Status type in the status output that we'll address in a future PR.
…to trial-runner-abstraction
This is another step in adding support for parallel trial execution #380.
Here we separate out the running of an individual trial to a single class - TrialRunner.
Multiple TrialRunners are instantiated at CLI invocation with the
--num-trial-runners
argument.Each TrialRunner associated with a single copy of the root Environment, and made unique by means of a unique
trial_runner_id
value that's included in that Environment's global_config.TODO:
In future PRs we will add: