Implement ChainRunner #1869
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Implement ChainRunner #1869
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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Codecov ReportAttention:
Additional details and impacted files@@ Coverage Diff @@
## main #1869 +/- ##
==========================================
- Coverage 94.61% 94.61% -0.01%
==========================================
Files 459 459
Lines 43637 43639 +2
==========================================
+ Hits 41287 41288 +1
- Misses 2350 2351 +1
☔ View full report in Codecov by Sentry. |
bernardbeckerman
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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This pull request was exported from Phabricator. Differential Revision: D47484883 |
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Reviewed By: lena-kashtelyan Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Reviewed By: lena-kashtelyan Differential Revision: D47484883
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Summary: Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial. High-level logic is as follows: * `ChainRunner.run` kicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata. * `ChainRunner.poll_trial_status` polls the current stage's runner's status. If this is `TrialStatus.COMPLETED` and there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process. In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient). Reviewed By: lena-kashtelyan Differential Revision: D47484883
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This pull request has been merged in 2e71d92. |
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Summary:
Implements ChainRunner, which takes List[ChainRunnerStage] and runs the stages in sequence for each trial.
High-level logic is as follows:
ChainRunner.runkicks off the first ChainRunnerStage in the list and records that stage's name in the trial's run_metadata.ChainRunner.poll_trial_statuspolls the current stage's runner's status. If this isTrialStatus.COMPLETEDand there are more stages left in the chain, ChainRunner kicks off the next stage in the chain, updating the run_metadata in the process.In the future this should be implemented such that this state management happens in the calling context (e.g., Scheduler, AxClient).
Differential Revision: D47484883