Use compute_metric_availability in AxClient.fit_model#5111
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Summary: The previous data check in `fit_model` only verified that the DataFrame was non-empty (`lookup_data().df.empty`), which would pass even when data existed for only a subset of required metrics. This could allow model fitting to proceed with incomplete data, leading to downstream errors. Replace the manual check with `compute_metric_availability()` from `ax.core.utils`, which inspects per-trial metric coverage against the optimization config's required metrics. `fit_model` now raises `DataRequiredError` unless at least one completed trial has data for **all** required metrics (`MetricAvailability.COMPLETE`). Reviewed By: saitcakmak Differential Revision: D98208718
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #5111 +/- ##
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+ Coverage 96.41% 96.42% +0.01%
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Files 613 613
Lines 68131 68142 +11
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+ Hits 65687 65705 +18
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This pull request has been merged in 8ec8faa. |
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Summary:
The previous data check in
fit_modelonly verified that the DataFramewas non-empty (
lookup_data().df.empty), which would pass even when dataexisted for only a subset of required metrics. This could allow model
fitting to proceed with incomplete data, leading to downstream errors.
Replace the manual check with
compute_metric_availability()fromax.core.utils, which inspects per-trial metric coverage against theoptimization config's required metrics.
fit_modelnow raisesDataRequiredErrorunless at least one completed trial has data forall required metrics (
MetricAvailability.COMPLETE).Reviewed By: saitcakmak
Differential Revision: D98208718