fix(MachineLearningScorer, v1.2): splice metric_list verbatim instead of double-encoding - #7003
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…uble-encoding (#6805) ### What changes were proposed in this PR? Fixes a double-encoding bug in `MachineLearningScorerOpDesc` where the selected metrics collapse into a single malformed `metric_list` element. `getSelectedMetrics()` returns the chosen metric names as one comma-separated, already-quoted fragment (e.g. `'Accuracy','F1 Score'`) and is spliced into the generated Python as a list: ``` metric_list = [${getSelectedMetrics()}] ``` Its return type was **`EncodableString`**, so the Python template builder **re-encoded the whole fragment as one Python string value** instead of splicing it verbatim. The emitted code became: ```python metric_list = [self.decode_python_template('J0FjY3VyYWN5JywnRjEgU2NvcmUn')] ``` where the base64 `J0FjY3VyYWN5JywnRjEgU2NvcmUn` decodes to `'Accuracy','F1 Score'` — i.e. the entire quoted list collapses into **one** decoded string element: ```python metric_list = ["'Accuracy','F1 Score'"] # ONE element, incl. inner quotes ``` instead of the intended: ```python metric_list = ['Accuracy', 'F1 Score'] ``` So every downstream `if 'X' in metric_list` and `for metric in metric_list` / `metrics_func[metric]` operates on that single malformed element — the selected metrics are never matched, and the classification path hits a `KeyError` on the bogus key. The Scorer produces wrong/empty output for both the classification and regression paths. **Fix:** change `getSelectedMetrics()`'s return type from `EncodableString` to plain `String`, so the builder splices it verbatim into `metric_list = ['Accuracy','F1 Score']`. The method body is unchanged. ```diff - private def getSelectedMetrics(): EncodableString = { + private def getSelectedMetrics(): String = { val metric = if (isRegression) regressionMetrics else classificationMetrics metric.map(metric => getMetricName(metric)).mkString("'", "','", "'") } ``` ### Any related issues, documentation, discussions? Closes #6790 ### How was this PR tested? Added a regression test to `MachineLearningScorerOpDescSpec` that constructs the descriptor with `classificationMetrics = List(accuracy, f1Score)`, calls `generatePythonCode()`, and asserts: - the emitted code contains `metric_list = ['Accuracy','F1 Score']` (verbatim), and - the metric names are **not** base64-re-encoded through the template builder. Both assertions fail on `main` (the line is emitted as `metric_list = [self.decode_python_template('J0FjY3VyYWN5JywnRjEgU2NvcmUn')]`) and pass with this change. Ran the full suite locally: ``` sbt "WorkflowOperator/testOnly org.apache.texera.amber.operator.machineLearning.Scorer.MachineLearningScorerOpDescSpec" ... Tests: succeeded 7, failed 0, canceled 0, ignored 0, pending 0 All tests passed. ``` ### Was this PR authored or co-authored using generative AI tooling? Generated-by: Claude Code (Claude Opus 4.8) 🤖 Generated with [Claude Code](https://claude.com/claude-code) --------- (backported from commit 3a51bfb) Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## release/v1.2 #7003 +/- ##
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- Coverage 53.95% 52.37% -1.58%
- Complexity 1441 2487 +1046
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Files 809 1077 +268
Lines 34144 42267 +8123
Branches 3448 4548 +1100
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+ Hits 18421 22138 +3717
- Misses 14815 18819 +4004
- Partials 908 1310 +402
*This pull request uses carry forward flags. Click here to find out more. ☔ View full report in Codecov by Harness. 🚀 New features to boost your workflow:
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What changes were proposed in this PR?
Backport of #6805 to
release/v1.2, cherry-picked from 3a51bfb.Source fix only. The test changes from #6805 were omitted: the touched test spec(s) do not exist on
release/v1.2(or depend on main-only test infrastructure), so backporting them cleanly is not possible. Only the source fix is carried over, per maintainer guidance.Any related issues, documentation, discussions?
Backport of #6805. Originally linked #6790.
How was this PR tested?
Release-branch CI runs on this PR. The source change cherry-picked cleanly; test changes were intentionally dropped (see above).
Was this PR authored or co-authored using generative AI tooling?
Yes — backport prepared with Claude Code (mechanical cherry-pick + conflict resolution; the change itself is #6805 by its original author).
🤖 Generated with Claude Code