Commit 2ce1570

committed

Revert "Fix long regresion"

This reverts commit 4fa4823.

1 parent 4fa4823 commit 2ce1570Copy full SHA for 2ce1570

File tree

-3

lines changed

-3

lines changed

Lines changed: 3 additions & 2 deletions

Original file line number	Diff line number	Diff line change
`@@ -249,9 +249,10 @@ def _fit(self, X: Dict[str, Any], y: Any = None, **kwargs: Any) -> 'TrainerChoic`
`249`	`249`	`)`
`250`	`250`
`251`	`251`	`# Support additional user metrics`
`252`		`- additional_metrics = X['additional_metrics'] if 'additional_metrics' in X else []`
	`252`	`+ additional_metrics = X['additional_metrics'] if 'additional_metrics' in X else None`
`253`	`253`	`if 'optimize_metric' in X:`
`254`		`- additional_metrics.append(X['optimize_metric'])`
	`254`	`+ additional_metrics = additional_metrics.append(X['optimize_metric']) if additional_metrics is not None \`
	`255`	`+ else [X['optimize_metric']]`
`255`	`256`	`additional_losses = X['additional_losses'] if 'additional_losses' in X else None`
`256`	`257`	`self.choice.prepare(`
`257`	`258`	`model=X['network'],`

Lines changed: 1 addition & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -153,7 +153,7 @@ def test_can_properly_fit_a_config(openml_task_id, configuration, scorer, lower_`
`153`	`153`	`train_data, target_data = fit_dictionary['backend'].load_datamanager().train_tensors`
`154`	`154`	`predictions = pipeline.predict(train_data[val_indices])`
`155`	`155`	`score = scorer(fit_dictionary['y_train'][val_indices], predictions)`
`156`		`- assert score >= lower_bound_score`
	`156`	`+ assert pytest.approx(score) >= lower_bound_score`
`157`	`157`
`158`	`158`	`# Check that we reverted to the best score`
`159`	`159`	`run_summary = pipeline.named_steps['trainer'].run_summary`

Comments

(0)