From 9196daf7781f84100d06b3704558ba69b3794a46 Mon Sep 17 00:00:00 2001 From: Manu S Joseph Date: Thu, 7 Dec 2023 09:11:31 +0100 Subject: [PATCH] Corrected all training data deletion function documentation in user guides --- docs/user_guides/fs/feature_view/training-data.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/user_guides/fs/feature_view/training-data.md b/docs/user_guides/fs/feature_view/training-data.md index 538609842..6d56ab652 100644 --- a/docs/user_guides/fs/feature_view/training-data.md +++ b/docs/user_guides/fs/feature_view/training-data.md @@ -101,7 +101,7 @@ To clean up unused training data, you can delete all training data or for a part feature_view.delete_training_dataset(version=1) # delete all training datasets -feature_view.delete_training_dataset() +feature_view.delete_all_training_datasets() ``` It is also possible to keep the metadata and delete only the materialised files. Then you can recreate the deleted files by just specifying a version, and you get back the exact same dataset again. This is useful when you are running out of storage. ```python