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improve error handling in create_training_dataset#3146

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deruyter92 wants to merge 3 commits intoDeepLabCut:mainfrom
deruyter92:jaap/refactor_code_formatting
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improve error handling in create_training_dataset#3146
deruyter92 wants to merge 3 commits intoDeepLabCut:mainfrom
deruyter92:jaap/refactor_code_formatting

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@deruyter92 deruyter92 commented Nov 13, 2025

Motivation: user feedback can be improved for invalid / deprecated arguments in create_training_dataset

Changes:

  • Instead of a failing function call to nonexitent code parse_available_models , now a ValueError error is raised for argument superanimal_name , providing the user instructions to the correct usage.
  • Add warning for empty annotated dataset. This addresses silent errors for incorrect bodypart configuration. (labeled data disappears after reindexing)
  • add ValueError for unsupported argument weight_init for tensorflow engine in create_training_dataset

@deruyter92 deruyter92 changed the title Jaap/refactor code formatting Jaap/small_refactors Nov 24, 2025
@deruyter92 deruyter92 marked this pull request as ready for review December 4, 2025 10:27
@deruyter92 deruyter92 force-pushed the jaap/refactor_code_formatting branch from d8cafa5 to 768ec3f Compare January 26, 2026 12:11
- Raise ValueError for `superanimal_name` Instead of a failing function call to nonexitent code `parse_available_models` , now a ValueError error is raised, providing the user instructions to the correct usage.
- Add warning for empty annotated dataset. This addresses silent errors for incorrect bodypart configuration. (labeled data disappears after reindexing)
- add ValueError for unsupported argument `weight_init` for tensorflow engine in `create_training_dataset`.
@deruyter92 deruyter92 force-pushed the jaap/refactor_code_formatting branch from 768ec3f to 846cd16 Compare January 26, 2026 12:14
@deruyter92 deruyter92 changed the title Jaap/small_refactors improve error handling in create_training_dataset Jan 26, 2026
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cleaned this PR and added more informative description

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@C-Achard C-Achard left a comment

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LGTM

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2 participants