AMOOOMA opened a new issue, #40715:
URL: https://github.com/apache/beam/issues/40715

   ### What would you like to happen?
   
   `RunInference.expand()` scopes the `model_identifier` transform annotation 
to the `BeamML_RunInference` step via 
`pipeline.transform_annotations(model_identifier=...)` (see #40671). Because 
`transform_annotations` applies to every sub-transform applied inside the 
context, when `with_exception_handling(threshold=<1.0)` is used, the 
threshold-checking transforms that 
`_ExceptionHandlingWrapper._post_process_result` adds (`CountTotal`, 
`CountBad`, `CombineGlobally`, `CheckThreshold`, ...) also inherit the 
`model_identifier` annotation, even though they never run `_RunInferenceDoFn`:
   
   
https://github.com/apache/beam/blob/5b6aa703f0ab6a48d92cc63ea89226485cc265f9/sdks/python/apache_beam/transforms/core.py#L2414
   
   This is harmless for Dataflow today (only `ParDo` steps consume the 
annotation and the threshold steps are tiny), but it is imprecise. We should 
refactor so the annotation is attached only to the inner inference `ParDo`, 
e.g.:
   
   - expose a hook on `_ExceptionHandlingWrapper` / 
`ParDo.with_exception_handling` to annotate only the wrapped `ParDo` built in 
`_build_pardo`, or
   - apply the annotation to `run_inference_pardo` directly (e.g. via 
`PTransform.annotations()` on a thin `ParDo` subclass) instead of using the 
pipeline-level `transform_annotations` context manager.
   
   Follow-up from the discussion in 
https://github.com/apache/beam/pull/40671#discussion_r4342559127.
   
   ### Issue Priority
   
   Priority: 3 (nice-to-have improvement)
   
   ### Issue Components
   
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