Inspected ve2e main at ec5d24c6 without changing it.
Traced ClearML OutputModel uploads and InputModel.get_local_copy() loading.
Documented Lightning main checkpoints, custom self-contained EMA payloads, slim DINO filtering, embedded configs, architecture construction, and EMA loading.
Identified gaps in the current model-ID inference loader and proposed one shared loader for main and EMA checkpoints.
Lessons Learned: Pitfalls
The knowledge base has no clinical workstream directory even though the required skill lists it. Infrastructure was used because this task centered on ClearML storage.
Similar inference loading logic is duplicated across scripts, but some copies omit key migration and load validation.
Lessons Learned: Improvements
Add a durable ve2e checkpoint contract that states key prefixes, required payload fields, main/EMA dispatch, and legacy compatibility.
Centralize ClearML fetch and architecture-weight loading in production code, then make inference scripts use it.
