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Object detection: Enable loading from checkpoint  #6670

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@LittleLittleCloud

It would be nice if I can pass a checkpoint folder to the object detection trainer option, which can be used to save and load intermediate weight for every N epoch/step/epic. In that case I don't have to retrain the model from the beginning everytime.

In the meantime, It would also be nice if object detection trainer will return instead of throw a cancellationException when mlcontext.CancelExcute get called.

Both features will allow user to pause training process whenever they want and restart training from preivous progress. This would be super useful for deep learning scenarios.

Describe the solution you'd like

  • in training option, accept a checkpoint folder
  • when cancelling, don't throw error, just return current result

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  1. ghost added
    untriagedNew issue has not been triaged
    on May 10, 2023
  2. michaelgsharp commented on Jan 24, 2024

    @michaelgsharp
    Contributor

    Is this for the new TorchSharp stuff @LittleLittleCloud? @luisquintanilla any thoughts on this?

  3. LittleLittleCloud commented on Jan 25, 2024

    @LittleLittleCloud
    MemberAuthor

    yes, for the new torchsharp model only

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    area-VisionImage processing and computer visionenhancementNew feature or requestneeds-further-triageNeeds deeper review after initial triageuntriagedNew issue has not been triagedyellowmaintenance only

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