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Hi, I Have A Future Roadmap Question On Clearml-Datasets. The Current Implementation Works Well For Small Datasets But Its Rather In Effective For Very Large Datasets. For Example, Let'S Say I Have 10 Million Images Just For The Training Dataset, And My T


SubstantialElk6 I just realized 3 weeks passed, wow!
So the good news we have some new examples:
https://github.com/allegroai/clearml/blob/master/examples/pipeline/pipeline_from_decorator.py
https://github.com/allegroai/clearml/blob/master/examples/pipeline/pipeline_from_functions.py
The bad news the documentation was postponed a bit, as we are still messaging the interface (the community is constantly pushing for great ideas and uses cases , and they are just too good to miss out 🙂 )
We added nested components and call backs and a metric/artifacts/model auto logging
https://github.com/allegroai/clearml/blob/b010f775bdd72ba6729f5e1e569626692d7b18af/clearml/automation/controller.py#L454

I'm hopeful that we will be able to push an initial version next week.
Please ping if you hear nothing, we appreciate it, and it really helps with prioritizing things 🙂

  
  
Posted 2 years ago
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