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  1. Red Hat Enterprise Linux AI
  2. RHELAI-3895

enable flexible, portable logging backends (wandb, tensorboard, etc.)

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      Today, logging in the training library consists of async_logger.py, and the python logger. redesign this structure to follow something like: https://github.com/meta-llama/llama-stack/pull/1362

      category based logging, especially in a modularized library, providers users with a much better idea of what is happening where.

              rh-ee-fschmitt Fynn Schmitt-Ulms
              cdoern@redhat.com Charles Doern
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