Botao Chen c294a01c4b [2/n][torchtune integration] implement job management and return training artifacts (#593) ... ### Context In this PR, we - Implement the post training job management and get training artifacts apis - get_training_jobs - get_training_job_status - get_training_job_artifacts - get_training_job_logstream is deleted since the trace can be directly accessed by UI with Jaeger https://llama-stack.readthedocs.io/en/latest/building_applications/telemetry.html#jaeger-to-visualize-traces - Refactor the post training and training types definition to make them more intuitive. - Rewrite the checkpointer to make it compatible with llama-stack file system and can be recognized during inference ### Test Unit test `pytest llama_stack/providers/tests/post_training/test_post_training.py -m "torchtune_post_training_huggingface_datasetio" -v -s --tb=short --disable-warnings` <img width="1506" alt="Screenshot 2024-12-10 at 4 06 17 PM" src="https://github.com/user-attachments/assets/16225029-bdb7-48c4-9d13-e580cc769c0a"> e2e test with client side call <img width="888" alt="Screenshot 2024-12-10 at 4 09 44 PM" src="https://github.com/user-attachments/assets/de375e4c-ef67-4dcc-a045-4037d9489191">		2024-12-13 15:00:04 -08:00
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__init__.py	API Updates (#73)	2024-09-17 19:51:35 -07:00
post_training.py	[2/n][torchtune integration] implement job management and return training artifacts (#593)	2024-12-13 15:00:04 -08:00