Comments (4)
Started on #732, but in distributed jobs, AFAICT there is a bug in accelerate with custom/external trackers (the same code works when put inside accelerate but not when outside the library). Rather than try to go deeper into it, I think it's better to finally make the move to migrate these callbacks to their respective ML frameworks.
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Related to #221
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Completed in huggingface/accelerate#2139
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Amazing, @dberenbaum ! good stuff.
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Related Issues (20)
- Log metrics/models etc... to studio directly with Live or DVCLiveCallbacks in training script HOT 9
- integrations: lightning fabric
- `log_image` fails to save an image if the path was provided, but the `name` does not have an extension HOT 1
- 4.0 Checklist HOT 1
- Add user friendly warning/error messages and helpers for log_plot() HOT 3
- Foreach to run multiple experiments HOT 3
- DVCLive throws a weird warning when origin is not defined HOT 6
- Add docstrings HOT 2
- Invalid path causes `TypeError` due to shadowed builtin `type` HOT 2
- `Live.log_artifact` raises `ValueError` by logging to closed `stderr` when Tensorflow is imported first HOT 6
- `log_image`: log bounding boxes HOT 5
- Test falling for Huggingface
- Path not supported for some path arguments HOT 2
- Error RuntimeError: SQLite version is too old, please upgrade to >= (3, 8, 3) HOT 7
- Provide examples or quick code snippets in the public methods
- System metrics should be plotted with `timestamp` rather than `step`
- log_sklearn_plot: exception when plot params are passed. HOT 3
- DVC Live hangs when pushing to remote HOT 3
- What is the proper way of enabling intermediate checkpointing when using pytorch lightning+dvc+dvclive? HOT 2
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