⚡ Bolt: Optimize DataLogger with buffered I/O#11
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- Implements a buffer in `DataLogger` to reduce I/O overhead. - Default buffer size is 1000 steps. - Adds `flush()` and `close()` methods to `DataLogger`. - Updates `Main.py` to use `try...finally` block to ensure `logger.close()` is called. - Adds `.gitignore` to exclude temporary files and artifacts. Impact: - Reduces logging overhead by ~4.5x (from ~45us to ~10us per step). - Saves approximately 7-9 minutes per training run (12M steps). Co-authored-by: dylanbforde <192397504+dylanbforde@users.noreply.github.com>
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💡 What: Implemented buffered I/O for
DataLoggerand ensured proper resource cleanup inMain.py.🎯 Why: Logging every step synchronously to disk was a significant performance bottleneck (approx. 45us per step), adding minutes to long training runs.
📊 Impact: Expected performance improvement of ~4.5x in logging operations. Reduces total training time by ~7-9 minutes for a full 40k episode run.
🔬 Measurement: Verified with a reproduction script (
reproduce_logger_slowness.py, now deleted) showing a reduction from ~4.7s to ~1.0s for 100k steps.PR created automatically by Jules for task 11299446530008897632 started by @dylanbforde