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Visualization for MLX Training logs #14
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Pull request overview
This pull request adds a comprehensive visualization feature for MLX training logs. The implementation includes a script that parses training logs, extracts various metrics (loss, learning rate, throughput, memory usage, etc.), and generates informative plots to help analyze training runs.
Changes:
- Added
scripts/visualize_mlx_training.pywith log parsing, run management, and visualization capabilities - Added unit tests for log parsing and run management functionality
- Added matplotlib as a dependency in
pyproject.toml
Reviewed changes
Copilot reviewed 3 out of 4 changed files in this pull request and generated 4 comments.
| File | Description |
|---|---|
| scripts/visualize_mlx_training.py | New script implementing MLX training log parser, run manager, and visualizer with support for both individual and combined plot generation |
| tests/test_visualize_mlx_training.py | Unit tests for log parsing and run management functionality |
| pyproject.toml | Added matplotlib dependency for visualization support |
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Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Description
This pull request adds visualization feature with 6 plots currently , keeping the current MLX training setup in mind. The image contents are as follows :
How to Test
Checklist
Added
matplotlibtopyproject.tomlUnit-testing is included by
pytest tests/test_visualize_mlx_training.py -vAdditional Information
The visualization code is folder friendly, it creates the plots for the latest timestamp, or specific if provided as an argument.