Hey team, Aim 3.10 is now available!
We are on a mission to democratize AI dev tools. Thanks to the awesome Aim community for the help and contributions.
Here is what’s new in Aim 3.10:
- Visualize terminal logs
- M1 support
- Better autocomplete experience
- Aim citation available
- CatBoost integration
- LightGBM integration
Visualize terminal logs
When it comes to automating training of multiple runs with job schedulers or workload managers on a cluster, it becomes hard to track the terminal logs of the runs.
Now Aim automatically streams the terminal logs to the UI. Near-real-time.
The terminal logs can be turned off if the run instance is created with the following flag in place:
aim_run = Run(capture_terminal_logs=False)
Check out more about this feature in Aim docs.
With the awesome work by the PyTorch team on enabling support for GPU-accelerated PyTorch training on Mac, there has been a huge demand to enable aim on M1 as well.
Aim now supports M1 too. Now you can use Aim with PyTorch on Mac to track and deeply compare your experiments 😊.
Better autocomplete experience
We have integrated a rich code autocomplete system as the Aim community loves to deeply query their training runs. This has been a highly requested improvement and a huge productivity booster. Expect more improvements here ❤️
Aim citation available
Now you can cite Aim from your paper if you are using Aim to compare your experiments. The citation file.
Here is a short example that shows how to use AimLogger for CatBoost.
LightGBM is one of the most widely-used and battle-tested gradient boosting frameworks. Due to high-demand we have also added an out-of-the-box Aim LightGBM integration.
We have been incredibly lucky to get help and contributions from the amazing Aim community. It’s humbling and inspiring.