Product Updates March’24: MosaicML Composer integration, Neptune Question Language, and Extra

I all the time stay up for sharing these updates with you! Hope you’ll discover one thing right here that may improve your workflow. Right here’s what we’ve launched within the final quarter.

New 🎉

1. MosaicML Composer integration

New integration alert! With the Neptune-Composer integration, you’ll be able to robotically log your Composer coaching metadata to Neptune.

See the instance undertaking here.

2. Help for Seaborn figures

We’re increasing the listing of supported visualizations. Now, you’ll be able to log and show Seaborn figures as PNG photographs.

3. Documentation updates

We documented the Neptune Query Language, which can be utilized to filter runs or fashions queried from a undertaking. This function is experimental. So, we’re pleased to listen to your suggestions by means of GitHub!

Oh, and by the best way, we might actually recognize it should you gave us a star and helped develop our repo.

We additionally revealed a couple of new guides and tutorials.

Tracking models end-to-end: This one reveals how one can leverage Neptune to trace a mannequin throughout all phases of its lifecycle (together with logging metadata, evaluating runs, and monitoring the mannequin in manufacturing).
Using multiple integrations at once: Right here, we’re addressing the query of whether or not you’ll be able to profit from a number of Neptune integrations on the identical time. The reply is sure. Test the information for an instance.

See different documentation news here.

Enhancements 🤓

Python consumer library

We took a step towards matching the net app’s querying capabilities: When fetching runs with fetch_runs_table(), you’ve gotten 4 new parameters: sort_by, ascending, restrict, and progress_bar. Additionally applies to model-fetching strategies: fetch_models_table() and fetch_model_versions_table(). (neptune 1.9.0)
Progress bars at the moment are enabled by default when fetching metadata through API. You may as well define and use your own bar. (neptune 1.9.0)
All messages that Neptune prints to the console are prefixed with [neptune]. (neptune 1.9.0)
We launched querying functionality to desk fetching strategies. See the Documentation updates part above. (neptune 1.10.0)
We enabled the auto-scaling of pixel values when logging figures with the as_image() methodology. (neptune 1.10.0)

Integrations

We launched the log_model_summary parameter to NeptuneCallback() ( neptune-tensorflow-keras 2.2.1)
We added assist for logging undertaking necessities with the dependencies parameter. (kedro-neptune 0.4.0)
We up to date the mixing to make use of the get_state() methodology throughout coaching. (neptune-airflow 1.0.1)