semvec/pypi-packages huggingface dataset:
neptune-optuna 1.4.1
Neptune.ai Optuna integration library
License: Apache-2.0
Requires Python: <4.0,>=3.7
Keywords: MLOps, ML Experiment Tracking, ML Model Registry, ML Model Store, ML Metadata Store

# Neptune + Optuna integration

Neptune is a lightweight experiment tracker that offers a single place to track, compare, store, and collaborate on experiments and models.

This integration lets you use it as an Optuna visualization dashboard to log and monitor hyperparameter sweeps live.

## What will you get with this integration?

* Log and monitor the Optuna hyperparameter sweep live:
  * values and params for each Trial
  * best values and params for the Study
  * hardware consumption and console logs
  * interactive plots from the optuna.visualization module
  * parameter distributions for each Trial
  * Study object itself for 'InMemoryStorage' or the database location for the Studies with database storage
* Load the Study directly from the existing Neptune run

![image](https://docs.neptune.ai/img/app/integrations/optuna.png)

## Resources

* [Documentation](https://docs.neptune.ai/integrations/optuna)
* [Code example on GitHub](https://github.com/neptune-ai/examples/blob/main/integrations-and-supported-tools/optuna/scripts)
* [Run logged in the Neptune app](https://app.neptune.ai/o/common/org/optuna-integration/runs/details?viewId=b6190a29-91be-4e64-880a-8f6085a6bb78&detailsTab=dashboard&dashboardId=Vizualizations-5ea92658-6a56-4656-b225-e81c6fbfc8ab&shortId=NEP1-18517&type=run)
* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/master/integrations-and-supported-tools/optuna/notebooks/Neptune_Optuna_integration.ipynb)

## Example

On the command line:

```
pip install neptune-optuna
```

In Python:

```python
import neptune
import neptune.integrations.optuna as npt_utils

# Start a run
run = neptune.init_run(
    api_token=neptune.ANONYMOUS_API_TOKEN,
    project="common/optuna-integration",
)

# Create a NeptuneCallback instance
neptune_callback = npt_utils.NeptuneCallback(run)

# Pass the callback to study.optimize()
study = optuna.create_study(direction="maximize")
study.optimize(objective, n_trials=100, callbacks=[neptune_callback])

# Watch the optimization live in Neptune
```

## Support

If you got stuck or simply want to talk to us, here are your options:

* Check our [FAQ page](https://docs.neptune.ai/getting_help)
* You can submit bug reports, feature requests, or contributions directly to the repository.
* Chat! When in the Neptune application click on the blue message icon in the bottom-right corner and send a message. A real person will talk to you ASAP (typically very ASAP),
* You can just shoot us an email at support@neptune.ai