Metadata-Version: 2.1
Name: neptune-pytorch
Version: 2.0.0
Summary: Neptune.ai pytorch integration library
Home-page: https://neptune.ai/
License: Apache-2.0
Keywords: MLOps,ML Experiment Tracking,ML Model Registry,ML Model Store,ML Metadata Store
Author: neptune.ai
Author-email: contact@neptune.ai
Requires-Python: >=3.7,<4.0
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Operating System :: MacOS
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Provides-Extra: dev
Requires-Dist: importlib-metadata ; python_version < "3.8"
Requires-Dist: neptune (>=1.0.0) ; extra == "dev"
Requires-Dist: pre-commit ; extra == "dev"
Requires-Dist: pydot ; extra == "dev"
Requires-Dist: pytest (>=5.0) ; extra == "dev"
Requires-Dist: pytest-cov (==2.10.1) ; extra == "dev"
Requires-Dist: torch (>1.8.0)
Requires-Dist: torchviz ; extra == "dev"
Project-URL: Documentation, https://docs.neptune.ai/integrations-and-supported-tools/model-training/pytorch
Project-URL: Repository, https://github.com/neptune-ai/neptune-pytorch
Project-URL: Tracker, https://github.com/neptune-ai/neptune-pytorch/issues
Description-Content-Type: text/markdown

# Neptune - PyTorch integration

Experiment tracking for PyTorch-trained models.

## What will you get with this integration?

* Log, organize, visualize, and compare ML experiments in a single place
* Monitor model training live
* Version and query production-ready models and associated metadata (e.g., datasets)
* Collaborate with the team and across the organization

## What will be logged to Neptune?

* Training metrics
* Model checkpoints
* Model predictions
* [Other metadata](https://docs.neptune.ai/logging/what_you_can_log)

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

## Resources

* [Documentation](https://docs.neptune.ai/integrations/pytorch/)
* [Code example on GitHub](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/pytorch/scripts)
* [Example project in the Neptune app](https://app.neptune.ai/o/common/org/pytorch-integration/runs/details?viewId=standard-view&detailsTab=dashboard&dashboardId=9920962e-ff6a-4dea-b551-88006799b116&shortId=PYTOR1-7411&type=run)

## Example



```python
from neptune_pytorch import NeptuneLogger

run = neptune.init_run()
neptune_logger = NeptuneLogger(
    run,
    model=model,  # your torch Model()
    log_model_diagram=True,
    log_gradients=True,
    log_parameters=True,
    log_freq=30,
)
```

## 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! In the Neptune app, click 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](mailto:support@neptune.ai).

