neptune-sacred


Nameneptune-sacred JSON
Version 1.0.1 PyPI version JSON
download
home_pagehttps://neptune.ai/
SummaryNeptune.ai sacred integration library
upload_time2023-07-26 11:25:08
maintainer
docs_urlNone
authorneptune.ai
requires_python>=3.7,<4.0
licenseApache-2.0
keywords mlops ml experiment tracking ml model registry ml model store ml metadata store
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Neptune + Sacred Integration

Neptune is a tool used for experiment tracking, model registry, data versioning, and live model monitoring. This integration lets you use it as a UI (frontend) for the experiments you track in Sacred.

## What will you get with this integration?

* Log, display, organize, and compare ML experiments in a single place
* Version, store, manage, and query trained models, and model building metadata
* Record and monitor model training, evaluation, or production runs live

## What will be logged to Neptune?

* Hyperparameters
* Losses and metrics
* Training code (Python scripts or Jupyter notebooks) and Git information
* Dataset version
* Model configuration
* [Other metadata](https://docs.neptune.ai/logging/what_you_can_log)

![image](https://user-images.githubusercontent.com/97611089/160633857-48aa87ac-fcab-4225-8172-05aba159feaf.png)
*Example custom dashboard in the Neptune app*

## Resources

* [Documentation](https://docs.neptune.ai/integrations/sacred)
* [Code example on GitHub](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/sacred/scripts)
* [Example dashboard in the Neptune app](https://app.neptune.ai/o/common/org/sacred-integration/e/SAC-1341/dashboard/Sacred-Dashboard-6741ab33-825c-4b25-8ebb-bb95c11ca3f4)
* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/sacred/notebooks/Neptune_Sacred.ipynb)

## Example

On the command line:

```
pip install neptune-sacred
```

In Python:

```python
import neptune

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

# Create a Sacred experiment
experiment = Experiment("image_classification", interactive=True)

# Add NeptuneObserver and run the experiment
experiment.observers.append(NeptuneObserver(run=run))
experiment.run()
```

## 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


            

Raw data

            {
    "_id": null,
    "home_page": "https://neptune.ai/",
    "name": "neptune-sacred",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.7,<4.0",
    "maintainer_email": "",
    "keywords": "MLOps,ML Experiment Tracking,ML Model Registry,ML Model Store,ML Metadata Store",
    "author": "neptune.ai",
    "author_email": "contact@neptune.ai",
    "download_url": "https://files.pythonhosted.org/packages/ec/6e/798fadeb6afc708deadad66600ca6e471ce4cab91c817635da94b107e272/neptune_sacred-1.0.1.tar.gz",
    "platform": null,
    "description": "# Neptune + Sacred Integration\n\nNeptune is a tool used for experiment tracking, model registry, data versioning, and live model monitoring. This integration lets you use it as a UI (frontend) for the experiments you track in Sacred.\n\n## What will you get with this integration?\n\n* Log, display, organize, and compare ML experiments in a single place\n* Version, store, manage, and query trained models, and model building metadata\n* Record and monitor model training, evaluation, or production runs live\n\n## What will be logged to Neptune?\n\n* Hyperparameters\n* Losses and metrics\n* Training code (Python scripts or Jupyter notebooks) and Git information\n* Dataset version\n* Model configuration\n* [Other metadata](https://docs.neptune.ai/logging/what_you_can_log)\n\n![image](https://user-images.githubusercontent.com/97611089/160633857-48aa87ac-fcab-4225-8172-05aba159feaf.png)\n*Example custom dashboard in the Neptune app*\n\n## Resources\n\n* [Documentation](https://docs.neptune.ai/integrations/sacred)\n* [Code example on GitHub](https://github.com/neptune-ai/examples/tree/main/integrations-and-supported-tools/sacred/scripts)\n* [Example dashboard in the Neptune app](https://app.neptune.ai/o/common/org/sacred-integration/e/SAC-1341/dashboard/Sacred-Dashboard-6741ab33-825c-4b25-8ebb-bb95c11ca3f4)\n* [Run example in Google Colab](https://colab.research.google.com/github/neptune-ai/examples/blob/main/integrations-and-supported-tools/sacred/notebooks/Neptune_Sacred.ipynb)\n\n## Example\n\nOn the command line:\n\n```\npip install neptune-sacred\n```\n\nIn Python:\n\n```python\nimport neptune\n\n# Start a run\nrun = neptune.init_run(\n    project = \"common/sacred-integration\",\n    api_token = neptune.ANONYMOUS_API_TOKEN,\n)\n\n# Create a Sacred experiment\nexperiment = Experiment(\"image_classification\", interactive=True)\n\n# Add NeptuneObserver and run the experiment\nexperiment.observers.append(NeptuneObserver(run=run))\nexperiment.run()\n```\n\n## Support\n\nIf you got stuck or simply want to talk to us, here are your options:\n\n* Check our [FAQ page](https://docs.neptune.ai/getting_help)\n* You can submit bug reports, feature requests, or contributions directly to the repository.\n* 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),\n* You can just shoot us an email at support@neptune.ai\n\n",
    "bugtrack_url": null,
    "license": "Apache-2.0",
    "summary": "Neptune.ai sacred integration library",
    "version": "1.0.1",
    "project_urls": {
        "Documentation": "https://docs.neptune.ai/integrations/sacred/",
        "Homepage": "https://neptune.ai/",
        "Repository": "https://github.com/neptune-ai/neptune-sacred",
        "Tracker": "https://github.com/neptune-ai/neptune-sacred/issues"
    },
    "split_keywords": [
        "mlops",
        "ml experiment tracking",
        "ml model registry",
        "ml model store",
        "ml metadata store"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "13118c0fdb475ee9cf28567728df9f0c87d3d81aaa31ad32f30f7a66d7c42905",
                "md5": "1c20f423602635e8fb9533526299023c",
                "sha256": "b0059e1f66dec8aff5bdf521f0b5c515d1f44dd75b554c5825bf7636c95cb210"
            },
            "downloads": -1,
            "filename": "neptune_sacred-1.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "1c20f423602635e8fb9533526299023c",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.7,<4.0",
            "size": 10895,
            "upload_time": "2023-07-26T11:25:06",
            "upload_time_iso_8601": "2023-07-26T11:25:06.211809Z",
            "url": "https://files.pythonhosted.org/packages/13/11/8c0fdb475ee9cf28567728df9f0c87d3d81aaa31ad32f30f7a66d7c42905/neptune_sacred-1.0.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "ec6e798fadeb6afc708deadad66600ca6e471ce4cab91c817635da94b107e272",
                "md5": "3c6ddcbb779f33baf471ea4f84c7ec13",
                "sha256": "076904429e80c870e0f553303e91a9ea7618c49cb9034cce9df842cfadc1b891"
            },
            "downloads": -1,
            "filename": "neptune_sacred-1.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "3c6ddcbb779f33baf471ea4f84c7ec13",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.7,<4.0",
            "size": 9365,
            "upload_time": "2023-07-26T11:25:08",
            "upload_time_iso_8601": "2023-07-26T11:25:08.277035Z",
            "url": "https://files.pythonhosted.org/packages/ec/6e/798fadeb6afc708deadad66600ca6e471ce4cab91c817635da94b107e272/neptune_sacred-1.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-07-26 11:25:08",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "neptune-ai",
    "github_project": "neptune-sacred",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "lcname": "neptune-sacred"
}
        
Elapsed time: 0.09083s