jellyml-lightning


Namejellyml-lightning JSON
Version 1.0.1 PyPI version JSON
download
home_page
SummaryA plugin to jelly-fill lightning checkpoints
upload_time2023-02-01 16:30:06
maintainer
docs_urlNone
author
requires_python
license
keywords pytorch jellyml lightning pytorch lightning model code snapshot embed library tool
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # JellyMl

JellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code 
             | into a checkpoint of a pytorch model.
Learn more at [jellyml.com](jellyml.com)

## Structure of the jellyml repository
(Note that the jellyml repository is a monorepo. If you are
reading this from the python package source code,
go to github.com/mmulet/jellyml to see the whole repository)

- jellyml is the source for the python package
- jellyml-lightning is the source for pytorch lightning plugin
- client is the source for the website
- dev_server is the source for the development server of the website

## Build

### jellyml

1. Make a venv
```sh
python3 -m venv venv
# activate the venv ( depends on your shell and OS)
# see https://docs.python.org/3/library/venv.html
# bash
source venv/bin/activate
```
2. Install build
```sh
pip install build
```
3.  Build the package
```sh
cd jellyml
python -m build
pip install dist/jellyml-0.0.1-py3-none-any.whl
```

### jellyml-lightning
1. Follow the directions for building and installing jellyml.
   jellyml is a dependency of jellyml-lightning.
2. Build the package
```sh
cd jellyml-lightning
python -m build
pip install dist/jellyml-lightning-0.0.1-py3-none-any.whl
```

### Website

#### Build the website

```sh
cd client
npm install .
cd ../dev_server
npm install .
npm run build
```

#### Dev the website

```sh
cd client
npm install .
cd ../dev_server
npm install .
npm run build
```

## Tests

Located in the source files in src/jellyml. Have the prefix test\_.
Run them as a module

```sh
cd src;
python3 -m jellyml.test_all
```

            

Raw data

            {
    "_id": null,
    "home_page": "",
    "name": "jellyml-lightning",
    "maintainer": "",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "",
    "keywords": "pytorch,jellyml,lightning,pytorch lightning,model,code,snapshot,embed,library,tool",
    "author": "",
    "author_email": "Michael Mulet <mike@jellyml.com>",
    "download_url": "https://files.pythonhosted.org/packages/76/43/eae46c1de7ff9dc995b1d9044ad550d15dc2c0f16664770d0f439d8e7e59/jellyml-lightning-1.0.1.tar.gz",
    "platform": null,
    "description": "# JellyMl\n\nJellyML is an open-source tool (python API and command line) for effortlessly embedding a snapshot of your code \n             | into a checkpoint of a pytorch model.\nLearn more at [jellyml.com](jellyml.com)\n\n## Structure of the jellyml repository\n(Note that the jellyml repository is a monorepo. If you are\nreading this from the python package source code,\ngo to github.com/mmulet/jellyml to see the whole repository)\n\n- jellyml is the source for the python package\n- jellyml-lightning is the source for pytorch lightning plugin\n- client is the source for the website\n- dev_server is the source for the development server of the website\n\n## Build\n\n### jellyml\n\n1. Make a venv\n```sh\npython3 -m venv venv\n# activate the venv ( depends on your shell and OS)\n# see https://docs.python.org/3/library/venv.html\n# bash\nsource venv/bin/activate\n```\n2. Install build\n```sh\npip install build\n```\n3.  Build the package\n```sh\ncd jellyml\npython -m build\npip install dist/jellyml-0.0.1-py3-none-any.whl\n```\n\n### jellyml-lightning\n1. Follow the directions for building and installing jellyml.\n   jellyml is a dependency of jellyml-lightning.\n2. Build the package\n```sh\ncd jellyml-lightning\npython -m build\npip install dist/jellyml-lightning-0.0.1-py3-none-any.whl\n```\n\n### Website\n\n#### Build the website\n\n```sh\ncd client\nnpm install .\ncd ../dev_server\nnpm install .\nnpm run build\n```\n\n#### Dev the website\n\n```sh\ncd client\nnpm install .\ncd ../dev_server\nnpm install .\nnpm run build\n```\n\n## Tests\n\nLocated in the source files in src/jellyml. Have the prefix test\\_.\nRun them as a module\n\n```sh\ncd src;\npython3 -m jellyml.test_all\n```\n",
    "bugtrack_url": null,
    "license": "",
    "summary": "A plugin to jelly-fill lightning checkpoints",
    "version": "1.0.1",
    "split_keywords": [
        "pytorch",
        "jellyml",
        "lightning",
        "pytorch lightning",
        "model",
        "code",
        "snapshot",
        "embed",
        "library",
        "tool"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "7b54403fd6864b388d0ba899ea4f3d6403f0f1759618faf7b35cd5e4e7a28c0c",
                "md5": "1a0eb102bd171269af2464ddc7ee3b1d",
                "sha256": "7c86be26d2f4fabd1b23a855c0a9010e09ee1da71b92c7ab800376bf5e8a2090"
            },
            "downloads": -1,
            "filename": "jellyml_lightning-1.0.1-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "1a0eb102bd171269af2464ddc7ee3b1d",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 5555,
            "upload_time": "2023-02-01T16:30:04",
            "upload_time_iso_8601": "2023-02-01T16:30:04.336390Z",
            "url": "https://files.pythonhosted.org/packages/7b/54/403fd6864b388d0ba899ea4f3d6403f0f1759618faf7b35cd5e4e7a28c0c/jellyml_lightning-1.0.1-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "7643eae46c1de7ff9dc995b1d9044ad550d15dc2c0f16664770d0f439d8e7e59",
                "md5": "58568a657461a800e18c831f9e7f6c8a",
                "sha256": "a4e75380f76b97d52010d19b2405e0d53a211a4004e2b021253f3a2af884ab37"
            },
            "downloads": -1,
            "filename": "jellyml-lightning-1.0.1.tar.gz",
            "has_sig": false,
            "md5_digest": "58568a657461a800e18c831f9e7f6c8a",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 4817,
            "upload_time": "2023-02-01T16:30:06",
            "upload_time_iso_8601": "2023-02-01T16:30:06.827154Z",
            "url": "https://files.pythonhosted.org/packages/76/43/eae46c1de7ff9dc995b1d9044ad550d15dc2c0f16664770d0f439d8e7e59/jellyml-lightning-1.0.1.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-02-01 16:30:06",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "lcname": "jellyml-lightning"
}
        
Elapsed time: 0.04370s