tidygrad

Name	tidygrad JSON
Version	0.0.1 JSON
	download
home_page	https://github.com/xl0/tidygrad
Summary	A tidy library for gradient-based optimization
upload_time	2023-10-14 15:32:33
maintainer
docs_url	None
author	Alexey
requires_python	>=3.7
license	MIT License
keywords	nbdev jupyter notebook python
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            TidyGrad
================

<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->

# TidyGrad \| [Documentation](https://xl0.github.io/tidygrad/) \| [Discord](https://discord.gg/qBaqauUWXP)

A tidy library for gradient-based optimization

![Tests](https://github.com/xl0/tidygrad/actions/workflows/test.yaml/badge.svg)

## Install

``` sh
pip install -e tidygrad
```

## Dev

``` sh
pip install -e .[dev] # Local install with dev dependencies
```

- Hack
- Hack
- Hack
- (edit and run the notebooks in the `./nbs` directory).

``` sh
nbdev_prepare
```

`nbdev_prepare` will:

- Export all norebooks into the `./tidygrad` directory.
  - Note: the notebooks themselves have an export cell, so they are
    exported every time you run them.
- Run all notebooks (equivalent of testing)
- Generate REDME.md from the index.ipynb
- Generate the docs

## How to use

``` python
# Later
```

            

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