Metadata-Version: 2.1
Name: froog
Version: 0.1.2
Summary: FROG: Fast Real-time Optimization of Gradients
Author: Kevin Buhler
License: MIT
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: requests

# frog <img src="https://github.com/kevbuh/frog/actions/workflows/test.yml/badge.svg" alt="unit test badge" >
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  <img src="https://github.com/kevbuh/frog/blob/main/assets/froog.jpeg" alt="froog the frog" height="300">
  
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  frog: fast real-time optimization of gradients 
  <br/>
  <a href="https://github.com/kevbuh/frog/tree/main/docs">documentation</a> | <a href="https://github.com/kevbuh/frog/tree/main/examples">examples</a> 
  <br/>
  <br/>
</div>

a beautifully compact machine-learning library

modern ml development is unintuitive, time consuming, and unaccessible. why not make it possible for anyone to build?


### Overview of Features
- Tensors
- Automatic Differentiation
    - Forward and backward passes
- Input/gradient shape-tracking
- MNIST example
- 2D Convolutions (im2col)
- Gradient checking
- The most common optimizers (SGD, Adam, RMSProp)

### Math Operations
- Scalar-Matrix Multiplication
- Dot Product
- Sum
- ReLU
- Log Softmax
- 2D Convolution

# Bounties

We really want to get a useful model working right out of the box! Our top bounty is to get EfficientNet v2 model working inside of the <a href="https://github.com/kevbuh/frog/tree/main/examples">examples</a>  folder.

- EfficientNet v2 (**top priority**)

#### Easy
- built in MLP model
- binary cross entropy
- dropout layer
- flatten

#### Medium
- publish to pip3
- simplify how context and gradients are handled

#### Hard
- Transformers
- Stable Diffusion
- Winograd Convs
- MPS support
- CUDA support

# Contributing

Here are some basic guidelines for contributing:

* Reduce code
* Increase speed
* Add features
* In that order

Bug fixes are the best and always welcome
Conceptual cleanups are great
All features must include <a href="https://github.com/kevbuh/frog/tree/main/tests">tests</a>
