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FROG: Fast Real-time Optimization of Gradients

Project description

frog unit test badge

froog the frog
frog: fast real-time optimization of gradients
documentation | examples | documentation | pypi | github

a beautifully compact machine-learning library

Installation

pip install froog

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 examples folder.

  • EfficientNet v2 (top priority)

Easy

  • built in MLP model
  • binary cross entropy
  • dropout layer
  • flatten

Medium

  • 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 tests

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