froog 0.1.4

FROG: Fast Real-time Optimization of Gradients

frog

frog: fast real-time optimization of gradients
a beautifully compact machine-learning library
homepage | documentation | examples| pip

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, currently at 585 lines
• Increase speed
• Add features
• In that order

Bug fixes are the best and always welcome Conceptual cleanups are great All features must include tests