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Tiny & Light weight Machine Learning Library

Project description

Bishõgrad

A Bishõ Autograd engine in python along with a lightweight deep neural-network library! (inspired from mircrograd by Andrej Karpathy)

what's Bishõ?

微小 - Bishõ is Japanese word for 'tiny' since my implementation is very tinyyyyy ^_^ compared to PyTorch/Tensorflow

what's Hako?

箱 - Hako is Japanese word for 'box' , here Hako signify the neurons in our network ;D

Installation

[!NOTE] Package is not released on pypi

  1. Manually build the wheel file and install it:

    • Clone this repo:
      git clone https://github.com/AK3847/Bishograd.git
      cd Bishograd
      
    • Use a python package manager like Rye to build the wheels:
      rye build
      
    • Use pip to install the package into your virtual env:
      pip install path/to/the/wheel/file/bishograd-0.1.0-py3-none-any.whl
      
  2. Download the temporary wheel file from here

    • Use pip to install the package into your virtual env:
      pip install path/to/the/wheel/file/bishograd-0.1.0-py3-none-any.whl
      

Example

Wonder how this works? Checkout the examples.

Targets :

  • ReLU Activation function
  • Add MLP.training() to automate the whole training code
  • Add Sigmoid, LeakyReLU & other activation functions
  • Add loss functions - categorical loss, mean-square loss etc

Contribution :

This repository is open for contribution! Primary way to contribute is to either raise an issue or a pull request with proper description and code format. You can contribute to any Targets or add new features as well.

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