pyfit

A minimalist neural networks library built on a tiny autograd engine. Very much inspired by the micrograd library created by Andrej Karpathy.

Overview

This project aims to:

demonstrate automatic differentiation, a core concept of modern Deep Learning frameworks like PyTorch and TensorFlow;
define a simple API for training neural nets, somehow mimicking Keras and PyTorch Ignite;
follow good coding practices, including type annotations and unit tests.

The demo notebook showcases what pyfit is all about.

pyfit uses the following tools:

Run the following commands in project root folder to check the codebase.

> pylint pyfit/* tests/*  # linting (including type checks)
> mypy .  # type checks only
> pytest  # test suite

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for pyfit 1.0.2
File	Size	Uploaded
pyfit-1.0.2.tar.gz	5.6 kB	Mar 26, 2024	Details

Table of built distributions (wheels) for pyfit 1.0.2
File	Interpreter	ABI	Platform	Reset
pyfit-1.0.2-py3-none-any.whl 7.5 kB Mar 26, 2024	Python 3	none	any	Details

Total release size: 13.1 kB

Download URL	pyfit-1.0.2.tar.gz
Size	5.6 kB
Tags	Source
SHA-256 checksum How to use checksums	`616dea6249546f9f84f95fad38c6c8fcaf134410e6c71af87226cf06d3d55a30`
BLAKE2b-256 checksum How to use checksums	`d5437c8815508429a81234eb428ffa0d9d189c6a9d5fa7f5476a301ae75e1ad6`
Upload date	Mar 26, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.0.0 CPython/3.12.2`

Download URL	pyfit-1.0.2-py3-none-any.whl
Size	7.5 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`56a0bd6e0381dbdc7306a610d8d89c6ddc0fece35afb7f481d371f4a4f49e994`
BLAKE2b-256 checksum How to use checksums	`578fdbe49293dc4dc2c73f43a2dd09b783f662e1057207914b096a93eeee818a`
Upload date	Mar 26, 2024
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/5.0.0 CPython/3.12.2`