khisr0w/grazie
Pure C tensor and autograd library for training neural networks
This C library helps developers understand and implement the core mathematical operations for neural networks. It takes numerical data arranged in multi-dimensional arrays (tensors) and processes them using fundamental operations like matrix multiplication and division, along with automatic differentiation. This tool is for C programmers who want to build highly efficient deep learning components from scratch, without relying on external libraries or dynamic memory allocation during runtime.
No commits in the last 6 months.
Use this if you are a C developer who wants to implement deep learning models with maximum control and efficiency, focusing on the mathematical fundamentals and avoiding external dependencies.
Not ideal if you are looking for a high-level deep learning framework with extensive pre-built models, automatic memory management, and GPU acceleration out-of-the-box.
Stars
9
Forks
—
Language
C
License
BSD-2-Clause
Category
Last pushed
Feb 19, 2025
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/khisr0w/grazie"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
JonathanRaiman/theano_lstm
:microscope: Nano size Theano LSTM module
google/tangent
Source-to-Source Debuggable Derivatives in Pure Python
ahrefs/ocannl
OCANNL: OCaml Compiles Algorithms for Neural Networks Learning
yoshoku/numo-openblas
Numo::OpenBLAS builds and uses OpenBLAS as a background library for Numo::Linalg
statusfailed/catgrad
a categorical deep learning compiler