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https://github.com/andresnowak/Micro-Mojograd
https://github.com/andresnowak/Micro-Mojograd
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/andresnowak/Micro-Mojograd
- Owner: andresnowak
- License: mit
- Created: 2023-09-12T00:53:27.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-11-25T20:16:24.000Z (about 1 year ago)
- Last Synced: 2024-02-11T18:46:15.016Z (11 months ago)
- Size: 57.6 KB
- Stars: 4
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- awesome-mojo - Micro-Mojograd - Implementation of Karpathy's micrograd in Mojo. (🗂️ Libraries / AI)
README
# Micro-Mojograd
This is for now going to be a **Toy project** to learn about how do tensors work, how to make them efficient, how to do the computational graph efficiently (like joining element wise operationss or making a tensors contiguous when it used in more than one operation *use more memory but have better performance*, etc...) and the Autograd part.
When the language is a bit more mature and has complete lifetime and ownership support and Traits support, I will try to make a more complete version of this library, or maybe help another mojo project like [numojo](https://github.com/MadAlex1997/Mojo-Arrays) or [Infermo](https://github.com/TilliFe/Infermo)
And it is going to be inspired by:
- [Micrograd](https://github.com/karpathy/micrograd)
- [Pytorch](https://github.com/pytorch/pytorch)
- [Tinygrad](https://github.com/tinygrad/tinygrad)## To-do
- [x] Tensor: using 1d memory and not using MLIR
- [x] Tensor Matmul
- [x] Tensor sum elementwise
- [x] Tensor Mul elementwise
- [x] Tensor equal operator
- [ ] Tensor broadcasting
- [ ] Fix problem where parallel version of element-wise operations (add, mul, eq, etc.) are slower than the sequential version.
- [ ] Autograd: _For now doing the autogradient part is difficult, because mojo still doesn't have complete ownership and lifetime support._