samrere/pytortto

deep learning from scratch. uses numpy/cupy, trains in GPU, follows pytorch API

26
/ 100
Experimental

This project offers a deep learning framework built from scratch using NumPy and CuPy, designed for those who want to understand the inner workings of models without the complexity of a full-fledged library. You input your datasets and model architectures, and it outputs trained deep learning models and gradients, providing a clear view into each computational step. This is ideal for deep learning researchers and students who are focused on pedagogical exploration rather than raw performance.

No commits in the last 6 months.

Use this if you are a deep learning student or researcher who wants to learn how frameworks like PyTorch handle operations, backpropagation, and memory management by implementing a full-featured framework yourself.

Not ideal if you need to train large-scale production models quickly, as its primary goal is educational insight, not speed or cutting-edge features.

deep-learning-education neural-network-implementation machine-learning-research computational-graphs model-architecture-study
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 4 / 25

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21

Forks

1

Language

Python

License

MIT

Last pushed

Sep 05, 2023

Commits (30d)

0

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