MiniTorch

MiniTorch is an experimental neural-network framework built from scratch.

Architecture

  • C++ numerical core
  • Python API
  • CPU backend
  • Future Vulkan backend
  • Automatic differentiation
  • Neural-network modules
  • Optimizers
  • Transformer support
  • Hardware-aware execution
  • GPU watchdog
  • Adaptive fallback

Current Version

V0.2.0

V0.2 Features

  • requires_grad
  • Gradient storage
  • Computational graph
  • backward()
  • Gradient accumulation
  • zero_grad()
  • Addition backward
  • Subtraction backward
  • Multiplication backward
  • Matrix multiplication backward
  • Sum backward

Build on Termux

./scripts/build_termux.sh

Roadmap

  • V0.1 Tensor core
  • V0.2 Automatic differentiation
  • V0.3 Neural network modules
  • V0.4 Optimizers
  • V0.5 Hardware profiler
  • V0.6 Vulkan compute backend
  • V0.7 GPU watchdog and adaptive scheduler
  • V0.8 Transformer
  • V0.9 Tokenizer and TinyLLM
  • V1.0 MiniTorch training engine

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.6.0)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for dika03 from gravatar.com dika03

License expression

MIT
View SPDX License List

Requires

Python >=3.9

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0.6.0

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