A tensor-valued autograd engine for Python
Project description
cudagrad
CUDA C++ strided float tensor automatic differentiation engine with Python bindings
Install
Available on PyPI:
pip install cudagrad
Distributed as:
- A source distribution, requiring the
cmakecommand, and optionally thenvcccommand, to be available at installation time. - A binary distribution, targeting the Kaggle Python docker images:
- CPU-only binary: Kaggle notebook example
- GPU accelerator binary: Work in Progress
Examples
The following examples were written purely in Python using only cudagrad.Tensor for learning:
OR
0.52 seconds (59.5% faster than torch)
XOR
4.5 seconds (39.2% faster than torch)
MOONS
14.25 seconds (5.8% slower than torch)
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