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 as a source distribution, requires cmake and optionally nvcc if available:
pip install cudagrad
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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