NOTE: This folder is currently work in progress.
This folder contains scripts that produce reproducible timings of various PyTorch features.
It also provides mechanisms to compare PyTorch with other frameworks.
Make sure you're on a machine with CUDA, torchvision, and pytorch installed. Install in the following order:
# Install torchvision. It comes with the pytorch stable release binary conda install pytorch torchvision -c pytorch # Install the latest pytorch master from source. # It should supersede the installation from the release binary. cd $PYTORCH_HOME python setup.py build develop # Check the pytorch installation version python -c "import torch; print(torch.__version__)"
Please refer to each subfolder to discover each benchmark suite