| # PyTorch Benchmarks | |
| This folder contains scripts that produce reproducible timings of various PyTorch features. | |
| It also provides mechanisms to compare PyTorch with other frameworks. | |
| ## Setup environment | |
| 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__)" | |
| ``` | |
| ## Benchmark List | |
| Please refer to each subfolder to discover each benchmark suite | |
| * [Fast RNNs benchmarks](fastrnns/README.md) |