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Huamin Li 1b38a6f602 add wipe cache 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/24390

Reviewed By: mingzhe09088

Differential Revision: D16808041

fbshipit-source-id: 1b19f47706e4e2f2e03356469315b55c6ff76d20
2019-08-14 23:48:52 -07:00
..
fastrnns Fix spelling errors (#21665) 2019-06-13 15:21:55 -07:00
framework_overhead_benchmark Added running via throughput benchmark options. (#23077) 2019-07-22 11:27:55 -07:00
operator_benchmark add wipe cache 2019-08-14 23:48:52 -07:00
README.md Move fast rnn benchmark to pytorch/pytorch 2019-03-27 14:46:09 -07:00

README.md

PyTorch Benchmarks

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.

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 supercede 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