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pytorch/benchmarks
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Zafar Takhirov d545e4f155 qrelu benchmarking 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/29174

Test Plan: Imported from OSS

Differential Revision: D18319345

Pulled By: z-a-f

fbshipit-source-id: b64f0131296771ed201d85664930cceb7be185bd
2019-11-05 17:20:40 -08:00
..
fastrnns Ignore F401 in all __init__.py without putting noqa (#25823) 2019-10-23 15:28:13 -07:00
framework_overhead_benchmark Added running via throughput benchmark options. (#23077) 2019-07-22 11:27:55 -07:00
operator_benchmark qrelu benchmarking 2019-11-05 17:20:40 -08:00
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