pytorch/benchmarks
elfringham db1b0b06c4 Flake8 fixes (#48453)
Summary:
Quiet errors from flake8. Only a couple of code changes for deprecated Python syntax from before 2.4. The rest is just adding noqa markers.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/48453

Reviewed By: mruberry

Differential Revision: D25181871

Pulled By: ngimel

fbshipit-source-id: f8d7298aae783b1bce2a46827b088fc390970641
2020-11-25 19:09:50 -08:00
..
cpp/tensorexpr [te][benchmark] Add more optimized versions of gemm (#48159) 2020-11-18 12:21:08 -08:00
distributed/ddp Flake8 fixes (#48453) 2020-11-25 19:09:50 -08:00
fastrnns Benchmarks: tweak PE config settings. (#45349) 2020-09-26 23:13:29 -07:00
framework_overhead_benchmark Remove py2 compatible future imports (#44735) 2020-09-16 12:55:57 -07:00
functional_autograd_benchmark Reland of benchmark code (#43428) 2020-08-24 13:27:26 -07:00
operator_benchmark [OpBench] change relu entry point after D24747035 2020-11-13 15:38:27 -08:00
overrides_benchmark Add __torch_function__ for methods (#37091) 2020-08-05 20:44:13 -07:00
profiler_benchmark Use libkineto in profiler (#46470) 2020-11-25 04:32:16 -08:00
record_function_benchmark Fix D23995953 import. 2020-09-29 19:30:23 -07:00
serialization
static_runtime [PT][StaticRuntime] Move prim op impl to ops.cpp (#48210) 2020-11-18 23:07:39 -08:00
tensorexpr [NVFuser]Benchmark minor update (#46778) 2020-10-26 12:22:36 -07:00
compare-fastrnn-results.py Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
compare.sh Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
README.md
upload_scribe.py Benchmarks: make fuser and executor configurable from command line. (#44291) 2020-09-09 11:59:35 -07:00

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 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