pytorch/benchmarks
2022-06-10 20:55:10 +00:00
..
cpp Revert "[nvfuser_upstream_push] nvfuser code base bump 060822 (#79147)" 2022-06-10 20:55:10 +00:00
distributed Fix some typos. 2022-04-11 21:55:59 +00:00
fastrnns [libkineto] Re-enable user-annotations in PyTorch (#75601) 2022-04-26 23:54:22 +00:00
framework_overhead_benchmark Remove py2 compatible future imports (#44735) 2020-09-16 12:55:57 -07:00
functional_autograd_benchmark Added functorch to functional_autograd_benchmark 2022-04-22 14:04:26 +00:00
fuser Benchmarks for various fusers (#67622) 2021-11-04 18:57:17 -07:00
instruction_counts [lint] upgrade mypy to latest version 2022-05-03 20:51:34 +00:00
operator_benchmark [TorchArrow][AIBench] Add AIBench Metrics for TorchArrow Inference Benchmark Test (#75035) 2022-04-01 00:35:42 +00:00
overrides_benchmark Use classmethods for overrides (#64841) 2021-09-17 08:32:49 -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 [JIT] Make new zip serialization for torch save/load significantly (~70%) faster (#38379) 2020-05-29 01:56:18 -07:00
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime [Static Runtime] Fix aten::clone out variant (#78297) (#78322) 2022-06-02 21:06:59 +00:00
tensorexpr Fix some typos. 2022-04-11 21:55:59 +00:00
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 Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
upload_scribe.py Fix benchmark's import module and remove its usage of tools.stats.scribe (#61808) 2021-07-19 09:45:05 -07:00

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