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Mikhail Zolotukhin d0421ff1cc Benchmarks: add scripts for FastRNNs results comparison. (#44134) 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/44134

Test Plan: Imported from OSS

Reviewed By: bertmaher

Differential Revision: D23505810

Pulled By: ZolotukhinM

fbshipit-source-id: d0b3d70d4c2a44a8c3773631d09a25a98ec59370
2020-09-03 13:44:42 -07:00
..
distributed/ddp
Add distributed data parallel benchmark tool (#35198)
2020-04-08 15:07:03 -07:00
fastrnns
[TensorExpr] Benchmarks: set number of profiling runs to 2 for PE. (#44112)
2020-09-03 11:29:35 -07:00
framework_overhead_benchmark
Fix spelling errors
2020-01-28 04:46:15 -08:00
functional_autograd_benchmark
Reland of benchmark code (#43428)
2020-08-24 13:27:26 -07:00
operator_benchmark
Add benchmark for channel_shuffle operator (#43509)
2020-09-02 08:15:19 -07:00
overrides_benchmark
Add __torch_function__ for methods (#37091)
2020-08-05 20:44:13 -07:00
profiler_benchmark
Destroy CUDA events after profiling (#39962)
2020-06-23 10:44:39 -07:00
record_function_benchmark
move benchmark utils into torch namespace (#41506)
2020-07-23 09:48:39 -07:00
serialization
[JIT] Make new zip serialization for torch save/load significantly (~70%) faster (#38379)
2020-05-29 01:56:18 -07:00
static_runtime
[Static Runtime] Add OSS build for static runtime benchmarks (#43881)
2020-09-02 08:00:18 -07:00
tensorexpr
Respect canFuseOn{CPU,GPU} in TE fuser (#43967)
2020-09-02 18:00:25 -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
Fix spelling errors
2020-01-28 04:46:15 -08:00
upload_scribe.py
Add executor and fuser options to the fastrnn test fixture (#42946)
2020-08-13 12:45:37 -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 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