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Raghavan Raman 38f696c0cd [nnc] Add a API to unroll loops by a given factor (#72071) 
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/72071

Reviewed By: ngimel

Differential Revision: D33946250

Pulled By: navahgar

fbshipit-source-id: 3f3f92054174620025a9d71154d006f1738953e2
(cherry picked from commit d8b53598e92e8d2e050bc1d0cd070fbe8e2d77dd)
2022-02-03 18:41:21 +00:00
..
cpp
[nnc] Add a API to unroll loops by a given factor (#72071)
2022-02-03 18:41:21 +00:00
distributed
Remove .data from benchmarks and tensorboard (#65389)
2021-09-22 11:16:59 -07:00
fastrnns
Remove .data from benchmarks and tensorboard (#65389)
2021-09-22 11:16:59 -07:00
framework_overhead_benchmark
Remove py2 compatible future imports (#44735)
2020-09-16 12:55:57 -07:00
functional_autograd_benchmark
Extend autograd functional benchmarking to run vectorized tasks (#67045)
2021-12-21 17:20:29 -08:00
fuser
Benchmarks for various fusers (#67622)
2021-11-04 18:57:17 -07:00
instruction_counts
Allow instruction counting to use shared memory as a staging ground. (And a couple other tweaks.) (#56711)
2021-05-12 20:37:41 -07:00
operator_benchmark
[quant][embedding qat] Add benchmarks for QAT Embedding+EmbeddingBag (#66560)
2021-11-19 06:29:19 -08:00
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
[SR] Relax aten::__is__ constraint for SR enablement (#71807)
2022-02-03 12:18:46 +00:00
tensorexpr
[nnc] Added micro-benchmark to show perf improvement with cat subgraph optimization (#59581)
2021-06-18 14:32:09 -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
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

README.md

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