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chilli 52b1d2a73d Increase timm batch sizes to make less overhead-bound and less noisy (#122581) 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/122581
Approved by: https://github.com/ezyang
ghstack dependencies: #122686, #122688, #121692, #122841
2024-03-28 02:34:32 +00:00
..
distributed [BE]: Apply FURB118 (prev): replaces unnecessary lambdas with operator. (#116027) 2023-12-20 19:35:08 +00:00
dynamo Increase timm batch sizes to make less overhead-bound and less noisy (#122581) 2024-03-28 02:34:32 +00:00
fastrnns Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
framework_overhead_benchmark [BE]: Enable F821 and fix bugs (#116579) 2024-01-01 08:40:46 +00:00
functional_autograd_benchmark [BE]: Enable F821 and fix bugs (#116579) 2024-01-01 08:40:46 +00:00
fuser Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
gpt_fast Add gpt-fast as a static benchmark (#121886) 2024-03-14 21:46:59 +00:00
inference Allow more backend worker threads with each using a separate cuda stream (#116190) 2023-12-20 22:08:29 +00:00
instruction_counts Use strict to toggle strict options in MYPYSTRICT (#118479) 2024-01-28 19:22:22 +00:00
nested Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
operator_benchmark highlight readme code block (#120228) 2024-02-22 21:23:08 +00:00
overrides_benchmark [BE]: Update ruff to 0.285 (#107519) 2023-08-22 23:16:38 +00:00
profiler_benchmark Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
record_function_benchmark Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
serialization Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
sparse [BE]: Enable F821 and fix bugs (#116579) 2024-01-01 08:40:46 +00:00
static_runtime [PyTorch] fix mixed int32/int64 indices/offsets for embedding_bag_out (#120752) 2024-02-28 20:13:30 +00:00
tensorexpr [BE]: Enable F821 and fix bugs (#116579) 2024-01-01 08:40:46 +00:00
transformer Add an option to sdpa benchmark to specify backend (#122368) 2024-03-21 07:00:40 +00:00
compare-fastrnn-results.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
compare.sh
README.md Add more child links to benchmark readme (#104627) 2023-07-06 12:11:00 +00:00
upload_scribe.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00

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. Links are provided where descriptions exist: