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Aaron Gokaslan 6d725e7d66 [BE]: enable ruff rules PLR1722 and PLW3301 (#109461) 
Enables two ruff rules derived from pylint:
* PLR1722 replaces any exit() calls with sys.exit(). exit() is only designed to be used in repl contexts as may not always be imported by default. This always use the version in the sys module which is better
* PLW3301 replaces nested min / max calls with simplified versions (ie. `min(a, min(b, c))` => `min(a, b. c)`). The new version is more idiomatic and more efficient.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/109461
Approved by: https://github.com/ezyang
2023-09-18 02:07:21 +00:00
..
cpp Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
distributed Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
dynamo [BE]: enable ruff rules PLR1722 and PLW3301 (#109461) 2023-09-18 02:07:21 +00:00
fastrnns Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
framework_overhead_benchmark Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
functional_autograd_benchmark [BE]: Update ruff to 0.285 (#107519) 2023-08-22 23:16:38 +00:00
fuser Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
instruction_counts Fix some typos, mostly "that that" (#106901) 2023-08-10 19:46:53 +00:00
nested Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
operator_benchmark [BE]: Update ruff to 0.285 (#107519) 2023-08-22 23:16:38 +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 Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
static_runtime fix some typos (#106018) 2023-07-26 18:14:44 +00:00
tensorexpr Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
transformer Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +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
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: