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Sergii Dymchenko d341b66e96 Revert [dynamo] support group=None when rewriting collectives (#12018) (#120677) 
This reverts commit 298c686d3f7bc26399481b8830e71c4f02ce629c.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/120677
Approved by: https://github.com/yifuwang, https://github.com/huydhn
2024-02-27 00:33:35 +00:00
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distributed
[BE]: Apply FURB118 (prev): replaces unnecessary lambdas with operator. (#116027)
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dynamo
Revert [dynamo] support group=None when rewriting collectives (#12018) (#120677)
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fastrnns
Apply UFMT to all files in benchmarks/ (#105928)
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framework_overhead_benchmark
[BE]: Enable F821 and fix bugs (#116579)
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functional_autograd_benchmark
[BE]: Enable F821 and fix bugs (#116579)
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fuser
Apply UFMT to all files in benchmarks/ (#105928)
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inference
Allow more backend worker threads with each using a separate cuda stream (#116190)
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instruction_counts
Use strict to toggle strict options in MYPYSTRICT (#118479)
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nested
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operator_benchmark
highlight readme code block (#120228)
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overrides_benchmark
[BE]: Update ruff to 0.285 (#107519)
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profiler_benchmark
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record_function_benchmark
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serialization
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sparse
[BE]: Enable F821 and fix bugs (#116579)
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static_runtime
fix some typos (#106018)
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tensorexpr
[BE]: Enable F821 and fix bugs (#116579)
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transformer
[CUDNN][SDPA] Experimental cuDNN Flash Attention v2 Inference (#115663)
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compare-fastrnn-results.py
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compare.sh
Benchmarks: add scripts for FastRNNs results comparison. (#44134)
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README.md
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upload_scribe.py
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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: