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Update PyTorch to the latest Triton release candidate branch (release/3.5.x in triton-lang/triton) Notably: * this does *not* include the version number bump from 3.4 -> 3.5 (we'll do that in a follow-up PR) * sam_fast is still failing, so we've disabled it temporarily https://github.com/pytorch/pytorch/issues/162282 and we are committed to fixing it, ideally before the branch cut but possibly as a cherry-pick into the release branch. Pull Request resolved: https://github.com/pytorch/pytorch/pull/162278 Approved by: https://github.com/atalman ghstack dependencies: #162244, #162309
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
python -m pip install torch torchvision
# Install the latest pytorch master from source.
# It should supersede the installation from the release binary.
cd $PYTORCH_HOME
python -m pip install --no-build-isolation -v -e .
# 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: