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7d11c61c26
Summary: This backs out D60320595 which itself turned off FakeTensor caching when a SymInt was present. There has been a lot of dynamic shape fixes done this year and tests pass so I'm assuming some of that work fixed what was breaking previously. Test Plan: Reran the tests listed in T196779132 and they pass. ## Perf ### Instruction Counter Benchmark: - 26% win on add_loop_eager_dynamic - 13% win on add_loop_inductor_dynamic_gpu ### Perf Dashboard Compilation Latency wins across the board but especially strong on the dynamic tests (like cudagraphs_dynamic) - for example MobileBertForMaskedLM went from 66s -> 50s. Pull Request resolved: https://github.com/pytorch/pytorch/pull/152662 Approved by: https://github.com/anijain2305
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
pip3 install torch torchvision
# 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: