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android / platform / external / pytorch / b4a4a8434d / . / benchmarks
tree: 5e972d323d81384c87a403cd4daee72384931059 [path history] [tgz]
  1. cpp/
  2. distributed/
  3. fastrnns/
  4. framework_overhead_benchmark/
  5. functional_autograd_benchmark/
  6. instruction_counts/
  7. operator_benchmark/
  8. overrides_benchmark/
  9. profiler_benchmark/
  10. record_function_benchmark/
  11. serialization/
  12. sparse/
  13. static_runtime/
  14. tensorexpr/
  15. compare-fastrnn-results.py
  16. compare.sh
  17. README.md
  18. upload_scribe.py
benchmarks/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