mirror of
https://github.com/zebrajr/pytorch.git
synced 2025-12-07 12:21:27 +01:00
873ced7cd0
Summary: Things changed in this PR that requires review: test/forward_backward_compatibility/check_forward_backward_compatibility.py Our previous function overload extension names were wrong and has been updated in this PR, hence the compatibility list updated. nvfuser code updates with bug fixes towards failures we encountered in OpInfoTests as well as failures reported by AOTAutograd team. Pull Request resolved: https://github.com/pytorch/pytorch/pull/73627 Reviewed By: Chillee Differential Revision: D34765458 Pulled By: davidberard98 fbshipit-source-id: c81f3d6a1b723fb3a8ba419b7f82227f70440ca7 (cherry picked from commit b6a2c362c37051e44fac31687b2fe272f776551e) |
||
|---|---|---|
| .. | ||
| cpp | ||
| distributed | ||
| fastrnns | ||
| framework_overhead_benchmark | ||
| functional_autograd_benchmark | ||
| fuser | ||
| instruction_counts | ||
| operator_benchmark | ||
| overrides_benchmark | ||
| profiler_benchmark | ||
| record_function_benchmark | ||
| serialization | ||
| sparse | ||
| static_runtime | ||
| tensorexpr | ||
| compare-fastrnn-results.py | ||
| compare.sh | ||
| README.md | ||
| upload_scribe.py | ||
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