pytorch/benchmarks
Horace He 79a258f448 s/foward/forward/g (#58497)
Summary:
Annoying typo.

Prompted by these profiling results: https://github.com/pytorch/pytorch/issues/56419#issuecomment-825787828

Pull Request resolved: https://github.com/pytorch/pytorch/pull/58497

Reviewed By: malfet

Differential Revision: D28521081

Pulled By: Chillee

fbshipit-source-id: ab91a2e167dd7d3387fd56106a6cff81f7a32f10
2021-05-19 11:42:42 -07:00
..
cpp [clang-tidy] Exclude cppcoreguidelines-avoid-magic-numbers (#57841) 2021-05-07 20:02:33 -07:00
distributed s/foward/forward/g (#58497) 2021-05-19 11:42:42 -07:00
fastrnns Add lint for unqualified noqa (#56272) 2021-04-19 13:16:18 -07:00
framework_overhead_benchmark
functional_autograd_benchmark Add lint for unqualified type: ignore (#56290) 2021-04-21 08:07:23 -07:00
instruction_counts Allow instruction counting to use shared memory as a staging ground. (And a couple other tweaks.) (#56711) 2021-05-12 20:37:41 -07:00
operator_benchmark Improve BatchNorm1d performance (CUDA) (#57786) 2021-05-08 19:09:29 -07:00
overrides_benchmark Remove legacy constructor calls from pytorch codebase. (#54142) 2021-04-11 15:45:17 -07:00
profiler_benchmark Use libkineto in profiler (#46470) 2020-11-25 04:32:16 -08:00
record_function_benchmark
serialization
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime [Static Runtime] Support clamp.Tensor (#58191) 2021-05-13 17:46:59 -07:00
tensorexpr s/foward/forward/g (#58497) 2021-05-19 11:42:42 -07:00
compare-fastrnn-results.py
compare.sh
README.md Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
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