mirror of
https://github.com/zebrajr/pytorch.git
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d8c384544e
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/39962 Adding a simple wrapper with ref count for cuda event and destroying cuda event after the last copy is destroyed Test Plan: CI cuda profiler tests Differential Revision: D22027092 Pulled By: ilia-cher fbshipit-source-id: e0810388aa60b2291eb010896e13af1fad92e472 |
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| distributed/ddp | ||
| fastrnns | ||
| framework_overhead_benchmark | ||
| operator_benchmark | ||
| overrides_benchmark | ||
| profiler_benchmark | ||
| serialization | ||
| tensorexpr | ||
| README.md | ||
PyTorch Benchmarks
NOTE: This folder is currently work in progress.
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