mirror of
https://github.com/zebrajr/pytorch.git
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ffdc0e23af
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/71113 This diff adds a variety of missing ~~out variants~~/native ops. Most of these are trivial, so I included them all in one diff. Native ops * `aten::mul` (list variant) * `aten::sub` (int variant) * `aten::add` (list variant) * `aten::Int` Out variants * ~~`aten::gt`~~ (codegen will handle) * ~~`aten::eq`~~ (codegen will handle) ghstack-source-id: 146927552 Test Plan: `buck test caffe2/benchmarks/static_runtime:static_runtime_cpptest` Reviewed By: hlu1 Differential Revision: D33510756 fbshipit-source-id: df385958b9561955b2e866dab2e4c050abd26766 |
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| .. | ||
| 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