| Name | Date | Size | #Lines | LOC | ||
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| distributed/ | H | 25-Apr-2025 | - | 3,111 | 2,600 | |
| dynamo/ | H | 25-Apr-2025 | - | 54,054 | 41,042 | |
| fastrnns/ | H | 25-Apr-2025 | - | 2,249 | 1,727 | |
| framework_overhead_benchmark/ | H | 25-Apr-2025 | - | 216 | 173 | |
| functional_autograd_benchmark/ | H | 25-Apr-2025 | - | 2,666 | 2,085 | |
| fuser/ | H | 25-Apr-2025 | - | 361 | 246 | |
| gpt_fast/ | H | 25-Apr-2025 | - | 1,611 | 1,269 | |
| inference/ | H | 25-Apr-2025 | - | 689 | 553 | |
| instruction_counts/ | H | 25-Apr-2025 | - | 2,238 | 1,720 | |
| nested/ | H | 25-Apr-2025 | - | 67 | 55 | |
| operator_benchmark/ | H | 25-Apr-2025 | - | 7,479 | 5,657 | |
| overrides_benchmark/ | H | 25-Apr-2025 | - | 176 | 123 | |
| profiler_benchmark/ | H | 25-Apr-2025 | - | 143 | 112 | |
| record_function_benchmark/ | H | 25-Apr-2025 | - | 119 | 95 | |
| serialization/ | H | 25-Apr-2025 | - | 72 | 51 | |
| sparse/ | H | 25-Apr-2025 | - | 1,524 | 1,228 | |
| static_runtime/ | H | 25-Apr-2025 | - | 14,614 | 12,610 | |
| tensorexpr/ | H | 25-Apr-2025 | - | 2,786 | 2,202 | |
| transformer/ | H | 25-Apr-2025 | - | 1,722 | 1,395 | |
| README.md | H A D | 25-Apr-2025 | 1.1 KiB | 34 | 25 | |
| compare-fastrnn-results.py | H A D | 25-Apr-2025 | 2.1 KiB | 73 | 60 | |
| compare.sh | H A D | 25-Apr-2025 | 230 | 5 | 3 | |
| upload_scribe.py | H A D | 25-Apr-2025 | 5.7 KiB | 164 | 149 |
README.md
1# PyTorch Benchmarks 2 3This folder contains scripts that produce reproducible timings of various PyTorch features. 4 5It also provides mechanisms to compare PyTorch with other frameworks. 6 7## Setup environment 8Make sure you're on a machine with CUDA, torchvision, and pytorch installed. Install in the following order: 9``` 10# Install torchvision. It comes with the pytorch stable release binary 11conda install pytorch torchvision -c pytorch 12 13# Install the latest pytorch master from source. 14# It should supersede the installation from the release binary. 15cd $PYTORCH_HOME 16python setup.py build develop 17 18# Check the pytorch installation version 19python -c "import torch; print(torch.__version__)" 20``` 21 22## Benchmark List 23 24Please refer to each subfolder to discover each benchmark suite. Links are provided where descriptions exist: 25 26* [Fast RNNs](fastrnns/README.md) 27* [Dynamo](dynamo/README.md) 28* [Functional autograd](functional_autograd_benchmark/README.md) 29* [Instruction counts](instruction_counts/README.md) 30* [Operator](operator_benchmark/README.md) 31* [Overrides](overrides_benchmark/README.md) 32* [Sparse](sparse/README.md) 33* [Tensor expression](tensorexpr/HowToRun.md) 34