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Raghavan Raman 80f60f2cc0 [Static Runtime] Handle fallback graphs that are generated as part of the TE Fuser (#72945) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/72945

ghstack-source-id: 149429754

Test Plan:
```
buck run mode/opt //caffe2/benchmarks/static_runtime:static_runtime_cpptest — --gtest_filter=CpuFusion.FallbackGraph
```

Reviewed By: mikeiovine

Differential Revision: D34283840

fbshipit-source-id: 868bd340a50fe691797164524f2400d07998d304
2022-02-18 10:33:08 -08:00
..
cpp Nvfuser code bump 2_1_2022 (#72127) 2022-02-14 16:40:18 -08:00
distributed Remove .data from benchmarks and tensorboard (#65389) 2021-09-22 11:16:59 -07:00
fastrnns Remove .data from benchmarks and tensorboard (#65389) 2021-09-22 11:16:59 -07:00
framework_overhead_benchmark Remove py2 compatible future imports (#44735) 2020-09-16 12:55:57 -07:00
functional_autograd_benchmark Extend autograd functional benchmarking to run vectorized tasks (#67045) 2021-12-21 17:20:29 -08:00
fuser Benchmarks for various fusers (#67622) 2021-11-04 18:57:17 -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 Fix command example (#72847) 2022-02-16 13:40:40 -08:00
overrides_benchmark Use classmethods for overrides (#64841) 2021-09-17 08:32:49 -07:00
profiler_benchmark Use libkineto in profiler (#46470) 2020-11-25 04:32:16 -08:00
record_function_benchmark Fix D23995953 import. 2020-09-29 19:30:23 -07:00
serialization [JIT] Make new zip serialization for torch save/load significantly (~70%) faster (#38379) 2020-05-29 01:56:18 -07:00
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime [Static Runtime] Handle fallback graphs that are generated as part of the TE Fuser (#72945) 2022-02-18 10:33:08 -08:00
tensorexpr [nnc] Added micro-benchmark to show perf improvement with cat subgraph optimization (#59581) 2021-06-18 14:32:09 -07:00
compare-fastrnn-results.py Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
compare.sh Benchmarks: add scripts for FastRNNs results comparison. (#44134) 2020-09-03 13:44:42 -07:00
README.md Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
upload_scribe.py Fix benchmark's import module and remove its usage of tools.stats.scribe (#61808) 2021-07-19 09:45:05 -07:00

README.md

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