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Scott Wolchok 66406ee0f7 [PyTorch][Static Runtime] Fix to() w/dtype bool (#69935) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/69935

Didn't realize that `AT_DISPATCH_ALL_TYPES` should really be called `AT_DISPATCH_MOST_TYPES`.
ghstack-source-id: 145661358

Test Plan:
Added test for dtype bool.

Ran CMF local_ro net:

before:

```
I1215 12:33:49.300174 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.966491. Iters per second: 1034.67
I1215 12:33:49.825570 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.94867. Iters per second: 1054.11
I1215 12:33:50.349246 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.947926. Iters per second: 1054.93
I1215 12:33:50.870433 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.943779. Iters per second: 1059.57
I1215 12:33:51.393702 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.947185. Iters per second: 1055.76
I1215 12:33:51.915666 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.945672. Iters per second: 1057.45
I1215 12:33:52.438475 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.948407. Iters per second: 1054.4
I1215 12:33:52.965337 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.95472. Iters per second: 1047.43
I1215 12:33:53.494563 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.967083. Iters per second: 1034.04
I1215 12:33:54.017879 1606538 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.948945. Iters per second: 1053.8
I1215 12:33:54.017930 1606538 PyTorchPredictorBenchLib.cpp:290] Mean milliseconds per iter: 0.951888, standard deviation: 0.0083367
```

after:
```
I1215 12:32:35.820874 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.999845. Iters per second: 1000.15
I1215 12:32:36.343147 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.944363. Iters per second: 1058.91
I1215 12:32:36.863806 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.942542. Iters per second: 1060.96
I1215 12:32:37.385459 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.944677. Iters per second: 1058.56
I1215 12:32:37.905436 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.941135. Iters per second: 1062.55
I1215 12:32:38.424907 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.939748. Iters per second: 1064.11
I1215 12:32:38.944643 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.941764. Iters per second: 1061.84
I1215 12:32:39.463791 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.938946. Iters per second: 1065.02
I1215 12:32:39.987567 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.95437. Iters per second: 1047.81
I1215 12:32:40.511204 1594955 PyTorchPredictorBenchLib.cpp:279] PyTorch run finished. Milliseconds per iter: 0.959139. Iters per second: 1042.6
I1215 12:32:40.511242 1594955 PyTorchPredictorBenchLib.cpp:290] Mean milliseconds per iter: 0.950653, standard deviation: 0.0184761
```

Reviewed By: hlu1

Differential Revision: D33106675

fbshipit-source-id: 5bb581f8d0ed22ef08df1936dc8d67045e44e862
2021-12-15 15:26:56 -08:00
..
cpp use irange for loops 2 (#66746) 2021-12-10 04:26:23 -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 Prefer mT and mH over transpose(-2, -1) and transpose(-2, -1).conj() (#64181) 2021-10-18 13:02:25 -07:00
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 [quant][embedding qat] Add benchmarks for QAT Embedding+EmbeddingBag (#66560) 2021-11-19 06:29:19 -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
sparse Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
static_runtime [PyTorch][Static Runtime] Fix to() w/dtype bool (#69935) 2021-12-15 15:26:56 -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