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mikeiovine 98b4a4100d [SR] Add a copy variant for fused_split_and_squeeze 
Pull Request resolved: https://github.com/pytorch/pytorch/pull/75660

The outputs of `split_and_squeeze` are passed to `VarStack` in models we care about. `VarStack` has a [fast path](https://www.internalfb.com/code/fbsource/[893193f5277184fd17f4ea3f28fe415a4df37707]/fbcode/caffe2/aten/src/ATen/native/TensorShape.cpp?lines=296-298) for when all of its inputs have the same strides.

Hitting the slow path adds a ton of extra overhead - so much that it's worth it to copy in `split_and_squeeze` and force all of `VarStack`'s inputs to be contiguous so we can take advantage of the fast path.

Differential Revision: [D35513777](https://our.internmc.facebook.com/intern/diff/D35513777/)

**NOTE FOR REVIEWERS**: This PR has internal Facebook specific changes or comments, please review them on [Phabricator](https://our.internmc.facebook.com/intern/diff/D35513777/)!

Approved by: https://github.com/hlu1
2022-04-13 20:02:01 +00:00
..
cpp
Add cuda-11.3+clang9 build workflow (take 2)
2022-04-11 17:13:01 +00:00
distributed
Fix some typos.
2022-04-11 21:55:59 +00:00
fastrnns
Clean up profiling mode and profiling executor strategy (#73875)
2022-03-29 18:38:51 +00:00
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
[TorchArrow][AIBench] Add AIBench Metrics for TorchArrow Inference Benchmark Test (#75035)
2022-04-01 00:35:42 +00:00
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
[SR] Add a copy variant for fused_split_and_squeeze
2022-04-13 20:02:01 +00:00
tensorexpr
Fix some typos.
2022-04-11 21:55:59 +00:00
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