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Ansha Yu bf1c936e06 [static runtime] out variant for full_like (#58079) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/58079

Support full_like

Test Plan:
`buck test mode/dev caffe2/benchmarks/static_runtime:static_runtime_cpptest -- StaticRuntime.IndividualOps_FullLike`

Test on regenerated local inline_cvr model
```
MKL_NUM_THREADS=1 OMP_NUM_THREADS=1 numactl -m 0 -C 3 ./buck-out/opt/gen/caffe2/caffe2/fb/predictor/ptvsc2_predictor_bench --scripted_model=/data/users/ansha/tmp/adfinder/dec_6x/266377643_shrunk.predictor.disagg.local.regenerated.pt --pt_inputs=/data/users/ansha/tmp/adfinder/dec_6x/local_inputs --pt_enable_static_runtime=1 --pt_cleanup_activations=1 --pt_enable_out_variant=1 --compare_results=1 --iters=5000 --warmup_iters=5000 --num_threads=1 --do_profile=0 --do_benchmark=1 --adsfinder_compatibility=1 --v=1
```

`V0511 10:59:57.187054 1911683 impl.cpp:1229] Switch to out variant for node: %5571 : Tensor = aten::full_like(%blob_for_shape.1, %235, %654, %75, %75, %75, %75)`

Reviewed By: hlu1

Differential Revision: D28361997

fbshipit-source-id: 89c41e37ce23d6008cfe4d80536832ee76d3405e
2021-05-20 16:17:40 -07:00
..
cpp
[clang-tidy] Exclude cppcoreguidelines-avoid-magic-numbers (#57841)
2021-05-07 20:02:33 -07:00
distributed
s/foward/forward/g (#58497)
2021-05-19 11:42:42 -07:00
fastrnns
Add lint for unqualified noqa (#56272)
2021-04-19 13:16:18 -07:00
framework_overhead_benchmark
Remove py2 compatible future imports (#44735)
2020-09-16 12:55:57 -07:00
functional_autograd_benchmark
Add lint for unqualified type: ignore (#56290)
2021-04-21 08:07:23 -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
Improve BatchNorm1d performance (CUDA) (#57786)
2021-05-08 19:09:29 -07:00
overrides_benchmark
Remove legacy constructor calls from pytorch codebase. (#54142)
2021-04-11 15:45:17 -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] out variant for full_like (#58079)
2021-05-20 16:17:40 -07:00
tensorexpr
s/foward/forward/g (#58497)
2021-05-19 11:42:42 -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
Benchmarks: make fuser and executor configurable from command line. (#44291)
2020-09-09 11:59:35 -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