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Mingzhe Li f63cbf3ae2 change op benchmark forward_only flag (#28967) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/28967

Change forward_only flag to take True or False so it should be integrated with PEP.

Test Plan:
```
[mingzhe0908@devgpu203.prn2 ~/fbsource/fbcode] ~/fbsource/fbcode/buck-out/opt/gen/caffe2/benchmarks/operator_benchmark/pt/add_test.par --forward_only True  --iterations 1
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : short

# Benchmarking PyTorch: add
# Mode: Eager
# Name: add_M64_N64_K64_cpu
# Input: M: 64, N: 64, K: 64, device: cpu
Forward Execution Time (us) : 152.489

# Benchmarking PyTorch: add
# Mode: Eager
# Name: add_M64_N64_K128_cpu
# Input: M: 64, N: 64, K: 128, device: cpu
Forward Execution Time (us) : 236.608

[mingzhe0908@devgpu203.prn2 ~/fbsource/fbcode] ~/fbsource/fbcode/buck-out/opt/gen/caffe2/benchmarks/operator_benchmark/pt/add_test.par --forward_only False   --iterations 1
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : short

# Benchmarking PyTorch: add
# Mode: Eager
# Name: add_M64_N64_K64_cpu
# Input: M: 64, N: 64, K: 64, device: cpu
Forward Execution Time (us) : 147.174

# Benchmarking PyTorch: add
# Mode: Eager
# Name: add_M64_N64_K128_cpu
# Input: M: 64, N: 64, K: 128, device: cpu
Forward Execution Time (us) : 253.437

# Benchmarking PyTorch: add
# Mode: Eager
# Name: add_M64_N64_K64_cpu_bwdall
# Input: M: 64, N: 64, K: 64, device: cpu
Backward Execution Time (us) : 1044.082

Reviewed By: hl475

Differential Revision: D18247416

fbshipit-source-id: 1c6cff1ac98233d4f0ca298e0cb4a0d3466e5834
2019-10-31 13:28:58 -07:00
..
fastrnns Ignore F401 in all __init__.py without putting noqa (#25823) 2019-10-23 15:28:13 -07:00
framework_overhead_benchmark Added running via throughput benchmark options. (#23077) 2019-07-22 11:27:55 -07:00
operator_benchmark change op benchmark forward_only flag (#28967) 2019-10-31 13:28:58 -07:00
README.md

README.md

PyTorch Benchmarks

NOTE: This folder is currently work in progress.

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 supercede 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