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Mingzhe Li 1aa80471b8 minor fix to filter (#30200) 
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/30200

as title

Test Plan:
```
buck run mode/opt //caffe2/benchmarks/operator_benchmark:benchmark_all_other_test -- --tag_filter all --iterations 1 --ai_pep_format True --operators None --iterations -1 --warmup_iterations -1 --wipe_cache --forward_only False --device cpu --tag_filter all --use_jit False --operator_range b-z
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : all

# Benchmarking PyTorch: batchnorm
PyTorchObserver {"type": "PyTorch_batchnorm_M1_N256_K3136_cpu_Eager", "metric": "latency", "unit": "ms", "value": "0.29026457108557224"}
PyTorchObserver {"type": "PyTorch_batchnorm_M1_N256_K3136_cpu_Eager", "metric": "latency", "unit": "ms", "value": "0.2813781425356865"}
PyTorchObserver {"type": "PyTorch_batchnorm_M1_N256_K3136_cpu_Eager", "metric": "latency", "unit": "ms", "value": "0.28009670320898294"}
...

Reviewed By: hl475

Differential Revision: D18627512

fbshipit-source-id: 23f622b96168f90a8d8648bfd9ff9a5116baafdf
2019-11-20 16:36:04 -08:00
..
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 minor fix to filter (#30200) 2019-11-20 16:36:04 -08:00
README.md Move fast rnn benchmark to pytorch/pytorch 2019-03-27 14:46:09 -07:00

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