Set number of threads for operator_benchmarks (#27010)
Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/27010
Setting OMP_NUM_THREADS programmatically doesn't do the right thing because initialization is already done. Fixing this by calling torch.set_num_threads explicitly.
Passing --omp_num_threads works as expected now.
In dir benchmarks/operator_benchmark/
python -m pt.qconv_test --tag_filter resnext101_32x4 --wipe_cache --test_name QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0 --omp_num_threads 1
```
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : None
# Benchmarking PyTorch: QConv2d
# Mode: Eager
# Name: QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0
# Input: N: 1, IC: 64, OC: 128, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0
Forward Execution Time (us) : 509.965
# Benchmarking PyTorch: QConv2d
# Mode: Eager
# Name: QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0
# Input: N: 1, IC: 64, OC: 128, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0
Forward Execution Time (us) : 576.007
```
python -m pt.qconv_test --tag_filter resnext101_32x4 --wipe_cache --test_name QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0 --omp_num_threads 4
```
# ----------------------------------------
# PyTorch/Caffe2 Operator Micro-benchmarks
# ----------------------------------------
# Tag : None
# Benchmarking PyTorch: QConv2d
# Mode: Eager
# Name: QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0
# Input: N: 1, IC: 64, OC: 128, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0
Forward Execution Time (us) : 195.002
# Benchmarking PyTorch: QConv2d
# Mode: Eager
# Name: QConv2d_N1_IC64_OC128_H56_W56_G1_kernel1_stride1_pad0
# Input: N: 1, IC: 64, OC: 128, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0
Forward Execution Time (us) : 189.788
```
ghstack-source-id: 91050434
Test Plan: See summary
Differential Revision: D17647391
fbshipit-source-id: e00de1151902291ed94fd34446995ea1f0199d14
