pytorch

4b77cae3 - Add qconv_test to benchmarking tests (#24913)

Add qconv_test to benchmarking tests (#24913) Summary: Adds the tests defined in `qconv_tests.py` to `benchmark_all_tests.py` so that they are ran by `benchmark_all_tests`. The next diff will create another `ai_benchmark_test` specifying the qconv operations similar to D16768680. Since AI-PEP integrates with benchmark_all_tests, this should add these qconv benchmarks to AI-PEP. Pull Request resolved: https://github.com/pytorch/pytorch/pull/24913 Test Plan: `buck run mode/opt caffe2/benchmarks/operator_benchmark:benchmark_all_test` (runs only test who's `tag` is `short`) `buck run mode/opt caffe2/benchmarks/operator_benchmark:benchmark_all_test -- --tag_filter resnext101_32x4d` (runs test who's `tag` is `resxnet101_32x4d`). This runs the tests for all the imported modules in `benchmark_all_test.py` (i.e. add_test, batchnorm_test, qconv_test, etc) ``` buck run mode/opt caffe2/benchmarks/operator_benchmark:benchmark_all_test -- --operators QConv2d,QLinear ``` tests the QConv and QLinear operators Relevant output for `qconv_test.py` (for short tag): ``` # 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) : 957.848 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC256_OC256_H56_W56_G32_kernel3_stride1_pad1 # Input: N: 1, IC: 256, OC: 256, H: 56, W: 56, G: 32, kernel: 3, stride: 1, pad: 1 Forward Execution Time (us) : 3638.806 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC256_OC256_H56_W56_G1_kernel1_stride1_pad0 # Input: N: 1, IC: 256, OC: 256, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0 Forward Execution Time (us) : 3870.311 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC512_H56_W56_G32_kernel3_stride2_pad1 # Input: N: 1, IC: 512, OC: 512, H: 56, W: 56, G: 32, kernel: 3, stride: 2, pad: 1 Forward Execution Time (us) : 10052.192 ``` For resnext tag: ``` # ---------------------------------------- # PyTorch/Caffe2 Operator Micro-benchmarks # ---------------------------------------- # Tag : resnext101_32x4d # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC512_H14_W14_G32_kernel3_stride1_pad1 # Input: N: 1, IC: 512, OC: 512, H: 14, W: 14, G: 32, kernel: 3, stride: 1, pad: 1 Forward Execution Time (us) : 543.171 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC1024_H28_W28_G1_kernel1_stride2_pad0 # Input: N: 1, IC: 512, OC: 1024, H: 28, W: 28, G: 1, kernel: 1, stride: 2, pad: 0 Forward Execution Time (us) : 1914.301 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC256_H28_W28_G1_kernel1_stride1_pad0 # Input: N: 1, IC: 512, OC: 256, H: 28, W: 28, G: 1, kernel: 1, stride: 1, pad: 0 Forward Execution Time (us) : 1809.069 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC512_H28_W28_G1_kernel1_stride1_pad0 # Input: N: 1, IC: 512, OC: 512, H: 28, W: 28, G: 1, kernel: 1, stride: 1, pad: 0 Forward Execution Time (us) : 3100.579 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC512_OC512_H28_W28_G32_kernel3_stride2_pad1 # Input: N: 1, IC: 512, OC: 512, H: 28, W: 28, G: 32, kernel: 3, stride: 2, pad: 1 Forward Execution Time (us) : 2247.540 # 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) : 1001.731 # Benchmarking PyTorch: QConv2d # Mode: Eager # Name: QConv2d_N1_IC64_OC256_H56_W56_G1_kernel1_stride1_pad0 # Input: N: 1, IC: 64, OC: 256, H: 56, W: 56, G: 1, kernel: 1, stride: 1, pad: 0 Forward Execution Time (us) : 1571.620 ``` Differential Revision: D16908445 Pulled By: rohan-varma fbshipit-source-id: b711bc3591ce5dcd3ab2521134cff2b12188e3ac