[2/2] Added backward pass on CUDA for interpolation with anti-alias option #4211
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
fmassa
approved these changes
Aug 4, 2021
|
Hey @fmassa! You merged this PR, but no labels were added. |
facebook-github-bot
pushed a commit
that referenced
this pull request
Aug 19, 2021
…i-alias option (#4211) Summary: * WIP on backward op interpolation with AA * Removed cuda tests and reformat cpp code * Fixed clang wrong formatting * Added channels last test case * Added CUDA support for backward pass, interpolation with AA * Removed unused buffers Reviewed By: NicolasHug Differential Revision: D30417194 fbshipit-source-id: 4aab5bc21621859cfc4254da6a230e0c8a8cffc2 Co-authored-by: vfdev-5 <vfdev-5@gmail.com>
facebook-github-bot
pushed a commit
to pytorch/pytorch
that referenced
this pull request
Jan 27, 2022
) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, #65142 Previous PR for CPU bicubic, #68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: #70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69
pytorchmergebot
pushed a commit
to pytorch/pytorch
that referenced
this pull request
Jan 27, 2022
) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, #65142 Previous PR for CPU bicubic, #68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: #70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
alexhagiopol
pushed a commit
to pytorch/pytorch
that referenced
this pull request
Jan 28, 2022
) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, #65142 Previous PR for CPU bicubic, #68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: #70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 3, 2022
…930) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, pytorch/pytorch#65142 Previous PR for CPU bicubic, pytorch/pytorch#68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: pytorch/pytorch#70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 3, 2022
…930) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, pytorch/pytorch#65142 Previous PR for CPU bicubic, pytorch/pytorch#68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: pytorch/pytorch#70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 9, 2022
…930) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, pytorch/pytorch#65142 Previous PR for CPU bicubic, pytorch/pytorch#68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: pytorch/pytorch#70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
cyyever
pushed a commit
to cyyever/pytorch_private
that referenced
this pull request
Feb 9, 2022
…930) Summary: Description: - Added antialias flag to interpolate (CUDA) - forward and backward for bicubic mode - added tests Previous PR for CPU bilinear, pytorch/pytorch#65142 Previous PR for CPU bicubic, pytorch/pytorch#68819 ### Benchmarks <details> <summary> Bilinear forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2851.2 | 874.1 | 57.1 channels_last non-contiguous torch.float32 | 2856.1 | 1155.8 | 130.6 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3705.9 | 1005.8 | 66.3 channels_last non-contiguous torch.float32 | 3742.9 | 1332.8 | 143.5 Times are in microseconds (us). [------------------------------------ Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 1768.0 | 725.2 | 77.9 channels_last non-contiguous torch.float32 | 1753.7 | 942.5 | 144.0 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 9522.6 | 2593.8 | 157.8 channels_last non-contiguous torch.float32 | 9513.5 | 3622.7 | 241.5 Times are in microseconds (us). [----------------------------------- Downsampling (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2240.1 | 565.5 | 93.3 channels_last non-contiguous torch.float32 | 2244.2 | 972.7 | 170.8 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1441.3 | 386.1 | 22.3 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1815.2 | 376.8 | 27.8 Times are in microseconds (us). [-------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 962.3 | 400.0 | 29.4 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 4749.7 | 910.1 | 63.7 Times are in microseconds (us). [------------------------- Downsampling (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) -------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1098.1 | 272.0 | 36.4 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic forward pass, PIL, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4522.4 | 1406.7 | 170.3 channels_last non-contiguous torch.float32 | 4530.0 | 1435.4 | 242.2 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 5726.4 | 1628.6 | 164.0 channels_last non-contiguous torch.float32 | 5722.6 | 1665.6 | 234.7 Times are in microseconds (us). [------------------------------------ Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) ------------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2909.1 | 1461.5 | 276.9 channels_last non-contiguous torch.float32 | 2892.9 | 1458.7 | 345.1 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 14699.2 | 4283.9 | 407.1 channels_last non-contiguous torch.float32 | 14711.3 | 4321.1 | 477.0 Times are in microseconds (us). [----------------------------------- Downsampling (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) -----------------------------------] | Reference, PIL 8.4.0, mode: RGB | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3467.0 | 980.0 | 339.2 channels_last non-contiguous torch.float32 | 3465.2 | 982.3 | 407.8 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 2396.7 | 877.8 | 68.1 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 3068.2 | 777.3 | 64.7 Times are in microseconds (us). [-------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) ---------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1540.2 | 829.3 | 100.4 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 7919.5 | 1467.8 | 151.6 Times are in microseconds (us). [------------------------- Downsampling (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) --------------------------] | Reference, PIL 8.4.0, mode: F | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: --------------------------------------------------------------------------------------------------------------- contiguous torch.float32 | 1695.7 | 631.2 | 117.7 Times are in microseconds (us). ``` </details> <details> <summary> Bilinear backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (320, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 4686.8 | 215.7 channels_last non-contiguous torch.float32 | 5101.1 | 220.5 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (460, 220) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6011.2 | 204.4 channels_last non-contiguous torch.float32 | 6396.0 | 210.0 Times are in microseconds (us). [------------- Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 2035.6 | 250.2 channels_last non-contiguous torch.float32 | 1589.6 | 252.5 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11392.5 | 256.5 channels_last non-contiguous torch.float32 | 11640.2 | 263.9 Times are in microseconds (us). [------------ Downsampling backward (bilinear): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 11769.6 | 465.9 channels_last non-contiguous torch.float32 | 12407.0 | 474.4 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (320, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3931.0 | 133.3 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (460, 220) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 5594.8 | 133.9 Times are in microseconds (us). [---- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 1272.6 | 133.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 10618.1 | 134.0 Times are in microseconds (us). [--- Downsampling backward (bilinear): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 11082.2 | 154.6 Times are in microseconds (us). ``` </details> <details> <summary> Bicubic backward pass, PTH CPU and PTH CUDA </summary> Code: https://gist.github.com/vfdev-5/b173761a567f2283b3c649c3c0574112 ``` - Measure only backward op Torch version: 1.11.0a0+gitd032369 Torch config: PyTorch built with: - GCC 9.3 - C++ Version: 201402 - OpenMP 201511 (a.k.a. OpenMP 4.5) - CPU capability usage: AVX2 - CUDA Runtime 11.1 - NVCC architecture flags: -gencode;arch=compute_61,code=sm_61 - CuDNN 8.0.5 - Build settings: BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_PYTORCH_QNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.11.0, USE_CUDA=1, USE_CUDNN=1, USE_EIGEN_FOR_BLAS=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=OFF, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=0, USE_OPENMP=ON, USE_ROCM=OFF, Num threads: 8 [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (320, 196) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 6791.2 | 618.9 channels_last non-contiguous torch.float32 | 7125.2 | 622.9 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (460, 220) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 8806.2 | 600.3 channels_last non-contiguous torch.float32 | 9167.6 | 607.5 Times are in microseconds (us). [-------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 96) -------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 3683.6 | 693.8 channels_last non-contiguous torch.float32 | 3617.4 | 695.0 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (1200, 196) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 17548.2 | 779.4 channels_last non-contiguous torch.float32 | 17966.2 | 786.5 Times are in microseconds (us). [------------- Downsampling backward (bicubic): torch.Size([1, 3, 906, 438]) -> (120, 1200) ------------] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ---------------------------------------------------------------------------------------------- channels_first contiguous torch.float32 | 28.4 | 1.6 channels_last non-contiguous torch.float32 | 28.4 | 1.6 Times are in milliseconds (ms). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (320, 196) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 6266.1 | 208.5 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (460, 220) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 8218.3 | 200.8 Times are in microseconds (us). [----- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 96) -----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 3458.9 | 231.9 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (1200, 196) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 15729.3 | 261.6 Times are in microseconds (us). [---- Downsampling backward (bicubic): torch.Size([1, 1, 906, 438]) -> (120, 1200) ----] | 1.11.0a0+gitd032369 cpu | 1.11.0a0+gitd032369 cuda 8 threads: ----------------------------------------------------------------------------- contiguous torch.float32 | 26279.8 | 547.0 Times are in microseconds (us). ``` </details> Code is moved from torchvision: pytorch/vision#4211 and optimized Pull Request resolved: pytorch/pytorch#70930 Reviewed By: zou3519 Differential Revision: D33817902 Pulled By: jbschlosser fbshipit-source-id: d63a620f8972ff36b63841f0bc6c820466f58f69 (cherry picked from commit d358cfd)
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Description:
This code is based on #4208
cc @fmassa