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Upgrade oneDNN (mkl-dnn) to v1.7 (#47853)
Summary: Bump oneDNN (mkl-dnn) to 1.7 for bug fixes and performance optimizations - Fixes https://github.com/pytorch/pytorch/issues/42115. Fixed build issue on Windows for the case when oneDNN is built as submodule - Fixes https://github.com/pytorch/pytorch/issues/45746. Fixed segmentation fault for convolution weight gradient on systems with Intel AVX512 support This PR also contains a few changes in ideep for follow-up update (not enabled in current PR yet): - Performance improvements for the CPU path of Convolution - Channel-last support Pull Request resolved: https://github.com/pytorch/pytorch/pull/47853 Reviewed By: bdhirsh Differential Revision: D25275268 Pulled By: VitalyFedyunin fbshipit-source-id: 75a589d57e3d19a7f23272a67045ad7494f1bdbe
This commit is contained in:
parent
47aa253632
commit
1eed54d17a
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@ -7,4 +7,4 @@ if "%REBUILD%"=="" (
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7z x -aoa %TMP_DIR_WIN%\mkl.7z -o%TMP_DIR_WIN%\mkl
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7z x -aoa %TMP_DIR_WIN%\mkl.7z -o%TMP_DIR_WIN%\mkl
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)
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)
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set CMAKE_INCLUDE_PATH=%TMP_DIR_WIN%\mkl\include
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set CMAKE_INCLUDE_PATH=%TMP_DIR_WIN%\mkl\include
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set LIB=%TMP_DIR_WIN%\mkl\lib;%LIB
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set LIB=%TMP_DIR_WIN%\mkl\lib;%LIB%
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@ -129,7 +129,7 @@ public:
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// Pointer-like operations {
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// Pointer-like operations {
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C10_HOST_DEVICE
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C10_HOST_DEVICE
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reference operator*() {
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reference operator*() const {
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return TupleInfo::tie(*keys, *values);
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return TupleInfo::tie(*keys, *values);
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}
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}
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@ -1,7 +1,7 @@
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#pragma once
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#pragma once
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#include <caffe2/core/macros.h> // For caffe2 macros.
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#include <caffe2/core/macros.h> // For caffe2 macros.
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#include <caffe2/utils/eigen_utils.h>
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// All caffe2 ideep related headers
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// All caffe2 ideep related headers
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#include <ideep.hpp>
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#include <ideep.hpp>
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#include <caffe2/ideep/utils/ideep_context.h>
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#include <caffe2/ideep/utils/ideep_context.h>
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2
third_party/ideep
vendored
2
third_party/ideep
vendored
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@ -1 +1 @@
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Subproject commit ba885200dbbc1f144c7b58eba487378eb324f281
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Subproject commit f0280bb805c2dedd4bb5dd4765cda7dfcd30989f
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9
third_party/mkl-dnn.BUILD
vendored
9
third_party/mkl-dnn.BUILD
vendored
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@ -7,9 +7,9 @@ template_rule(
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out = "include/dnnl_version.h",
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out = "include/dnnl_version.h",
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substitutions = {
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substitutions = {
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"@DNNL_VERSION_MAJOR@": "1",
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"@DNNL_VERSION_MAJOR@": "1",
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"@DNNL_VERSION_MINOR@": "5",
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"@DNNL_VERSION_MINOR@": "7",
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"@DNNL_VERSION_PATCH@": "0",
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"@DNNL_VERSION_PATCH@": "0",
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"@DNNL_VERSION_HASH@": "e2ac1fac44c5078ca927cb9b90e1b3066a0b2ed0",
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"@DNNL_VERSION_HASH@": "2e4732679f0211bb311780d0f383cf2dce9baca7",
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},
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},
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)
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)
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@ -30,6 +30,8 @@ cc_library(
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srcs = glob([
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srcs = glob([
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"src/common/*.cpp",
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"src/common/*.cpp",
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"src/cpu/**/*.cpp",
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"src/cpu/**/*.cpp",
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], exclude=[
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"src/cpu/aarch64/*.cpp",
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]),
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]),
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hdrs = glob([
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hdrs = glob([
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"include/*.h",
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"include/*.h",
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@ -38,7 +40,8 @@ cc_library(
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"src/cpu/**/*.hpp",
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"src/cpu/**/*.hpp",
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"src/cpu/**/*.h",
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"src/cpu/**/*.h",
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"src/common/*.hpp",
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"src/common/*.hpp",
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"src/cpu/rnn/*.hpp",
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], exclude=[
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"src/cpu/aarch64/*.hpp",
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]) + [
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]) + [
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"include/dnnl_version.h",
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"include/dnnl_version.h",
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"include/dnnl_config.h",
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"include/dnnl_config.h",
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@ -1,5 +1,5 @@
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#pragma once
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#pragma once
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#include <math.h>
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// workaround for Python 2 issue: https://bugs.python.org/issue17120
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// workaround for Python 2 issue: https://bugs.python.org/issue17120
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// NOTE: It looks like this affects Python 3 as well.
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// NOTE: It looks like this affects Python 3 as well.
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#pragma push_macro("_XOPEN_SOURCE")
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#pragma push_macro("_XOPEN_SOURCE")
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