CPU: remove oneDNN
This commit is contained in:
Attila Afra
@@ -270,17 +270,6 @@ jobs:
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artifact-out: build-rockylinux8-gcc-minimal
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artifact-out: build-rockylinux8-gcc-minimal
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artifact-path: build install deps
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artifact-path: build install deps
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build-rockylinux8-gcc-onednn:
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/docker.yml@main
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with:
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project: oidn
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image: oidn/rockylinux:8.8
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dpcpp-version: intel-llvm/v6.0.1-rk
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cmd: scripts/build.py install --compiler gcc -D OIDN_DEVICE_CPU_ONEDNN=ON
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artifact-out: build-rockylinux8-gcc-onednn
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artifact-path: build install deps
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build-rockylinux8-gta-aotjit:
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build-rockylinux8-gta-aotjit:
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secrets: inherit
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/docker.yml@main
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/docker.yml@main
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@@ -754,20 +743,6 @@ jobs:
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artifact-on-failure: true
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artifact-on-failure: true
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cmd: scripts/test.py --device cpu --log test.log
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cmd: scripts/test.py --device cpu --log test.log
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test-rockylinux8-gcc-onednn-avx2:
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needs: build-rockylinux8-gcc-onednn
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/docker.yml@main
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with:
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project: oidn
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runs-on: '[ "Linux", "avx2" ]'
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image: oidn/rockylinux:8.8
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artifact-in: build-rockylinux8-gcc-onednn
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artifact-out: test-rockylinux8-gcc-onednn-avx2
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artifact-path: test.log
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artifact-on-failure: true
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cmd: scripts/test.py --device cpu --log test.log
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test-ubuntu2204-clang-asan:
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test-ubuntu2204-clang-asan:
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needs: build-ubuntu2204-clang-asan
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needs: build-ubuntu2204-clang-asan
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secrets: inherit
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secrets: inherit
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@@ -1433,16 +1408,6 @@ jobs:
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runs-on: '[ "Windows", "build" ]'
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runs-on: '[ "Windows", "build" ]'
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cmd: python scripts/build.py --compiler msvc17 -D OIDN_LIBRARY_NAME=OIDN -D OIDN_API_NAMESPACE=myoidn
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cmd: python scripts/build.py --compiler msvc17 -D OIDN_LIBRARY_NAME=OIDN -D OIDN_API_NAMESPACE=myoidn
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build-windows-msvc17-onednn:
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/windows.yml@main
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with:
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project: oidn
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runs-on: '[ "Windows", "build" ]'
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artifact-out: build-windows-msvc17-onednn
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artifact-path: build install
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cmd: python scripts/build.py install --compiler msvc17 -D OIDN_DEVICE_CPU_ONEDNN=ON
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build-windows-msvc17-asan:
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build-windows-msvc17-asan:
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secrets: inherit
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/windows.yml@main
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/windows.yml@main
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@@ -1580,19 +1545,6 @@ jobs:
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artifact-on-failure: true
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artifact-on-failure: true
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cmd: python scripts/test.py --device cpu --log test.log
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cmd: python scripts/test.py --device cpu --log test.log
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test-windows-msvc17-onednn-avx512:
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needs: build-windows-msvc17-onednn
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secrets: inherit
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uses: intel-innersource/libraries.devops.renderkit.workflows/.github/workflows/windows.yml@main
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with:
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project: oidn
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runs-on: '[ "Windows", "avx512", "NAS" ]'
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artifact-in: build-windows-msvc17-onednn
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artifact-out: test-windows-msvc17-onednn-avx512
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artifact-path: test.log
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artifact-on-failure: true
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cmd: python scripts/test.py --device cpu --minimal --log test.log
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# FIXME: ASAN not on the path?
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# FIXME: ASAN not on the path?
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# test-windows-msvc17-asan-avx2:
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# test-windows-msvc17-asan-avx2:
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# needs: build-windows-msvc17-asan
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# needs: build-windows-msvc17-asan
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@@ -1,6 +1,3 @@
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[submodule "mkl-dnn"]
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path = external/mkl-dnn
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url = ../mkl-dnn.git
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[submodule "weights"]
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[submodule "weights"]
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path = weights
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path = weights
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url = ../oidn-weights.git
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url = ../oidn-weights.git
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@@ -134,7 +134,6 @@ install(
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${PROJECT_SOURCE_DIR}/CHANGELOG.md
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${PROJECT_SOURCE_DIR}/CHANGELOG.md
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${PROJECT_SOURCE_DIR}/third-party-programs.txt
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${PROJECT_SOURCE_DIR}/third-party-programs.txt
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${PROJECT_SOURCE_DIR}/third-party-programs-DPCPP.txt
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${PROJECT_SOURCE_DIR}/third-party-programs-DPCPP.txt
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${PROJECT_SOURCE_DIR}/third-party-programs-oneDNN.txt
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${PROJECT_SOURCE_DIR}/third-party-programs-oneTBB.txt
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${PROJECT_SOURCE_DIR}/third-party-programs-oneTBB.txt
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DESTINATION ${CMAKE_INSTALL_DOCDIR}
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DESTINATION ${CMAKE_INSTALL_DOCDIR}
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COMPONENT lib
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COMPONENT lib
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@@ -1,166 +0,0 @@
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## Copyright 2018 Intel Corporation
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## SPDX-License-Identifier: Apache-2.0
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set(DNNL_SOURCE_DIR "${PROJECT_SOURCE_DIR}/external/mkl-dnn")
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set(DNNL_BINARY_DIR "${PROJECT_BINARY_DIR}/external/mkl-dnn")
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set(DNNL_VERSION_MAJOR 3)
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set(DNNL_VERSION_MINOR 0)
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set(DNNL_VERSION_PATCH 1)
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set(DNNL_VERSION_HASH "N/A")
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set(DNNL_CPU_RUNTIME "TBB")
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set(DNNL_CPU_THREADING_RUNTIME "TBB")
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set(DNNL_GPU_RUNTIME "NONE")
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option(DNNL_ENABLE_JIT_PROFILING
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"Enable registration of oneDNN kernels that are generated at runtime with
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VTune Amplifier. Without the registrations, VTune Amplifier would report
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data collected inside the kernels as `outside any known module`."
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OFF)
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mark_as_advanced(DNNL_ENABLE_JIT_PROFILING)
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option(DNNL_ENABLE_ITT_TASKS
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"Enable ITT Tasks tagging feature and tag all primitive execution. VTune
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Amplifier can group profiling results based on those ITT tasks and show
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corresponding timeline information."
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OFF)
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mark_as_advanced(DNNL_ENABLE_ITT_TASKS)
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set(BUILD_INFERENCE TRUE)
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set(BUILD_CONVOLUTION TRUE)
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set(BUILD_PRIMITIVE_CPU_ISA_ALL TRUE)
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configure_file(
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"${DNNL_SOURCE_DIR}/include/oneapi/dnnl/dnnl_config.h.in"
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"${DNNL_BINARY_DIR}/include/oneapi/dnnl/dnnl_config.h"
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)
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configure_file(
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"${DNNL_SOURCE_DIR}/include/oneapi/dnnl/dnnl_version.h.in"
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"${DNNL_BINARY_DIR}/include/oneapi/dnnl/dnnl_version.h"
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)
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file(GLOB DNNL_SOURCES
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${DNNL_SOURCE_DIR}/src/common/*.[ch]pp
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${DNNL_SOURCE_DIR}/src/cpu/jit_utils/*.[ch]pp
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${DNNL_SOURCE_DIR}/src/cpu/x64/injectors/*.[ch]pp
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${DNNL_SOURCE_DIR}/src/cpu/x64/xbyak/*.h
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)
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list(APPEND DNNL_SOURCES
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${DNNL_SOURCE_DIR}/src/cpu/bfloat16.cpp
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${DNNL_SOURCE_DIR}/src/cpu/binary_injector_utils.cpp
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${DNNL_SOURCE_DIR}/src/cpu/binary_injector_utils.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_concat.cpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_convolution_list.cpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_convolution_pd.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_eltwise_pd.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_engine.cpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_engine.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_memory_storage.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_stream.hpp
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${DNNL_SOURCE_DIR}/src/cpu/cpu_sum.cpp
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${DNNL_SOURCE_DIR}/src/cpu/float16.cpp
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${DNNL_SOURCE_DIR}/src/cpu/platform.cpp
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${DNNL_SOURCE_DIR}/src/cpu/platform.hpp
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${DNNL_SOURCE_DIR}/src/cpu/primitive_attr_postops.cpp
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${DNNL_SOURCE_DIR}/src/cpu/primitive_attr_postops.hpp
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${DNNL_SOURCE_DIR}/src/cpu/scale_utils.cpp
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${DNNL_SOURCE_DIR}/src/cpu/scale_utils.hpp
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${DNNL_SOURCE_DIR}/src/cpu/simple_q10n.hpp
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${DNNL_SOURCE_DIR}/src/cpu/zero_point_utils.cpp
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${DNNL_SOURCE_DIR}/src/cpu/zero_point_utils.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/amx_tile_configure.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/amx_tile_configure.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_barrier.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_barrier.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_isa_traits.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_isa_traits.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_reducer.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/cpu_reducer.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx2_conv_kernel_f32.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx2_conv_kernel_f32.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx2_convolution.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx2_convolution.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx512_common_convolution.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx512_common_convolution.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx512_common_conv_kernel.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_avx512_common_conv_kernel.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_generator.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_primitive_conf.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_sse41_conv_kernel_f32.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_sse41_conv_kernel_f32.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_sse41_convolution.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_sse41_convolution.hpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_transpose_utils.cpp
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${DNNL_SOURCE_DIR}/src/cpu/x64/jit_transpose_utils.hpp
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)
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if(DNNL_ENABLE_JIT_PROFILING OR DNNL_ENABLE_ITT_TASKS)
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file(GLOB ITT_SOURCES ${DNNL_SOURCE_DIR}/src/common/ittnotify/*.[ch])
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list(APPEND DNNL_SOURCES ${ITT_SOURCES})
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endif()
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if(DNNL_ENABLE_JIT_PROFILING)
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list(APPEND DNNL_SOURCES
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${DNNL_SOURCE_DIR}/src/cpu/jit_utils/linux_perf/linux_perf.cpp
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${DNNL_SOURCE_DIR}/src/cpu/jit_utils/linux_perf/linux_perf.hpp
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)
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endif()
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if(MSVC)
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if(CMAKE_CXX_COMPILER_ID STREQUAL "MSVC" OR CMAKE_CXX_COMPILER_ID STREQUAL "Intel")
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set_source_files_properties(${DNNL_SOURCES} PROPERTIES COMPILE_FLAGS "/bigobj")
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endif()
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endif()
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add_library(dnnl STATIC ${DNNL_SOURCES})
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target_include_directories(dnnl
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PUBLIC
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$<BUILD_INTERFACE:${DNNL_SOURCE_DIR}/include>
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$<BUILD_INTERFACE:${DNNL_BINARY_DIR}/include>
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$<BUILD_INTERFACE:${DNNL_SOURCE_DIR}/src>
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$<BUILD_INTERFACE:${DNNL_SOURCE_DIR}/src/common>
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$<BUILD_INTERFACE:${DNNL_SOURCE_DIR}/src/cpu>
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$<BUILD_INTERFACE:${DNNL_SOURCE_DIR}/src/cpu/xbyak>
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)
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target_compile_definitions(dnnl
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PUBLIC
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-DDNNL_ENABLE_CONCURRENT_EXEC
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)
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set(DNNL_COMPILE_OPTIONS "")
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if(WIN32 AND CMAKE_CXX_COMPILER_ID STREQUAL "Intel")
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# Correct 'jnl' macro/jit issue
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list(APPEND DNNL_COMPILE_OPTIONS "/Qlong-double")
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endif()
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target_compile_options(dnnl PRIVATE ${DNNL_COMPILE_OPTIONS})
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target_link_libraries(dnnl
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|
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PUBLIC
|
|
||||||
${CMAKE_THREAD_LIBS_INIT}
|
|
||||||
TBB::tbb
|
|
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)
|
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||||||
|
|
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if(DNNL_ENABLE_JIT_PROFILING OR DNNL_ENABLE_ITT_TASKS)
|
|
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if(UNIX AND NOT APPLE)
|
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# Not every compiler adds -ldl automatically
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target_link_libraries(dnnl PUBLIC ${CMAKE_DL_LIBS})
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|
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endif()
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endif()
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if(DNNL_ENABLE_ITT_TASKS)
|
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target_compile_definitions(dnnl PUBLIC -DDNNL_ENABLE_ITT_TASKS)
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|
||||||
endif()
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|
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if(NOT DNNL_ENABLE_JIT_PROFILING)
|
|
||||||
target_compile_definitions(dnnl PUBLIC -DDNNL_ENABLE_JIT_PROFILING=0)
|
|
||||||
endif()
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|
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|
|
||||||
if(OIDN_STATIC_LIB)
|
|
||||||
install(TARGETS dnnl
|
|
||||||
EXPORT
|
|
||||||
OpenImageDenoise_Exports
|
|
||||||
ARCHIVE
|
|
||||||
DESTINATION ${CMAKE_INSTALL_LIBDIR} COMPONENT devel
|
|
||||||
)
|
|
||||||
endif()
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|
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@@ -16,15 +16,7 @@ if(NOT TBB_FOUND)
|
|||||||
find_package(TBB ${OIDN_TBB_MIN_VERSION} REQUIRED tbb)
|
find_package(TBB ${OIDN_TBB_MIN_VERSION} REQUIRED tbb)
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
if(OIDN_ARCH STREQUAL "X64")
|
if(APPLE AND OIDN_ARCH STREQUAL "ARM64")
|
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# oneDNN
|
|
||||||
option(OIDN_DEVICE_CPU_ONEDNN "Enable oneDNN for CPU device." OFF)
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|
||||||
mark_as_advanced(OIDN_DEVICE_CPU_ONEDNN)
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|
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if(OIDN_DEVICE_CPU_ONEDNN)
|
|
||||||
set(OIDN_DNNL ON)
|
|
||||||
include(oidn_dnnl)
|
|
||||||
endif()
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|
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elseif(APPLE AND OIDN_ARCH STREQUAL "ARM64")
|
|
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# BNNS
|
# BNNS
|
||||||
option(OIDN_DEVICE_CPU_BNNS "Enable BNNS for CPU device." ON)
|
option(OIDN_DEVICE_CPU_BNNS "Enable BNNS for CPU device." ON)
|
||||||
mark_as_advanced(OIDN_DEVICE_CPU_BNNS)
|
mark_as_advanced(OIDN_DEVICE_CPU_BNNS)
|
||||||
@@ -88,18 +80,7 @@ set(OIDN_ISPC_SOURCES_COMMON
|
|||||||
vec.isph
|
vec.isph
|
||||||
)
|
)
|
||||||
|
|
||||||
if(OIDN_DNNL)
|
if(OIDN_BNNS)
|
||||||
list(APPEND OIDN_CPU_SOURCES
|
|
||||||
dnnl/dnnl_conv.h
|
|
||||||
dnnl/dnnl_conv.cpp
|
|
||||||
dnnl/dnnl_common.h
|
|
||||||
dnnl/dnnl_common.cpp
|
|
||||||
dnnl/dnnl_engine.h
|
|
||||||
dnnl/dnnl_engine.cpp
|
|
||||||
dnnl/dnnl_tensor.h
|
|
||||||
dnnl/dnnl_tensor.cpp
|
|
||||||
)
|
|
||||||
elseif(OIDN_BNNS)
|
|
||||||
list(APPEND OIDN_CPU_SOURCES
|
list(APPEND OIDN_CPU_SOURCES
|
||||||
bnns/bnns_common.h
|
bnns/bnns_common.h
|
||||||
bnns/bnns_common.cpp
|
bnns/bnns_common.cpp
|
||||||
@@ -139,11 +120,7 @@ if(OIDN_LIBRARY_VERSIONED)
|
|||||||
set_target_properties(OpenImageDenoise_device_cpu PROPERTIES VERSION ${PROJECT_VERSION})
|
set_target_properties(OpenImageDenoise_device_cpu PROPERTIES VERSION ${PROJECT_VERSION})
|
||||||
endif()
|
endif()
|
||||||
|
|
||||||
if(OIDN_DNNL)
|
if(OIDN_BNNS)
|
||||||
target_compile_definitions(OpenImageDenoise_device_cpu PRIVATE OIDN_DNNL)
|
|
||||||
ispc_add_definitions(-DOIDN_DNNL)
|
|
||||||
target_link_libraries(OpenImageDenoise_device_cpu PRIVATE dnnl)
|
|
||||||
elseif(OIDN_BNNS)
|
|
||||||
target_compile_definitions(OpenImageDenoise_device_cpu PRIVATE OIDN_BNNS)
|
target_compile_definitions(OpenImageDenoise_device_cpu PRIVATE OIDN_BNNS)
|
||||||
ispc_add_definitions(-DOIDN_BNNS)
|
ispc_add_definitions(-DOIDN_BNNS)
|
||||||
target_link_libraries(OpenImageDenoise_device_cpu PRIVATE "-framework Accelerate")
|
target_link_libraries(OpenImageDenoise_device_cpu PRIVATE "-framework Accelerate")
|
||||||
|
|||||||
@@ -2,7 +2,7 @@
|
|||||||
// SPDX-License-Identifier: Apache-2.0
|
// SPDX-License-Identifier: Apache-2.0
|
||||||
|
|
||||||
#include "cpu_common.h"
|
#include "cpu_common.h"
|
||||||
#if !defined(OIDN_DNNL) && !defined(OIDN_BNNS)
|
#if !defined(OIDN_BNNS)
|
||||||
#include "cpu_conv_ispc.h"
|
#include "cpu_conv_ispc.h"
|
||||||
#if defined(OIDN_ARCH_X64)
|
#if defined(OIDN_ARCH_X64)
|
||||||
#include "cpu_conv_amx_ispc.h"
|
#include "cpu_conv_amx_ispc.h"
|
||||||
@@ -89,7 +89,7 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
}
|
}
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
#if !defined(OIDN_DNNL) && !defined(OIDN_BNNS)
|
#if !defined(OIDN_BNNS)
|
||||||
Tensor::operator ispc::TensorAccessor1D()
|
Tensor::operator ispc::TensorAccessor1D()
|
||||||
{
|
{
|
||||||
if (layout != TensorLayout::x)
|
if (layout != TensorLayout::x)
|
||||||
|
|||||||
@@ -4,9 +4,7 @@
|
|||||||
#include "cpu_device.h"
|
#include "cpu_device.h"
|
||||||
#include "platform_ispc.h"
|
#include "platform_ispc.h"
|
||||||
|
|
||||||
#if defined(OIDN_DNNL)
|
#if defined(OIDN_BNNS)
|
||||||
#include "dnnl/dnnl_engine.h"
|
|
||||||
#elif defined(OIDN_BNNS)
|
|
||||||
#include "bnns/bnns_engine.h"
|
#include "bnns/bnns_engine.h"
|
||||||
#else
|
#else
|
||||||
#include "cpu_engine.h"
|
#include "cpu_engine.h"
|
||||||
@@ -151,22 +149,7 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
|
|
||||||
std::unique_ptr<CPUEngine> engine;
|
std::unique_ptr<CPUEngine> engine;
|
||||||
|
|
||||||
#if defined(OIDN_DNNL)
|
#if defined(OIDN_BNNS)
|
||||||
if (arch == CPUArch::AVX512)
|
|
||||||
{
|
|
||||||
tensorLayout = TensorLayout::Chw16c;
|
|
||||||
weightLayout = TensorLayout::OIhw16i16o;
|
|
||||||
tensorBlockC = 16;
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
tensorLayout = TensorLayout::Chw8c;
|
|
||||||
weightLayout = TensorLayout::OIhw8i8o;
|
|
||||||
tensorBlockC = 8;
|
|
||||||
}
|
|
||||||
|
|
||||||
engine.reset(new DNNLEngine(this, numThreads));
|
|
||||||
#elif defined(OIDN_BNNS)
|
|
||||||
tensorLayout = TensorLayout::chw;
|
tensorLayout = TensorLayout::chw;
|
||||||
weightLayout = TensorLayout::oihw;
|
weightLayout = TensorLayout::oihw;
|
||||||
tensorBlockC = 1;
|
tensorBlockC = 1;
|
||||||
|
|||||||
@@ -33,7 +33,6 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
class CPUDevice final : public Device
|
class CPUDevice final : public Device
|
||||||
{
|
{
|
||||||
friend class CPUEngine;
|
friend class CPUEngine;
|
||||||
friend class DNNLEngine;
|
|
||||||
|
|
||||||
public:
|
public:
|
||||||
static std::vector<Ref<PhysicalDevice>> getPhysicalDevices();
|
static std::vector<Ref<PhysicalDevice>> getPhysicalDevices();
|
||||||
@@ -44,9 +43,7 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
|
|
||||||
DeviceType getType() const override { return DeviceType::CPU; }
|
DeviceType getType() const override { return DeviceType::CPU; }
|
||||||
|
|
||||||
#if !defined(OIDN_DNNL)
|
|
||||||
bool needWeightAndBiasOnDevice() const override { return false; } // no need to copy
|
bool needWeightAndBiasOnDevice() const override { return false; } // no need to copy
|
||||||
#endif
|
|
||||||
Storage getPtrStorage(const void* ptr) override;
|
Storage getPtrStorage(const void* ptr) override;
|
||||||
|
|
||||||
int getInt(const std::string& name) override;
|
int getInt(const std::string& name) override;
|
||||||
|
|||||||
@@ -3,7 +3,7 @@
|
|||||||
|
|
||||||
#include "core/conv.h"
|
#include "core/conv.h"
|
||||||
#include "cpu_engine.h"
|
#include "cpu_engine.h"
|
||||||
#if !defined(OIDN_DNNL) && !defined(OIDN_BNNS)
|
#if !defined(OIDN_BNNS)
|
||||||
#include "cpu_conv.h"
|
#include "cpu_conv.h"
|
||||||
#if defined(OIDN_ARCH_X64)
|
#if defined(OIDN_ARCH_X64)
|
||||||
#include "cpu_conv_amx.h"
|
#include "cpu_conv_amx.h"
|
||||||
@@ -75,7 +75,7 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
return postOp == PostOp::None;
|
return postOp == PostOp::None;
|
||||||
}
|
}
|
||||||
|
|
||||||
#if !defined(OIDN_DNNL) && !defined(OIDN_BNNS)
|
#if !defined(OIDN_BNNS)
|
||||||
Ref<Conv> CPUEngine::newConv(const ConvDesc& desc)
|
Ref<Conv> CPUEngine::newConv(const ConvDesc& desc)
|
||||||
{
|
{
|
||||||
#if defined(OIDN_ARCH_X64)
|
#if defined(OIDN_ARCH_X64)
|
||||||
|
|||||||
@@ -24,7 +24,7 @@ OIDN_NAMESPACE_BEGIN
|
|||||||
|
|
||||||
// Ops
|
// Ops
|
||||||
bool isConvSupported(PostOp postOp) override;
|
bool isConvSupported(PostOp postOp) override;
|
||||||
#if !defined(OIDN_DNNL) && !defined(OIDN_BNNS)
|
#if !defined(OIDN_BNNS)
|
||||||
Ref<Conv> newConv(const ConvDesc& desc) override;
|
Ref<Conv> newConv(const ConvDesc& desc) override;
|
||||||
#endif
|
#endif
|
||||||
Ref<Pool> newPool(const PoolDesc& desc) override;
|
Ref<Pool> newPool(const PoolDesc& desc) override;
|
||||||
|
|||||||
@@ -1,94 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#include "dnnl_common.h"
|
|
||||||
#include "dnnl_tensor.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
dnnl::memory::data_type toDNNL(DataType dataType)
|
|
||||||
{
|
|
||||||
switch (dataType)
|
|
||||||
{
|
|
||||||
case DataType::Float32:
|
|
||||||
return dnnl::memory::data_type::f32;
|
|
||||||
case DataType::Float16:
|
|
||||||
return dnnl::memory::data_type::f16;
|
|
||||||
case DataType::UInt8:
|
|
||||||
return dnnl::memory::data_type::u8;
|
|
||||||
default:
|
|
||||||
throw std::invalid_argument("unsupported data type");
|
|
||||||
}
|
|
||||||
}
|
|
||||||
|
|
||||||
dnnl::memory::desc toDNNL(const TensorDesc& td)
|
|
||||||
{
|
|
||||||
dnnl::memory::dims dnnlDims;
|
|
||||||
dnnl::memory::format_tag dnnlFormat;
|
|
||||||
switch (td.layout)
|
|
||||||
{
|
|
||||||
case TensorLayout::x:
|
|
||||||
assert(td.getRank() == 1);
|
|
||||||
dnnlDims = {td.getPaddedX()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::x;
|
|
||||||
break;
|
|
||||||
case TensorLayout::chw:
|
|
||||||
assert(td.getRank() == 3);
|
|
||||||
dnnlDims = {1, td.getPaddedC(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::nchw;
|
|
||||||
break;
|
|
||||||
case TensorLayout::Chw8c:
|
|
||||||
assert(td.getRank() == 3);
|
|
||||||
dnnlDims = {1, td.getPaddedC(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::nChw8c;
|
|
||||||
break;
|
|
||||||
case TensorLayout::Chw16c:
|
|
||||||
assert(td.getRank() == 3);
|
|
||||||
dnnlDims = {1, td.getPaddedC(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::nChw16c;
|
|
||||||
break;
|
|
||||||
case TensorLayout::oihw:
|
|
||||||
assert(td.getRank() == 4);
|
|
||||||
dnnlDims = {td.getPaddedO(), td.getPaddedI(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::oihw;
|
|
||||||
break;
|
|
||||||
case TensorLayout::OIhw8i8o:
|
|
||||||
assert(td.getRank() == 4);
|
|
||||||
dnnlDims = {td.getPaddedO(), td.getPaddedI(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::OIhw8i8o;
|
|
||||||
break;
|
|
||||||
case TensorLayout::OIhw16i16o:
|
|
||||||
assert(td.getRank() == 4);
|
|
||||||
dnnlDims = {td.getPaddedO(), td.getPaddedI(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::OIhw16i16o;
|
|
||||||
break;
|
|
||||||
case TensorLayout::OIhw2o8i8o2i:
|
|
||||||
assert(td.getRank() == 4);
|
|
||||||
dnnlDims = {td.getPaddedO(), td.getPaddedI(), td.getH(), td.getW()};
|
|
||||||
dnnlFormat = dnnl::memory::format_tag::OIhw2o8i8o2i;
|
|
||||||
break;
|
|
||||||
default:
|
|
||||||
throw std::invalid_argument("unsupported tensor layout");
|
|
||||||
}
|
|
||||||
|
|
||||||
return dnnl::memory::desc(dnnlDims, toDNNL(td.dataType), dnnlFormat);
|
|
||||||
}
|
|
||||||
|
|
||||||
dnnl::memory toDNNL(const Ref<Buffer>& buffer)
|
|
||||||
{
|
|
||||||
DNNLEngine* engine = dynamic_cast<DNNLEngine*>(buffer->getEngine());
|
|
||||||
if (!engine)
|
|
||||||
throw std::logic_error("buffer does not belong to a DNNL engine");
|
|
||||||
dnnl::memory::desc desc({int64_t(buffer->getByteSize())}, dnnl::memory::data_type::u8, dnnl::memory::format_tag::x);
|
|
||||||
return {desc, engine->getDNNLEngine(), buffer->getPtr()};
|
|
||||||
}
|
|
||||||
|
|
||||||
const dnnl::memory& getDNNL(const Ref<Tensor>& tensor)
|
|
||||||
{
|
|
||||||
if (auto dnnlTensor = dynamic_cast<const DNNLTensor*>(tensor.get()))
|
|
||||||
return dnnlTensor->getDNNLMemory();
|
|
||||||
else
|
|
||||||
throw std::invalid_argument("not DNNLTensor");
|
|
||||||
}
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,20 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#pragma once
|
|
||||||
|
|
||||||
#include "core/tensor.h"
|
|
||||||
#include "dnnl_engine.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
dnnl::memory::data_type toDNNL(DataType dataType);
|
|
||||||
dnnl::memory::desc toDNNL(const TensorDesc& td);
|
|
||||||
|
|
||||||
// Creates a DNNL memory structure for a buffer
|
|
||||||
dnnl::memory toDNNL(const Ref<Buffer>& buffer);
|
|
||||||
|
|
||||||
// Returns the internal DNNL memory structure of a DNNLTensor
|
|
||||||
const dnnl::memory& getDNNL(const Ref<Tensor>& tensor);
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,87 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#include "dnnl_conv.h"
|
|
||||||
#include "dnnl_tensor.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
DNNLConv::DNNLConv(DNNLEngine* engine, const ConvDesc& desc)
|
|
||||||
: Conv(desc),
|
|
||||||
engine(engine)
|
|
||||||
{
|
|
||||||
const dnnl::memory::dims strides = {1, 1};
|
|
||||||
const dnnl::memory::dims padding = {1, 1};
|
|
||||||
|
|
||||||
// Incorporate activation
|
|
||||||
dnnl::primitive_attr attr;
|
|
||||||
if (activation == Activation::ReLU)
|
|
||||||
{
|
|
||||||
dnnl::post_ops ops;
|
|
||||||
ops.append_eltwise(
|
|
||||||
dnnl::algorithm::eltwise_relu,
|
|
||||||
0.f, // alpha
|
|
||||||
0.f // beta
|
|
||||||
);
|
|
||||||
attr.set_post_ops(ops);
|
|
||||||
}
|
|
||||||
attr.set_scratchpad_mode(dnnl::scratchpad_mode::user);
|
|
||||||
|
|
||||||
primDesc = dnnl::convolution_forward::primitive_desc(
|
|
||||||
engine->getDNNLEngine(),
|
|
||||||
dnnl::prop_kind::forward_inference, dnnl::algorithm::convolution_direct,
|
|
||||||
toDNNL(srcDesc),
|
|
||||||
toDNNL(weightDesc),
|
|
||||||
toDNNL(biasDesc),
|
|
||||||
toDNNL(dstDesc),
|
|
||||||
strides, padding, padding,
|
|
||||||
attr);
|
|
||||||
}
|
|
||||||
|
|
||||||
size_t DNNLConv::getScratchByteSize()
|
|
||||||
{
|
|
||||||
return primDesc.scratchpad_desc().get_size();
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::setScratch(const Ref<Buffer>& scratch)
|
|
||||||
{
|
|
||||||
this->scratch = scratch;
|
|
||||||
args[DNNL_ARG_SCRATCHPAD] = toDNNL(scratch);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::updateSrc()
|
|
||||||
{
|
|
||||||
args[DNNL_ARG_SRC] = getDNNL(src);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::updateWeight()
|
|
||||||
{
|
|
||||||
args[DNNL_ARG_WEIGHTS] = getDNNL(weight);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::updateBias()
|
|
||||||
{
|
|
||||||
args[DNNL_ARG_BIAS] = getDNNL(bias);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::updateDst()
|
|
||||||
{
|
|
||||||
args[DNNL_ARG_DST] = getDNNL(dst);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::finalize()
|
|
||||||
{
|
|
||||||
prim = dnnl::convolution_forward(primDesc);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLConv::submitKernels(const Ref<CancellationToken>& ct)
|
|
||||||
{
|
|
||||||
if (!prim)
|
|
||||||
throw std::logic_error("convolution not finalized");
|
|
||||||
if (!src || !dst || !weight || !bias)
|
|
||||||
throw std::logic_error("convolution source/weight/bias/destination not set");
|
|
||||||
|
|
||||||
engine->submitFunc([=] { prim.execute(engine->getDNNLStream(), args); }, ct);
|
|
||||||
}
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,37 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#pragma once
|
|
||||||
|
|
||||||
#include "core/conv.h"
|
|
||||||
#include "dnnl_common.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
class DNNLConv final : public Conv
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
DNNLConv(DNNLEngine* engine, const ConvDesc& desc);
|
|
||||||
|
|
||||||
Engine* getEngine() const override { return engine; }
|
|
||||||
|
|
||||||
size_t getScratchByteSize() override;
|
|
||||||
void setScratch(const Ref<Buffer>& scratch) override;
|
|
||||||
|
|
||||||
void finalize() override;
|
|
||||||
void submitKernels(const Ref<CancellationToken>& ct) override;
|
|
||||||
|
|
||||||
private:
|
|
||||||
void updateSrc() override;
|
|
||||||
void updateWeight() override;
|
|
||||||
void updateBias() override;
|
|
||||||
void updateDst() override;
|
|
||||||
|
|
||||||
DNNLEngine* engine;
|
|
||||||
dnnl::convolution_forward::primitive_desc primDesc;
|
|
||||||
dnnl::convolution_forward prim;
|
|
||||||
std::unordered_map<int, dnnl::memory> args;
|
|
||||||
Ref<Buffer> scratch;
|
|
||||||
};
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,41 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#include "dnnl_engine.h"
|
|
||||||
#include "dnnl_tensor.h"
|
|
||||||
#include "dnnl_conv.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
DNNLEngine::DNNLEngine(CPUDevice* device, int numThreads)
|
|
||||||
: CPUEngine(device, numThreads)
|
|
||||||
{
|
|
||||||
dnnl_set_verbose(clamp(device->verbose - 2, 0, 2)); // unfortunately this is not per-device but global
|
|
||||||
dnnlEngine = dnnl::engine(dnnl::engine::kind::cpu, 0);
|
|
||||||
dnnlStream = dnnl::stream(dnnlEngine);
|
|
||||||
}
|
|
||||||
|
|
||||||
Ref<Tensor> DNNLEngine::newTensor(const TensorDesc& desc, Storage storage)
|
|
||||||
{
|
|
||||||
if (!isSupported(desc))
|
|
||||||
throw std::invalid_argument("unsupported tensor descriptor");
|
|
||||||
|
|
||||||
return makeRef<DNNLTensor>(this, desc, storage);
|
|
||||||
}
|
|
||||||
|
|
||||||
Ref<Tensor> DNNLEngine::newTensor(const Ref<Buffer>& buffer, const TensorDesc& desc, size_t byteOffset)
|
|
||||||
{
|
|
||||||
if (!isSupported(desc))
|
|
||||||
throw std::invalid_argument("unsupported tensor descriptor");
|
|
||||||
if (buffer->getEngine() != this)
|
|
||||||
throw std::invalid_argument("buffer was created by a different engine");
|
|
||||||
|
|
||||||
return makeRef<DNNLTensor>(buffer, desc, byteOffset);
|
|
||||||
}
|
|
||||||
|
|
||||||
Ref<Conv> DNNLEngine::newConv(const ConvDesc& desc)
|
|
||||||
{
|
|
||||||
return makeRef<DNNLConv>(this, desc);
|
|
||||||
}
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,30 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#pragma once
|
|
||||||
|
|
||||||
#include "../cpu_engine.h"
|
|
||||||
#include "mkl-dnn/include/dnnl.hpp"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
class DNNLEngine final : public CPUEngine
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
DNNLEngine(CPUDevice* device, int numThreads);
|
|
||||||
|
|
||||||
oidn_inline dnnl::engine& getDNNLEngine() { return dnnlEngine; }
|
|
||||||
oidn_inline dnnl::stream& getDNNLStream() { return dnnlStream; }
|
|
||||||
|
|
||||||
Ref<Tensor> newTensor(const TensorDesc& desc, Storage storage) override;
|
|
||||||
Ref<Tensor> newTensor(const Ref<Buffer>& buffer, const TensorDesc& desc, size_t byteOffset) override;
|
|
||||||
|
|
||||||
// Ops
|
|
||||||
Ref<Conv> newConv(const ConvDesc& desc) override;
|
|
||||||
|
|
||||||
private:
|
|
||||||
dnnl::engine dnnlEngine;
|
|
||||||
dnnl::stream dnnlStream;
|
|
||||||
};
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,31 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#include "dnnl_tensor.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
DNNLTensor::DNNLTensor(DNNLEngine* engine, const TensorDesc& desc, Storage storage)
|
|
||||||
: Tensor(engine->newBuffer(desc.getByteSize(), storage), desc)
|
|
||||||
{
|
|
||||||
mem = dnnl::memory(toDNNL(getDesc()), engine->getDNNLEngine(), buffer->getPtr());
|
|
||||||
}
|
|
||||||
|
|
||||||
DNNLTensor::DNNLTensor(const Ref<Buffer>& buffer, const TensorDesc& desc, size_t byteOffset)
|
|
||||||
: Tensor(buffer, desc, byteOffset)
|
|
||||||
{
|
|
||||||
if (byteOffset + getByteSize() > buffer->getByteSize())
|
|
||||||
throw Exception(Error::InvalidArgument, "buffer region is out of bounds");
|
|
||||||
|
|
||||||
mem = dnnl::memory(toDNNL(getDesc()),
|
|
||||||
static_cast<DNNLEngine*>(buffer->getEngine())->getDNNLEngine(),
|
|
||||||
static_cast<char*>(buffer->getPtr()) + byteOffset);
|
|
||||||
}
|
|
||||||
|
|
||||||
void DNNLTensor::postRealloc()
|
|
||||||
{
|
|
||||||
if (buffer)
|
|
||||||
mem.set_data_handle(static_cast<char*>(buffer->getPtr()) + byteOffset);
|
|
||||||
}
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,27 +0,0 @@
|
|||||||
// Copyright 2018 Intel Corporation
|
|
||||||
// SPDX-License-Identifier: Apache-2.0
|
|
||||||
|
|
||||||
#pragma once
|
|
||||||
|
|
||||||
#include "core/tensor.h"
|
|
||||||
#include "dnnl_common.h"
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_BEGIN
|
|
||||||
|
|
||||||
// Native DNNL tensor
|
|
||||||
class DNNLTensor final : public Tensor
|
|
||||||
{
|
|
||||||
public:
|
|
||||||
DNNLTensor(DNNLEngine* engine, const TensorDesc& desc, Storage storage);
|
|
||||||
DNNLTensor(const Ref<Buffer>& buffer, const TensorDesc& desc, size_t byteOffset);
|
|
||||||
|
|
||||||
void* getPtr() const override { return mem.get_data_handle(); }
|
|
||||||
const dnnl::memory& getDNNLMemory() const { return mem; }
|
|
||||||
|
|
||||||
private:
|
|
||||||
void postRealloc() override;
|
|
||||||
|
|
||||||
dnnl::memory mem;
|
|
||||||
};
|
|
||||||
|
|
||||||
OIDN_NAMESPACE_END
|
|
||||||
@@ -1,583 +0,0 @@
|
|||||||
oneAPI Deep Neural Network Library (oneDNN) Third Party Programs File
|
|
||||||
|
|
||||||
This file contains the list of third party software ("third party programs")
|
|
||||||
contained in the Intel software and their required notices and/or license
|
|
||||||
terms. This third party software, even if included with the distribution of
|
|
||||||
the Intel software, may be governed by separate license terms, including
|
|
||||||
without limitation, third party license terms, other Intel software license
|
|
||||||
terms, and open source software license terms. These separate license terms
|
|
||||||
govern your use of the third party programs as set forth in in the
|
|
||||||
"THIRD-PARTY-PROGRAMS" file.
|
|
||||||
|
|
||||||
Third party programs and their corresponding required notices and/or license
|
|
||||||
terms are listed below.
|
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
|
||||||
1. XByak (src/cpu/xbyak/)
|
|
||||||
Copyright (c) 2007 MITSUNARI Shigeo
|
|
||||||
All rights reserved.
|
|
||||||
|
|
||||||
3-Clause BSD License
|
|
||||||
|
|
||||||
Redistribution and use in source and binary forms, with or without
|
|
||||||
modification, are permitted provided that the following conditions are met:
|
|
||||||
|
|
||||||
Redistributions of source code must retain the above copyright notice, this
|
|
||||||
list of conditions and the following disclaimer.
|
|
||||||
Redistributions in binary form must reproduce the above copyright notice,
|
|
||||||
this list of conditions and the following disclaimer in the documentation
|
|
||||||
and/or other materials provided with the distribution.
|
|
||||||
Neither the name of the copyright owner nor the names of its contributors may
|
|
||||||
be used to endorse or promote products derived from this software without
|
|
||||||
specific prior written permission.
|
|
||||||
|
|
||||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
||||||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
||||||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
|
|
||||||
ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
|
||||||
LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
|
||||||
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
|
||||||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
|
||||||
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
|
||||||
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
|
||||||
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
|
|
||||||
THE POSSIBILITY OF SUCH DAMAGE.
|
|
||||||
|
|
||||||
|
|
||||||
ソースコード形式かバイナリ形式か、変更するかしないかを問わず、以下の条件を満た
|
|
||||||
す場合に限り、再頒布および使用が許可されます。
|
|
||||||
|
|
||||||
ソースコードを再頒布する場合、上記の著作権表示、本条件一覧、および下記免責条項
|
|
||||||
を含めること。
|
|
||||||
バイナリ形式で再頒布する場合、頒布物に付属のドキュメント等の資料に、上記の著作
|
|
||||||
権表示、本条件一覧、および下記免責条項を含めること。
|
|
||||||
書面による特別の許可なしに、本ソフトウェアから派生した製品の宣伝または販売促進
|
|
||||||
に、著作権者の名前またはコントリビューターの名前を使用してはならない。
|
|
||||||
本ソフトウェアは、著作権者およびコントリビューターによって「現状のまま」提供さ
|
|
||||||
れており、明示黙示を問わず、商業的な使用可能性、および特定の目的に対する適合性
|
|
||||||
に関する暗黙の保証も含め、またそれに限定されない、いかなる保証もありません。
|
|
||||||
著作権者もコントリビューターも、事由のいかんを問わず、 損害発生の原因いかんを
|
|
||||||
問わず、かつ責任の根拠が契約であるか厳格責任であるか（過失その他の）不法行為で
|
|
||||||
あるかを問わず、仮にそのような損害が発生する可能性を知らされていたとしても、
|
|
||||||
本ソフトウェアの使用によって発生した（代替品または代用サービスの調達、使用の
|
|
||||||
喪失、データの喪失、利益の喪失、業務の中断も含め、またそれに限定されない）直接
|
|
||||||
損害、間接損害、偶発的な損害、特別損害、懲罰的損害、または結果損害について、
|
|
||||||
一切責任を負わないものとします。
|
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
|
||||||
2. Googletest (tests/gtests/gtest/)
|
|
||||||
Copyright 2005, Google Inc.
|
|
||||||
Copyright 2006, Google Inc.
|
|
||||||
Copyright 2007, Google Inc.
|
|
||||||
Copyright 2008, Google Inc.
|
|
||||||
Copyright 2015, Google Inc.
|
|
||||||
All rights reserved.
|
|
||||||
|
|
||||||
3-Clause BSD License
|
|
||||||
|
|
||||||
Redistribution and use in source and binary forms, with or without
|
|
||||||
modification, are permitted provided that the following conditions are
|
|
||||||
met:
|
|
||||||
|
|
||||||
* Redistributions of source code must retain the above copyright
|
|
||||||
notice, this list of conditions and the following disclaimer.
|
|
||||||
* Redistributions in binary form must reproduce the above
|
|
||||||
copyright notice, this list of conditions and the following disclaimer
|
|
||||||
in the documentation and/or other materials provided with the
|
|
||||||
distribution.
|
|
||||||
* Neither the name of Google Inc. nor the names of its
|
|
||||||
contributors may be used to endorse or promote products derived from
|
|
||||||
this software without specific prior written permission.
|
|
||||||
|
|
||||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
|
||||||
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
|
||||||
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
|
||||||
OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
|
||||||
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
|
||||||
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
|
||||||
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
||||||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
||||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
|
||||||
3. Instrumentation and Tracing Technology API (src/common/ittnotify/)
|
|
||||||
Copyright (c) 2011, Intel Corporation. All rights reserved.
|
|
||||||
Copyright (c) 2005-2014 Intel Corporation. All rights reserved.
|
|
||||||
|
|
||||||
3-Clause BSD License
|
|
||||||
|
|
||||||
Redistribution and use in source and binary forms, with or without
|
|
||||||
modification, are permitted provided that the following conditions are met:
|
|
||||||
|
|
||||||
1. Redistributions of source code must retain the above copyright notice, this
|
|
||||||
list of conditions and the following disclaimer.
|
|
||||||
|
|
||||||
2. Redistributions in binary form must reproduce the above copyright notice,
|
|
||||||
this list of conditions and the following disclaimer in the documentation
|
|
||||||
and/or other materials provided with the distribution.
|
|
||||||
|
|
||||||
3. Neither the name of Intel Corporation nor the names of its
|
|
||||||
contributors may be used to endorse or promote products derived from
|
|
||||||
this software without specific prior written permission.
|
|
||||||
|
|
||||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
||||||
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
||||||
IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
|
|
||||||
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
|
|
||||||
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
|
|
||||||
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
|
|
||||||
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
|
|
||||||
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
|
|
||||||
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
||||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
|
||||||
4. CMake (cmake/FindOpenCL.cmake, cmake/FindBLAS.cmake, cmake/FindACL.cmake)
|
|
||||||
CMake - Cross Platform Makefile Generator
|
|
||||||
Copyright 2000-2020 Kitware, Inc. and Contributors
|
|
||||||
All rights reserved.
|
|
||||||
|
|
||||||
3-Clause BSD License
|
|
||||||
|
|
||||||
Redistribution and use in source and binary forms, with or without
|
|
||||||
modification, are permitted provided that the following conditions
|
|
||||||
are met:
|
|
||||||
|
|
||||||
* Redistributions of source code must retain the above copyright
|
|
||||||
notice, this list of conditions and the following disclaimer.
|
|
||||||
|
|
||||||
* Redistributions in binary form must reproduce the above copyright
|
|
||||||
notice, this list of conditions and the following disclaimer in the
|
|
||||||
documentation and/or other materials provided with the distribution.
|
|
||||||
|
|
||||||
* Neither the name of Kitware, Inc. nor the names of Contributors
|
|
||||||
may be used to endorse or promote products derived from this
|
|
||||||
software without specific prior written permission.
|
|
||||||
|
|
||||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
|
||||||
"AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
|
|
||||||
A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT
|
|
||||||
HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
|
|
||||||
SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
|
|
||||||
LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
|
|
||||||
DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
|
|
||||||
THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
|
|
||||||
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
|
|
||||||
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
|
||||||
|
|
||||||
------------------------------------------------------------------------------
|
|
||||||
|
|
||||||
The following individuals and institutions are among the Contributors:
|
|
||||||
|
|
||||||
* Aaron C. Meadows <cmake@shadowguarddev.com>
|
|
||||||
* Adriaan de Groot <groot@kde.org>
|
|
||||||
* Aleksey Avdeev <solo@altlinux.ru>
|
|
||||||
* Alexander Neundorf <neundorf@kde.org>
|
|
||||||
* Alexander Smorkalov <alexander.smorkalov@itseez.com>
|
|
||||||
* Alexey Sokolov <sokolov@google.com>
|
|
||||||
* Alex Merry <alex.merry@kde.org>
|
|
||||||
* Alex Turbov <i.zaufi@gmail.com>
|
|
||||||
* Andreas Pakulat <apaku@gmx.de>
|
|
||||||
* Andreas Schneider <asn@cryptomilk.org>
|
|
||||||
* André Rigland Brodtkorb <Andre.Brodtkorb@ifi.uio.no>
|
|
||||||
* Axel Huebl, Helmholtz-Zentrum Dresden - Rossendorf
|
|
||||||
* Benjamin Eikel
|
|
||||||
* Bjoern Ricks <bjoern.ricks@gmail.com>
|
|
||||||
* Brad Hards <bradh@kde.org>
|
|
||||||
* Christopher Harvey
|
|
||||||
* Christoph Grüninger <foss@grueninger.de>
|
|
||||||
* Clement Creusot <creusot@cs.york.ac.uk>
|
|
||||||
* Daniel Blezek <blezek@gmail.com>
|
|
||||||
* Daniel Pfeifer <daniel@pfeifer-mail.de>
|
|
||||||
* Enrico Scholz <enrico.scholz@informatik.tu-chemnitz.de>
|
|
||||||
* Eran Ifrah <eran.ifrah@gmail.com>
|
|
||||||
* Esben Mose Hansen, Ange Optimization ApS
|
|
||||||
* Geoffrey Viola <geoffrey.viola@asirobots.com>
|
|
||||||
* Google Inc
|
|
||||||
* Gregor Jasny
|
|
||||||
* Helio Chissini de Castro <helio@kde.org>
|
|
||||||
* Ilya Lavrenov <ilya.lavrenov@itseez.com>
|
|
||||||
* Insight Software Consortium <insightsoftwareconsortium.org>
|
|
||||||
* Jan Woetzel
|
|
||||||
* Julien Schueller
|
|
||||||
* Kelly Thompson <kgt@lanl.gov>
|
|
||||||
* Konstantin Podsvirov <konstantin@podsvirov.pro>
|
|
||||||
* Laurent Montel <montel@kde.org>
|
|
||||||
* Mario Bensi <mbensi@ipsquad.net>
|
|
||||||
* Martin Gräßlin <mgraesslin@kde.org>
|
|
||||||
* Mathieu Malaterre <mathieu.malaterre@gmail.com>
|
|
||||||
* Matthaeus G. Chajdas
|
|
||||||
* Matthias Kretz <kretz@kde.org>
|
|
||||||
* Matthias Maennich <matthias@maennich.net>
|
|
||||||
* Michael Hirsch, Ph.D. <www.scivision.co>
|
|
||||||
* Michael Stürmer
|
|
||||||
* Miguel A. Figueroa-Villanueva
|
|
||||||
* Mike Jackson
|
|
||||||
* Mike McQuaid <mike@mikemcquaid.com>
|
|
||||||
* Nicolas Bock <nicolasbock@gmail.com>
|
|
||||||
* Nicolas Despres <nicolas.despres@gmail.com>
|
|
||||||
* Nikita Krupen'ko <krnekit@gmail.com>
|
|
||||||
* NVIDIA Corporation <www.nvidia.com>
|
|
||||||
* OpenGamma Ltd. <opengamma.com>
|
|
||||||
* Patrick Stotko <stotko@cs.uni-bonn.de>
|
|
||||||
* Per Øyvind Karlsen <peroyvind@mandriva.org>
|
|
||||||
* Peter Collingbourne <peter@pcc.me.uk>
|
|
||||||
* Petr Gotthard <gotthard@honeywell.com>
|
|
||||||
* Philip Lowman <philip@yhbt.com>
|
|
||||||
* Philippe Proulx <pproulx@efficios.com>
|
|
||||||
* Raffi Enficiaud, Max Planck Society
|
|
||||||
* Raumfeld <raumfeld.com>
|
|
||||||
* Roger Leigh <rleigh@codelibre.net>
|
|
||||||
* Rolf Eike Beer <eike@sf-mail.de>
|
|
||||||
* Roman Donchenko <roman.donchenko@itseez.com>
|
|
||||||
* Roman Kharitonov <roman.kharitonov@itseez.com>
|
|
||||||
* Ruslan Baratov
|
|
||||||
* Sebastian Holtermann <sebholt@xwmw.org>
|
|
||||||
* Stephen Kelly <steveire@gmail.com>
|
|
||||||
* Sylvain Joubert <joubert.sy@gmail.com>
|
|
||||||
* The Qt Company Ltd.
|
|
||||||
* Thomas Sondergaard <ts@medical-insight.com>
|
|
||||||
* Tobias Hunger <tobias.hunger@qt.io>
|
|
||||||
* Todd Gamblin <tgamblin@llnl.gov>
|
|
||||||
* Tristan Carel
|
|
||||||
* University of Dundee
|
|
||||||
* Vadim Zhukov
|
|
||||||
* Will Dicharry <wdicharry@stellarscience.com>
|
|
||||||
|
|
||||||
See version control history for details of individual contributions.
|
|
||||||
|
|
||||||
The above copyright and license notice applies to distributions of
|
|
||||||
CMake in source and binary form. Third-party software packages supplied
|
|
||||||
with CMake under compatible licenses provide their own copyright notices
|
|
||||||
documented in corresponding subdirectories or source files.
|
|
||||||
|
|
||||||
------------------------------------------------------------------------------
|
|
||||||
|
|
||||||
CMake was initially developed by Kitware with the following sponsorship:
|
|
||||||
|
|
||||||
* National Library of Medicine at the National Institutes of Health
|
|
||||||
as part of the Insight Segmentation and Registration Toolkit (ITK).
|
|
||||||
|
|
||||||
* US National Labs (Los Alamos, Livermore, Sandia) ASC Parallel
|
|
||||||
Visualization Initiative.
|
|
||||||
|
|
||||||
* National Alliance for Medical Image Computing (NAMIC) is funded by the
|
|
||||||
National Institutes of Health through the NIH Roadmap for Medical Research,
|
|
||||||
Grant U54 EB005149.
|
|
||||||
|
|
||||||
* Kitware, Inc.
|
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
|
||||||
5. Xbyak_aarch64 (src/cpu/aarch64/xbyak_aarch64/)
|
|
||||||
Copyright 2019-2020 FUJITSU LIMITED
|
|
||||||
|
|
||||||
Apache License, Version 2.0
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|
||||||
|
|
||||||
Licensed under the Apache License, Version 2.0 (the "License");
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|
||||||
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|
|
||||||
You may obtain a copy of the License at
|
|
||||||
|
|
||||||
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|
|
||||||
|
|
||||||
Unless required by applicable law or agreed to in writing, software
|
|
||||||
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|
||||||
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|
|
||||||
See the License for the specific language governing permissions and
|
|
||||||
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|
|
||||||
|
|
||||||
|
|
||||||
Apache License
|
|
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|
||||||
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|
||||||
|
|
||||||
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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--------------------------------------------------------------------------------
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|
||||||
6. Boost C++ Libraries (src/common/primitive_hashing.hpp)
|
|
||||||
Copyright 2005-2014 Daniel James.
|
|
||||||
|
|
||||||
Boost Software License - Version 1.0 - August 17th, 2003
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||||||
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|
||||||
--------------------------------------------------------------------------------
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|
||||||
7. Intel(R) Graphics Compute Runtime for oneAPI Level Zero and OpenCL(TM)
|
|
||||||
Driver (src/gpu/jit/ngen/npack/{elf_structs,hash}.hpp)
|
|
||||||
Copyright (c) 2018 Intel Corporation
|
|
||||||
|
|
||||||
Intel(R) Graphics Compiler (src/gpu/jit/ngen/npack/neo_structs.hpp)
|
|
||||||
Copyright (c) 2019 Intel Corporation
|
|
||||||
|
|
||||||
oneAPI Level Zero (src/sycl/level_zero)
|
|
||||||
Copyright (C) 2019-2021 Intel Corporation
|
|
||||||
|
|
||||||
Doxyrest toolkit (doc/doxyrest/*)
|
|
||||||
Copyright (c) 2016, Tibbo Technology Inc
|
|
||||||
Copyright (c) 2016, Vladimir Gladkov
|
|
||||||
Copyright (c) 2016, Doxyrest maintainers
|
|
||||||
|
|
||||||
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|
|
||||||
|
|
||||||
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|
||||||
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|
||||||
|
|
||||||
8. Sphinx (doc/sphinx/conf/py)
|
|
||||||
Copyright (c) 2007-2021 by the Sphinx team (see AUTHORS file).
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|
||||||
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|
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||||||
|
|
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9. Intel(R) Metrics Discovery Application Programming Interface (src/gpu/ocl/mdapi/metrics_discovery_api.h)
|
|
||||||
MIT License
|
|
||||||
|
|
||||||
Copyright (c) 2019, Intel Corporation
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|
||||||
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|
||||||
Permission is hereby granted, free of charge, to any person obtaining a
|
|
||||||
copy of this software and associated documentation files (the "Software"),
|
|
||||||
to deal in the Software without restriction, including without limitation
|
|
||||||
the rights to use, copy, modify, merge, publish, distribute, sublicense,
|
|
||||||
and/or sell copies of the Software, and to permit persons to whom the
|
|
||||||
Software is furnished to do so, subject to the following conditions:
|
|
||||||
|
|
||||||
The above copyright notice and this permission notice shall be included
|
|
||||||
in all copies or substantial portions of the Software.
|
|
||||||
|
|
||||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
|
||||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
|
||||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
|
|
||||||
THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
|
||||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
|
|
||||||
FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
|
|
||||||
IN THE SOFTWARE.
|
|
||||||
@@ -14,10 +14,7 @@ terms are listed below.
|
|||||||
|
|
||||||
--------------------------------------------------------------------------------
|
--------------------------------------------------------------------------------
|
||||||
|
|
||||||
1. Intel(R) oneAPI Deep Neural Network Library (oneDNN)
|
1. Intel(R) oneAPI Threading Building Blocks (oneTBB)
|
||||||
Copyright 2016-2023 Intel Corporation
|
|
||||||
|
|
||||||
Intel(R) oneAPI Threading Building Blocks (oneTBB)
|
|
||||||
Copyright 2005-2023 Intel Corporation
|
Copyright 2005-2023 Intel Corporation
|
||||||
|
|
||||||
Intel® Embree (snippets)
|
Intel® Embree (snippets)
|
||||||
@@ -633,13 +630,10 @@ Software.
|
|||||||
The following third party programs have their own third party programs. These
|
The following third party programs have their own third party programs. These
|
||||||
additional third party program files are as follows:
|
additional third party program files are as follows:
|
||||||
|
|
||||||
1. Intel(R) oneAPI Deep Neural Network Library (oneDNN)
|
1. Intel(R) oneAPI Threading Building Blocks (oneTBB)
|
||||||
./third-party-programs-oneDNN.txt
|
|
||||||
|
|
||||||
2. Intel(R) oneAPI Threading Building Blocks (oneTBB)
|
|
||||||
./third-party-programs-oneTBB.txt
|
./third-party-programs-oneTBB.txt
|
||||||
|
|
||||||
3. oneAPI DPC++ Compiler
|
2. oneAPI DPC++ Compiler
|
||||||
./third-party-programs-DPCPP.txt
|
./third-party-programs-DPCPP.txt
|
||||||
|
|
||||||
--------------------------------------------------------------------------------
|
--------------------------------------------------------------------------------
|
||||||
Reference in New Issue
Block a user