diff --git a/.clang-format b/.clang-format new file mode 100644 index 0000000000..22f2674966 --- /dev/null +++ b/.clang-format @@ -0,0 +1,90 @@ +--- +Language: Cpp +AccessModifierOffset: 0 +AlignAfterOpenBracket: Align +AlignConsecutiveAssignments: true +AlignConsecutiveDeclarations: false +AlignEscapedNewlinesLeft: true +AlignOperands: true +AlignTrailingComments: true +AllowAllParametersOfDeclarationOnNextLine: true +AllowShortBlocksOnASingleLine: true +AllowShortCaseLabelsOnASingleLine: true +AllowShortFunctionsOnASingleLine: All +AllowShortIfStatementsOnASingleLine: false +AllowShortLoopsOnASingleLine: false +AlwaysBreakAfterDefinitionReturnType: None +AlwaysBreakAfterReturnType: None +AlwaysBreakBeforeMultilineStrings: false +AlwaysBreakTemplateDeclarations: true +BinPackArguments: false +BinPackParameters: false +BraceWrapping: + AfterClass: true + AfterControlStatement: true + AfterEnum: true + AfterFunction: true + AfterNamespace: false + AfterObjCDeclaration: true + AfterStruct: true + AfterUnion: true + BeforeCatch: true + BeforeElse: true + IndentBraces: false +BreakBeforeBinaryOperators: None +BreakBeforeBraces: Custom +BreakBeforeTernaryOperators: true +BreakConstructorInitializersBeforeComma: false +ColumnLimit: 100 +CommentPragmas: '^ IWYU pragma:' +ConstructorInitializerAllOnOneLineOrOnePerLine: true +ConstructorInitializerIndentWidth: 4 +ContinuationIndentWidth: 4 +Cpp11BracedListStyle: true +DerivePointerAlignment: false +DisableFormat: false +ExperimentalAutoDetectBinPacking: false +ForEachMacros: [ foreach, Q_FOREACH, BOOST_FOREACH ] +IncludeCategories: + - Regex: '^"(llvm|llvm-c|clang|clang-c)/' + Priority: 2 + - Regex: '^(<|"(gtest|isl|json)/)' + Priority: 3 + - Regex: '.*' + Priority: 1 +IndentCaseLabels: false +IndentWidth: 4 +IndentWrappedFunctionNames: false +KeepEmptyLinesAtTheStartOfBlocks: true +MacroBlockBegin: '' +MacroBlockEnd: '' +MaxEmptyLinesToKeep: 1 +NamespaceIndentation: None +ObjCBlockIndentWidth: 2 +ObjCSpaceAfterProperty: false +ObjCSpaceBeforeProtocolList: true +PenaltyBreakBeforeFirstCallParameter: 19 +PenaltyBreakComment: 300 +PenaltyBreakFirstLessLess: 120 +PenaltyBreakString: 1000 +PenaltyExcessCharacter: 1000000 +PenaltyReturnTypeOnItsOwnLine: 60 +PointerAlignment: Left +ReflowComments: true +SortIncludes: false +SpaceAfterCStyleCast: false +# SpaceAfterTemplateKeyword: true +SpaceBeforeAssignmentOperators: true +SpaceBeforeParens: Never +SpaceInEmptyParentheses: false +SpacesBeforeTrailingComments: 1 +SpacesInAngles: false +SpacesInContainerLiterals: true +SpacesInCStyleCastParentheses: false +SpacesInParentheses: false +SpacesInSquareBrackets: false +Standard: Cpp11 +TabWidth: 8 +UseTab: Never +... + diff --git a/CMakeLists.txt b/CMakeLists.txt new file mode 100644 index 0000000000..b83215e744 --- /dev/null +++ b/CMakeLists.txt @@ -0,0 +1,337 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2020 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +cmake_minimum_required( VERSION 3.5 ) + +# This has to be initialized before the project() command appears +# Set the default of CMAKE_BUILD_TYPE to be release, unless user specifies with -D. MSVC_IDE does not use CMAKE_BUILD_TYPE +if( NOT MSVC_IDE AND NOT CMAKE_BUILD_TYPE ) + set( CMAKE_BUILD_TYPE Release CACHE STRING "Choose the type of build, options are: None Debug Release RelWithDebInfo MinSizeRel." ) +endif() + +# Default installation path +if(WIN32) + set(CMAKE_INSTALL_PREFIX "/opt/rocm/x86_64-w64-mingw32" CACHE PATH "") +else() + set(CMAKE_INSTALL_PREFIX "/opt/rocm" CACHE PATH "") +endif() + +project ( fin C CXX ) +option( BUILD_SHARED_LIBS "Build as a shared library" ON ) +enable_testing() + +find_package(ROCM REQUIRED PATHS /opt/rocm) + +include(ROCMInstallTargets) +include(ROCMPackageConfigHelpers) +include(ROCMSetupVersion) +include(ROCMInstallSymlinks) +include(ROCMCreatePackage) +include(CheckCXXCompilerFlag) + +option( BUILD_DEV "Build for development only" OFF) + +# Strip symbols for release +if(NOT WIN32 AND NOT APPLE) + set(CMAKE_C_FLAGS_RELEASE "${CMAKE_C_FLAGS_RELEASE} -s") + set(CMAKE_CXX_FLAGS_RELEASE "${CMAKE_CXX_FLAGS_RELEASE} -s") +endif() + +rocm_setup_version(VERSION 1.0.0) + +list( APPEND CMAKE_MODULE_PATH ${PROJECT_SOURCE_DIR}/cmake ) +include(TargetFlags) + +if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU") + if(CMAKE_CXX_COMPILER_VERSION VERSION_LESS "5.3") + message(FATAL_ERROR "MIOpen requires at least gcc 5.3") + endif() +endif() + +############################################################ +# require C++14 +add_compile_options(-std=c++14) + +############################################################ +# OPTION - MIOpen Backend +# - OpenCL +# - HCC +check_cxx_compiler_flag("--cuda-host-only -x hip" HAS_HIP) +if(CMAKE_CXX_COMPILER MATCHES ".*hcc" OR CMAKE_CXX_COMPILER MATCHES ".*hipcc" OR HAS_HIP) + set(FIN_DEFAULT_BACKEND "HIP") +else() + set(FIN_DEFAULT_BACKEND "OpenCL") +endif() + +if(WIN32 AND CMAKE_CROSSCOMPILING) + set(WINE_CMD "wine") +else() + set(WINE_CMD) +endif() + +list(APPEND CMAKE_PREFIX_PATH /opt/rocm /opt/rocm/hcc /opt/rocm/hip) + +set( FIN_BACKEND ${FIN_DEFAULT_BACKEND} CACHE STRING + "Which of MIOpens's backends to use?" ) +set_property( CACHE FIN_BACKEND PROPERTY STRINGS + OpenCL HIP HIPOC ) + +# HIP is always required +find_package(hip REQUIRED PATHS /opt/rocm) +find_package(rocblas REQUIRED PATHS /opt/rocm) +# probably not required +target_flags(HIP_COMPILER_FLAGS hip::device) +# Remove cuda arch flags +string(REGEX REPLACE --cuda-gpu-arch=[a-z0-9]+ "" HIP_COMPILER_FLAGS "${HIP_COMPILER_FLAGS}") + +message(STATUS "Hip compiler flags: ${HIP_COMPILER_FLAGS}") + +add_definitions("-DHIP_COMPILER_FLAGS=${HIP_COMPILER_FLAGS}") + +# OpenCL 1.2 +if( FIN_BACKEND STREQUAL "OpenCL") + message(STATUS "OpenCL Backend") + set(FIN_BACKEND_OPENCL 1) + find_package( OpenCL REQUIRED ) + find_program(FIN_HIP_COMPILER hcc + PATH_SUFFIXES bin + PATHS /opt/rocm + ) + find_package(miopengemm PATHS /opt/rocm) +endif() + +# HIP +if( FIN_BACKEND STREQUAL "HIP" OR FIN_BACKEND STREQUAL "HIPOC") + message(STATUS "HIP Backend") + set(FIN_BACKEND_HIP 1) + find_program(HIP_OC_COMPILER clang-ocl + PATH_SUFFIXES bin + PATHS /opt/rocm + ) + if(HIP_OC_COMPILER) + message(STATUS "hip compiler: ${HIP_OC_COMPILER}") + set(HIP_OC_COMPILER "${HIP_OC_COMPILER}") + else() + message(FATAL_ERROR "clang-ocl not found") + endif() + + if(CMAKE_CXX_COMPILER MATCHES ".*hcc") + link_libraries(stdc++) + + # A hack to make this work without the device enumerator + link_libraries(-amdgpu-target=gfx803 -amdgpu-target=gfx900 -Wno-unused-command-line-argument) + CHECK_CXX_COMPILER_FLAG("-amdgpu-target=gfx906 -Werror" GFX_906_FLAG_VALID) + if(GFX_906_FLAG_VALID) + link_libraries(-amdgpu-target=gfx906) + endif() + + CHECK_CXX_COMPILER_FLAG(-amdgpu-target=gfx908 -Werror, GFX_908_FLAG_VALID) + if(GFX_908_FLAG_VALID) + link_libraries(-amdgpu-target=gfx908) + endif() + # end hack + else() + # Hcc's clang always defines __HCC__ even when not using hcc driver + add_definitions(-U__HCC__) + endif() + # end hack + + set(MIOPEN_HIP_COMPILER ${CMAKE_CXX_COMPILER} CACHE PATH "") + +endif() +message( STATUS "${FIN_BACKEND} backend selected." ) + +# find_package for miopen is broken on the OpenCL backend +# look for and register extractkernel +find_program(EXTRACTKERNEL_BIN extractkernel + PATH_SUFFIXES bin + PATHS /opt/rocm +) +if(CMAKE_CXX_COMPILER MATCHES ".*hcc") + if(EXTRACTKERNEL_BIN) + message(STATUS "extractkernel found: ${EXTRACTKERNEL_BIN}") + set(EXTRACTKERNEL_BIN "${EXTRACTKERNEL_BIN}") + else() + message(FATAL_ERROR "extractkernel not found") + endif() +endif() + +option(Boost_USE_STATIC_LIBS "Use boost static libraries" ON) +set(BOOST_COMPONENTS filesystem system) +add_definitions(-DBOOST_ALL_NO_LIB=1) +find_package(Boost REQUIRED COMPONENTS ${BOOST_COMPONENTS}) + +find_path(HALF_INCLUDE_DIR half.hpp) + +option( BUILD_SHARED_LIBS "Build as a shared library" ON ) + +set(MIOPEN_PACKAGE_REQS "rocm-utils, hip-hcc") +set(CPACK_DEBIAN_PACKAGE_DEPENDS "${MIOPEN_PACKAGE_REQS}, rocm-opencl-dev") +set(CPACK_RPM_PACKAGE_REQUIRES "${MIOPEN_PACKAGE_REQS}, rocm-opencl-devel") + +rocm_create_package( + NAME fin-${FIN_BACKEND} + DESCRIPTION "Fin MIOpen Driver" + MAINTAINER "Jehandad Khan " + LDCONFIG + # DEPENDS rocm-opencl rocm-utils hip-hcc tinygemm +) + +include(EnableCompilerWarnings) +set(MIOPEN_TIDY_ERRORS ERRORS * -readability-inconsistent-declaration-parameter-name) +if(CMAKE_CXX_COMPILER MATCHES ".*hcc" OR CMAKE_CXX_COMPILER MATCHES ".*clang\\+\\+") + set(MIOPEN_TIDY_CHECKS -modernize-use-override -readability-non-const-parameter) +# Enable tidy on hip +elseif(FIN_BACKEND STREQUAL "HIP") + set(MIOPEN_TIDY_ERRORS ALL) +endif() + +include(ClangTidy) +enable_clang_tidy( + CHECKS + * + -android-cloexec-fopen + # Yea we shouldn't be using rand() + -cert-msc30-c + -bugprone-exception-escape + -cert-env33-c + -cert-msc32-c + -cert-msc50-cpp + -cert-msc51-cpp + -clang-analyzer-alpha.core.CastToStruct + -clang-analyzer-optin.performance.Padding + -clang-diagnostic-deprecated-declarations + -clang-diagnostic-extern-c-compat + -clang-diagnostic-unused-command-line-argument + -cppcoreguidelines-avoid-c-arrays + -cppcoreguidelines-avoid-magic-numbers + -cppcoreguidelines-explicit-virtual-functions + -cppcoreguidelines-init-variables + -cppcoreguidelines-macro-usage + -cppcoreguidelines-non-private-member-variables-in-classes + -cppcoreguidelines-pro-bounds-array-to-pointer-decay + -cppcoreguidelines-pro-bounds-constant-array-index + -cppcoreguidelines-pro-bounds-pointer-arithmetic + -cppcoreguidelines-pro-type-member-init + -cppcoreguidelines-pro-type-reinterpret-cast + -cppcoreguidelines-pro-type-union-access + -cppcoreguidelines-pro-type-vararg + -cppcoreguidelines-special-member-functions + -fuchsia-* + -google-explicit-constructor + -google-readability-braces-around-statements + -google-readability-todo + -google-runtime-int + -google-runtime-references + -hicpp-braces-around-statements + -hicpp-explicit-conversions + -hicpp-no-array-decay + # We really shouldn't use bitwise operators with signed integers, but + # opencl leaves us no choice + -hicpp-avoid-c-arrays + -hicpp-signed-bitwise + -hicpp-special-member-functions + -hicpp-uppercase-literal-suffix + -hicpp-use-auto + -hicpp-use-equals-default + -hicpp-use-override + -llvm-header-guard + -llvm-include-order + -misc-misplaced-const + -misc-non-private-member-variables-in-classes + -modernize-avoid-c-arrays + -modernize-pass-by-value + -modernize-use-auto + -modernize-use-default-member-init + -modernize-use-equals-default + -modernize-use-trailing-return-type + -modernize-use-transparent-functors + -performance-unnecessary-value-param + -readability-braces-around-statements + -readability-else-after-return + -readability-isolate-declaration + -readability-magic-numbers + -readability-named-parameter + -readability-uppercase-literal-suffix + -readability-convert-member-functions-to-static + + ${MIOPEN_TIDY_CHECKS} + ${MIOPEN_TIDY_ERRORS} + HEADER_FILTER + ".*hpp" + EXTRA_ARGS + -DMIOPEN_USE_CLANG_TIDY + +) +include(CppCheck) +enable_cppcheck( + CHECKS + warning + style + performance + portability + SUPPRESS + ConfigurationNotChecked + constStatement + duplicateCondition + noExplicitConstructor + passedByValue + # preprocessorErrorDirective + shadowVariable + unusedFunction + unusedPrivateFunction + unusedStructMember + # Ignore initializer lists in the tests + useInitializationList:*test/*.cpp + *:*.cl + *:*src/kernels/*.h + knownConditionTrueFalse:*src/kernels/composable_kernel/*/* + redundantAssignment:*src/kernels/composable_kernel/*/* + unreadVariable:*src/kernels/composable_kernel/*/* + unusedScopedObject:*src/kernels/composable_kernel/*/* + wrongPrintfScanfArgNum:*src/kernels/composable_kernel/*/* + unmatchedSuppression + FORCE + SOURCES + addkernels/ + # driver/ + include/ + src/ + test/ + INCLUDE + ${CMAKE_CURRENT_SOURCE_DIR}/include + ${CMAKE_CURRENT_BINARY_DIR}/include + ${CMAKE_CURRENT_SOURCE_DIR}/src/include + DEFINE + CPPCHECK=1 + MIOPEN_USE_MIOPENGEMM=1 + __linux__=1 +) + +set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/lib) +set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/lib) +set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/bin) + +add_subdirectory(src) diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000..723f52e803 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,89 @@ +FROM ubuntu:18.04 + +ARG PREFIX=/usr/local + +# Support multiarch +RUN dpkg --add-architecture i386 + +# Add rocm repository +RUN apt-get update +RUN DEBIAN_FRONTEND=noninteractive apt-get install -y curl apt-utils wget gnupg2 +RUN curl https://raw.githubusercontent.com/RadeonOpenCompute/ROCm-docker/master/add-rocm.sh | bash + +# Install dependencies required to build hcc +# Ubuntu csomic contains llvm-7 required to build Tensile +RUN sh -c "echo deb http://mirrors.kernel.org/ubuntu xenial main universe | tee -a /etc/apt/sources.list" +RUN apt-get update && DEBIAN_FRONTEND=noninteractive apt-get install -y --allow-unauthenticated \ + apt-utils \ + build-essential \ + clang-3.9 \ + clang-format-3.9 \ + clang-tidy-3.9 \ + cmake \ + comgr \ + curl \ + doxygen \ + g++-5-multilib \ + git \ + hsa-rocr-dev \ + hsakmt-roct-dev \ + jq \ + lcov \ + libelf-dev \ + libfile-which-perl \ + libncurses5-dev \ + libpthread-stubs0-dev \ + libnuma-dev \ + libunwind-dev \ + nsis \ + python \ + python-dev \ + python-pip \ + software-properties-common \ + libboost-all-dev \ + llvm-7 \ + pkg-config \ + python3 \ + python3-distutils \ + python3-venv \ + python-yaml \ + cppcheck \ + rocm-dev \ + rocm-opencl \ + rocm-opencl-dev \ + rocblas \ + miopen-hip && \ + apt-get clean && \ + rm -rf /var/lib/apt/lists/* + +# Setup ubsan environment to printstacktrace +ENV UBSAN_OPTIONS=print_stacktrace=1 + +# Install an init system +RUN wget https://github.com/Yelp/dumb-init/releases/download/v1.2.0/dumb-init_1.2.0_amd64.deb +RUN dpkg -i dumb-init_*.deb && rm dumb-init_*.deb + +# Install cget +RUN pip install https://github.com/pfultz2/cget/archive/57b3289000fcdb3b7e424c60a35ea09bc44d8538.tar.gz + +# Install rclone +RUN pip install https://github.com/pfultz2/rclone/archive/master.tar.gz + +# Install hcc from ROCm 3.0 +RUN rclone -b roc-3.0.x -c 286651a04d9c3a8e3052dd84b1822985498cd27d https://github.com/RadeonOpenCompute/hcc.git /hcc +RUN LDFLAGS=-fuse-ld=gold cget -p $PREFIX install hcc,/hcc && rm -rf /hcc + +# Make sure /opt/rcom is in the paths +ENV PATH="/opt/rocm:${PATH}" + +# Build using hcc +RUN cget -p $PREFIX init --cxx $PREFIX/bin/hcc --std=c++14 + +# Install dependencies +ADD requirements.txt /requirements.txt +RUN CXXFLAGS='-isystem $PREFIX/include' cget -p $PREFIX install -f /requirements.txt + +# Install doc requirements +#ADD doc/requirements.txt /doc-requirements.txt +#RUN pip install -r /doc-requirements.txt + diff --git a/Jenkinsfile b/Jenkinsfile new file mode 100644 index 0000000000..99e9550aa4 --- /dev/null +++ b/Jenkinsfile @@ -0,0 +1,172 @@ + + +def rocmnode(name) { + def node_name = 'rocmtest' + if(name == 'fiji') { + node_name = 'rocmtest && fiji'; + } else if(name == 'vega') { + node_name = 'rocmtest && vega'; + } else if(name == 'vega10') { + node_name = 'rocmtest && vega10'; + } else if(name == 'vega20') { + node_name = 'rocmtest && vega20'; + } else if(name == 'gfx908') { + node_name = 'gfx908'; + } else { + node_name = name + } + return node_name +} + + + +def cmake_build(compiler, flags, prefixpath="/opt/rocm"){ + def workspace_dir = pwd() + def vcache = "/var/jenkins/.cache/miopen/vcache" + def archive = (flags == '-DCMAKE_BUILD_TYPE=release') + def config_targets = "all" // "check doc MIOpenDriver" + def test_flags = "--disable-verification-cache" + def debug_flags = "-g -fno-omit-frame-pointer -fsanitize=undefined -fno-sanitize-recover=undefined" + def compilerpath = "" + def configargs = "" + if (prefixpath == "") + compilerpath = compiler; + else + { + compilerpath = prefixpath + "/bin/" + compiler + configargs = "-DCMAKE_PREFIX_PATH=${prefixpath}" + } + + if (archive == true) { + config_targets = "package" + } + def cmd = """ + echo \$HSA_ENABLE_SDMA + ulimit -c unlimited + rm -rf build + mkdir build + cd build + CXX=${compilerpath} CXXFLAGS='-Werror' cmake ${configargs} -DMIOPEN_GPU_SYNC=On -DMIOPEN_TEST_FLAGS='${test_flags}' -DCMAKE_CXX_FLAGS_DEBUG='${debug_flags}' ${flags} .. + MIOPEN_DEBUG_CONV_IMPLICIT_GEMM_XDLOPS=1 CTEST_PARALLEL_LEVEL=4 MIOPEN_VERIFY_CACHE_PATH=${vcache} MIOPEN_CONV_PRECISE_ROCBLAS_TIMING=0 dumb-init make -j\$(nproc) ${config_targets} + """ + echo cmd + sh cmd + // Only archive from master or develop + if (archive == true && (env.BRANCH_NAME == "develop" || env.BRANCH_NAME == "master")) { + archiveArtifacts artifacts: "build/*.deb", allowEmptyArchive: true, fingerprint: true + } +} + +def buildJob(compiler, flags, image, prefixpath="/opt/rocm", cmd = ""){ + + env.HSA_ENABLE_SDMA=0 + checkout scm + def dockerOpts="--device=/dev/kfd --device=/dev/dri --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined --user=root --privileged " + def dockerArgs = "--build-arg PREFIX=${prefixpath} " + if(prefixpath == "") + { + dockerArgs = "" + } + def retimage + try { + echo "build docker" + retimage = docker.build("${image}", dockerArgs + '.') + withDockerContainer(image: image, args: dockerOpts) { + timeout(time: 5, unit: 'MINUTES') + { + sh 'PATH="/opt/rocm/opencl/bin:/opt/rocm/opencl/bin/x86_64/:$PATH" clinfo' + } + } + } catch(Exception ex) { + echo "exception ocurred" + retimage = docker.build("${image}", dockerArgs + "--no-cache .") + withDockerContainer(image: image, args: dockerOpts) { + timeout(time: 5, unit: 'MINUTES') + { + sh 'PATH="/opt/rocm/opencl/bin:/opt/rocm/opencl/bin/x86_64/:$PATH" clinfo' + } + } + } + + withDockerContainer(image: image, args: dockerOpts + ' -v=/var/jenkins/:/var/jenkins') { + timeout(time: 5, unit: 'HOURS') + { + if(cmd == ""){ + cmake_build(compiler, flags, prefixpath) + }else{ + echo "run shell command" + sh cmd + } + } + } + return retimage +} + + + +pipeline { + agent none + options { + parallelsAlwaysFailFast() + } + environment{ + image = "miopen" + } + stages{ + // Run all static analysis tests + stage("Static checks"){ + parallel{ + stage('Clang Tidy') { + agent{ label rocmnode("rocmtest") } + environment{ + cmd = "rm -rf build; \ + mkdir build; \ + cd build; \ + CXX='clang++-3.9' cmake -DBUILD_DEV=On ..; \ + make -j\$(nproc) -k analyze;" + } + steps{ + buildJob('clang++-3.9', '-DCMAKE_BUILD_TYPE=release', image, "", cmd) + } + } + + stage('Clang Format') { + agent{ label rocmnode("rocmtest") } + environment{ + cmd = "cd src; find . -iname \'*.h\' \ + -o -iname \'*.hpp\' \ + -o -iname \'*.cpp\' \ + -o -iname \'*.h.in\' \ + -o -iname \'*.hpp.in\' \ + -o -iname \'*.cpp.in\' \ + -o -iname \'*.cl\' \ + | grep -v 'build/' \ + | grep -v 'base64' \ + | xargs -n 1 -P 1 -I{} -t sh -c \'clang-format-3.9 -style=file {} | diff - {}\'" + } + steps{ + buildJob('clang++-3.9', '-DCMAKE_BUILD_TYPE=release', image, "", cmd) + } + } + + stage('Hip Tidy') { + agent{ label rocmnode("rocmtest") } + environment{ + cmd = "rm -rf build; \ + mkdir build; \ + cd build; \ + CXX=/usr/local/bin/hcc cmake -DBUILD_DEV=On ..; \ + make -j\$(nproc) -k analyze;" + } + steps{ + buildJob('hcc', '-DCMAKE_BUILD_TYPE=release', image, "", cmd) + } + } + } + } + + + + } +} + diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000000..c1bbfe9e0a --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2020 ROCm Software Platform + +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. diff --git a/cmake/Analyzers.cmake b/cmake/Analyzers.cmake new file mode 100644 index 0000000000..1bf1a52c68 --- /dev/null +++ b/cmake/Analyzers.cmake @@ -0,0 +1,34 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ + +if(NOT TARGET analyze) + add_custom_target(analyze) +endif() + +function(mark_as_analyzer) + add_dependencies(analyze ${ARGN}) +endfunction() + diff --git a/cmake/ClangTidy.cmake b/cmake/ClangTidy.cmake new file mode 100644 index 0000000000..291291a446 --- /dev/null +++ b/cmake/ClangTidy.cmake @@ -0,0 +1,160 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. +# +################################################################################ +include(CMakeParseArguments) +include(Analyzers) + +get_filename_component(CLANG_TIDY_EXE_HINT "${CMAKE_CXX_COMPILER}" PATH) + +find_program(CLANG_TIDY_EXE + NAMES + clang-tidy + clang-tidy-5.0 + clang-tidy-4.0 + clang-tidy-3.9 + clang-tidy-3.8 + clang-tidy-3.7 + clang-tidy-3.6 + clang-tidy-3.5 + HINTS + ${CLANG_TIDY_EXE_HINT} + PATH_SUFFIXES + compiler/bin + PATHS + /opt/rocm/llvm/bin + /opt/rocm/hcc + /usr/local/opt/llvm/bin +) + +function(find_clang_tidy_version VAR) + execute_process(COMMAND ${CLANG_TIDY_EXE} -version OUTPUT_VARIABLE VERSION_OUTPUT) + separate_arguments(VERSION_OUTPUT_LIST UNIX_COMMAND "${VERSION_OUTPUT}") + list(FIND VERSION_OUTPUT_LIST "version" VERSION_INDEX) + if(VERSION_INDEX GREATER 0) + math(EXPR VERSION_INDEX "${VERSION_INDEX} + 1") + list(GET VERSION_OUTPUT_LIST ${VERSION_INDEX} VERSION) + set(${VAR} ${VERSION} PARENT_SCOPE) + else() + set(${VAR} "0.0" PARENT_SCOPE) + endif() + +endfunction() + +if( NOT CLANG_TIDY_EXE ) + message( STATUS "Clang tidy not found" ) + set(CLANG_TIDY_VERSION "0.0") +else() + find_clang_tidy_version(CLANG_TIDY_VERSION) + message( STATUS "Clang tidy found: ${CLANG_TIDY_VERSION}") +endif() + +set(CMAKE_EXPORT_COMPILE_COMMANDS ON) + +set(CLANG_TIDY_FIXIT_DIR ${CMAKE_BINARY_DIR}/fixits) +file(MAKE_DIRECTORY ${CLANG_TIDY_FIXIT_DIR}) +set_property(DIRECTORY APPEND PROPERTY ADDITIONAL_MAKE_CLEAN_FILES ${CLANG_TIDY_FIXIT_DIR}) + +macro(enable_clang_tidy) + set(options ANALYZE_TEMPORARY_DTORS ALL) + set(oneValueArgs HEADER_FILTER) + set(multiValueArgs CHECKS ERRORS EXTRA_ARGS) + + cmake_parse_arguments(PARSE "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + string(REPLACE ";" "," CLANG_TIDY_CHECKS "${PARSE_CHECKS}") + string(REPLACE ";" "," CLANG_TIDY_ERRORS "${PARSE_ERRORS}") + set(CLANG_TIDY_EXTRA_ARGS) + foreach(ARG ${PARSE_EXTRA_ARGS}) + list(APPEND CLANG_TIDY_EXTRA_ARGS "-extra-arg=${ARG}") + endforeach() + + set(CLANG_TIDY_ALL) + if(PARSE_ALL) + set(CLANG_TIDY_ALL ALL) + endif() + + message(STATUS "Clang tidy checks: ${CLANG_TIDY_CHECKS}") + + if (${PARSE_ANALYZE_TEMPORARY_DTORS}) + set(CLANG_TIDY_ANALYZE_TEMPORARY_DTORS "-analyze-temporary-dtors") + endif() + + if (${CLANG_TIDY_VERSION} VERSION_LESS "3.9.0") + set(CLANG_TIDY_ERRORS_ARG "") + else() + set(CLANG_TIDY_ERRORS_ARG "-warnings-as-errors='${CLANG_TIDY_ERRORS}'") + endif() + + if (${CLANG_TIDY_VERSION} VERSION_LESS "3.9.0") + set(CLANG_TIDY_QUIET_ARG "") + else() + set(CLANG_TIDY_QUIET_ARG "-quiet") + endif() + + if(PARSE_HEADER_FILTER) + string(REPLACE "$" "$$" CLANG_TIDY_HEADER_FILTER "${PARSE_HEADER_FILTER}") + else() + set(CLANG_TIDY_HEADER_FILTER ".*") + endif() + + set(CLANG_TIDY_COMMAND + ${CLANG_TIDY_EXE} + ${CLANG_TIDY_QUIET_ARG} + -p ${CMAKE_BINARY_DIR} + -checks='${CLANG_TIDY_CHECKS}' + ${CLANG_TIDY_ERRORS_ARG} + ${CLANG_TIDY_EXTRA_ARGS} + ${CLANG_TIDY_ANALYZE_TEMPORARY_DTORS} + -header-filter='${CLANG_TIDY_HEADER_FILTER}' + ) + add_custom_target(tidy ${CLANG_TIDY_ALL}) + mark_as_analyzer(tidy) + add_custom_target(tidy-base) + add_custom_target(tidy-make-fixit-dir COMMAND ${CMAKE_COMMAND} -E make_directory ${CLANG_TIDY_FIXIT_DIR}) + add_custom_target(tidy-rm-fixit-dir COMMAND ${CMAKE_COMMAND} -E remove_directory ${CLANG_TIDY_FIXIT_DIR}) + add_dependencies(tidy-make-fixit-dir tidy-rm-fixit-dir) + add_dependencies(tidy-base tidy-make-fixit-dir) +endmacro() + +function(clang_tidy_check TARGET) + get_target_property(SOURCES ${TARGET} SOURCES) + # TODO: Use generator expressions instead + # COMMAND ${CLANG_TIDY_COMMAND} $ + # COMMAND ${CLANG_TIDY_COMMAND} $, > + foreach(SOURCE ${SOURCES}) + if(NOT "${SOURCE}" MATCHES "(h|hpp|hxx)$") + string(MAKE_C_IDENTIFIER "${SOURCE}" tidy_file) + set(tidy_target tidy-target-${TARGET}-${tidy_file}) + add_custom_target(${tidy_target} + COMMAND ${CLANG_TIDY_COMMAND} ${SOURCE} "-export-fixes=${CLANG_TIDY_FIXIT_DIR}/${TARGET}-${tidy_file}.yaml" + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + COMMENT "clang-tidy: Running clang-tidy on target ${SOURCE}..." + ) + add_dependencies(${tidy_target} ${TARGET}) + add_dependencies(${tidy_target} tidy-base) + add_dependencies(tidy ${tidy_target}) + endif() + endforeach() +endfunction() + diff --git a/cmake/CppCheck.cmake b/cmake/CppCheck.cmake new file mode 100644 index 0000000000..797dcf4b4d --- /dev/null +++ b/cmake/CppCheck.cmake @@ -0,0 +1,130 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ + +include(CMakeParseArguments) +include(ProcessorCount) +include(Analyzers) + +find_program(CPPCHECK_EXE + NAMES + cppcheck + PATHS + /opt/rocm/bin +) + +ProcessorCount(CPPCHECK_JOBS) + +set(CPPCHECK_BUILD_DIR ${CMAKE_BINARY_DIR}/cppcheck-build) +file(MAKE_DIRECTORY ${CPPCHECK_BUILD_DIR}) +set_property(DIRECTORY APPEND PROPERTY ADDITIONAL_MAKE_CLEAN_FILES ${CPPCHECK_BUILD_DIR}) + +macro(enable_cppcheck) + set(options FORCE) + set(oneValueArgs) + set(multiValueArgs CHECKS SUPPRESS DEFINE UNDEFINE INCLUDE SOURCES) + + cmake_parse_arguments(PARSE "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + string(REPLACE ";" "," CPPCHECK_CHECKS "${PARSE_CHECKS}") + string(REPLACE ";" "\n" CPPCHECK_SUPPRESS "${PARSE_SUPPRESS};*:/usr/*") + file(WRITE ${CMAKE_BINARY_DIR}/cppcheck-supressions "${CPPCHECK_SUPPRESS}") + set(CPPCHECK_DEFINES) + foreach(DEF ${PARSE_DEFINE}) + set(CPPCHECK_DEFINES "${CPPCHECK_DEFINES} -D${DEF}") + endforeach() + + set(CPPCHECK_UNDEFINES) + foreach(DEF ${PARSE_UNDEFINE}) + set(CPPCHECK_UNDEFINES "${CPPCHECK_UNDEFINES} -U${DEF}") + endforeach() + + set(CPPCHECK_INCLUDES) + foreach(INC ${PARSE_INCLUDE}) + set(CPPCHECK_INCLUDES "${CPPCHECK_INCLUDES} -I${INC}") + endforeach() + + # set(CPPCHECK_FORCE) + set(CPPCHECK_FORCE "--project=${CMAKE_BINARY_DIR}/compile_commands.json") + if(PARSE_FORCE) + set(CPPCHECK_FORCE --force) + endif() + + set(SOURCES) + set(GLOBS) + foreach(SOURCE ${PARSE_SOURCES}) + get_filename_component(ABS_SOURCE ${SOURCE} ABSOLUTE) + if(EXISTS ${ABS_SOURCE}) + if(IS_DIRECTORY ${ABS_SOURCE}) + set(GLOBS "${GLOBS} ${ABS_SOURCE}/*.cpp ${ABS_SOURCE}/*.hpp ${ABS_SOURCE}/*.cxx ${ABS_SOURCE}/*.c ${ABS_SOURCE}/*.h") + else() + set(SOURCES "${SOURCES} ${ABS_SOURCE}") + endif() + else() + set(GLOBS "${GLOBS} ${ABS_SOURCE}") + endif() + endforeach() + + file(WRITE ${CMAKE_BINARY_DIR}/cppcheck.cmake " + file(GLOB_RECURSE GSRCS ${GLOBS}) + set(CPPCHECK_COMMAND + ${CPPCHECK_EXE} + -q + # -v + # --report-progress + ${CPPCHECK_FORCE} + --cppcheck-build-dir=${CPPCHECK_BUILD_DIR} + --platform=native + --template=gcc + --error-exitcode=1 + -j ${CPPCHECK_JOBS} + ${CPPCHECK_DEFINES} + ${CPPCHECK_UNDEFINES} + ${CPPCHECK_INCLUDES} + --enable=${CPPCHECK_CHECKS} + --inline-suppr + --suppressions-list=${CMAKE_BINARY_DIR}/cppcheck-supressions + ${SOURCES} \${GSRCS} + ) + string(REPLACE \";\" \" \" CPPCHECK_SHOW_COMMAND \"\${CPPCHECK_COMMAND}\") + message(\"\${CPPCHECK_SHOW_COMMAND}\") + execute_process( + COMMAND \${CPPCHECK_COMMAND} + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + RESULT_VARIABLE RESULT + ) + if(NOT RESULT EQUAL 0) + message(FATAL_ERROR \"Cppcheck failed\") + endif() +") + + add_custom_target(cppcheck + COMMAND ${CMAKE_COMMAND} -P ${CMAKE_BINARY_DIR}/cppcheck.cmake + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + COMMENT "cppcheck: Running cppcheck..." + ) + mark_as_analyzer(cppcheck) +endmacro() + + diff --git a/cmake/DoxygenDoc.cmake b/cmake/DoxygenDoc.cmake new file mode 100644 index 0000000000..2e3669fcdf --- /dev/null +++ b/cmake/DoxygenDoc.cmake @@ -0,0 +1,355 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +include(CMakeParseArguments) +include(MainDoc) + +find_program(DOXYGEN_EXECUTABLE NAMES doxygen + PATH_SUFFIXES bin + DOC "Doxygen documentation generator" +) +mark_as_advanced(DOXYGEN_EXECUTABLE) + +find_path(DOT_EXECUTABLE NAMES dot + PATH_SUFFIXES bin + DOC "Graphviz" +) +mark_as_advanced(DOT_EXECUTABLE) + +set(DOXYGEN_ARGS +ABBREVIATE_BRIEF +ALIASES +ALLEXTERNALS +ALLOW_UNICODE_NAMES +ALPHABETICAL_INDEX +ALWAYS_DETAILED_SEC +AUTOLINK_SUPPORT +BINARY_TOC +BRIEF_MEMBER_DESC +BUILTIN_STL_SUPPORT +CALLER_GRAPH +CALL_GRAPH +CASE_SENSE_NAMES +CHM_FILE +CHM_INDEX_ENCODING +CITE_BIB_FILES +CLANG_ASSISTED_PARSING +CLANG_OPTIONS +CLASS_DIAGRAMS +CLASS_GRAPH +COLLABORATION_GRAPH +COLS_IN_ALPHA_INDEX +COMPACT_LATEX +COMPACT_RTF +CPP_CLI_SUPPORT +CREATE_SUBDIRS +DIAFILE_DIRS +DIA_PATH +DIRECTORY_GRAPH +DISABLE_INDEX +DISTRIBUTE_GROUP_DOC +DOCBOOK_OUTPUT +DOCBOOK_PROGRAMLISTING +DOCSET_BUNDLE_ID +DOCSET_FEEDNAME +DOCSET_PUBLISHER_ID +DOCSET_PUBLISHER_NAME +DOTFILE_DIRS +DOT_CLEANUP +DOT_FONTNAME +DOT_FONTPATH +DOT_FONTSIZE +DOT_GRAPH_MAX_NODES +DOT_IMAGE_FORMAT +DOT_MULTI_TARGETS +DOT_NUM_THREADS +# DOT_PATH +DOT_TRANSPARENT +DOXYFILE_ENCODING +ECLIPSE_DOC_ID +ENABLED_SECTIONS +ENABLE_PREPROCESSING +ENUM_VALUES_PER_LINE +EXAMPLE_PATH +EXAMPLE_PATTERNS +EXAMPLE_RECURSIVE +EXCLUDE +EXCLUDE_PATTERNS +EXCLUDE_SYMBOLS +EXCLUDE_SYMLINKS +EXPAND_AS_DEFINED +EXPAND_ONLY_PREDEF +EXTENSION_MAPPING +EXTERNAL_GROUPS +EXTERNAL_PAGES +EXTERNAL_SEARCH +EXTERNAL_SEARCH_ID +EXTRACT_ALL +EXTRACT_ANON_NSPACES +EXTRACT_LOCAL_CLASSES +EXTRACT_LOCAL_METHODS +EXTRACT_PACKAGE +EXTRACT_PRIVATE +EXTRACT_STATIC +EXTRA_PACKAGES +EXTRA_SEARCH_MAPPINGS +EXT_LINKS_IN_WINDOW +FILE_PATTERNS +FILE_VERSION_FILTER +FILTER_PATTERNS +FILTER_SOURCE_FILES +FILTER_SOURCE_PATTERNS +FORCE_LOCAL_INCLUDES +FORMULA_FONTSIZE +FORMULA_TRANSPARENT +FULL_PATH_NAMES +GENERATE_AUTOGEN_DEF +GENERATE_BUGLIST +GENERATE_CHI +GENERATE_DEPRECATEDLIST +GENERATE_DOCBOOK +GENERATE_DOCSET +GENERATE_ECLIPSEHELP +GENERATE_HTML +GENERATE_HTMLHELP +GENERATE_LATEX +GENERATE_LEGEND +GENERATE_MAN +GENERATE_PERLMOD +GENERATE_QHP +GENERATE_RTF +GENERATE_TAGFILE +GENERATE_TESTLIST +GENERATE_TODOLIST +GENERATE_TREEVIEW +GENERATE_XML +GRAPHICAL_HIERARCHY +GROUP_GRAPHS +GROUP_NESTED_COMPOUNDS +# HAVE_DOT +HHC_LOCATION +HIDE_COMPOUND_REFERENCE +HIDE_FRIEND_COMPOUNDS +HIDE_IN_BODY_DOCS +HIDE_SCOPE_NAMES +HIDE_UNDOC_CLASSES +HIDE_UNDOC_MEMBERS +HIDE_UNDOC_RELATIONS +HTML_COLORSTYLE_GAMMA +HTML_COLORSTYLE_HUE +HTML_COLORSTYLE_SAT +HTML_DYNAMIC_SECTIONS +HTML_EXTRA_FILES +HTML_EXTRA_STYLESHEET +HTML_FILE_EXTENSION +HTML_FOOTER +HTML_HEADER +HTML_INDEX_NUM_ENTRIES +HTML_OUTPUT +HTML_STYLESHEET +HTML_TIMESTAMP +IDL_PROPERTY_SUPPORT +IGNORE_PREFIX +IMAGE_PATH +INCLUDED_BY_GRAPH +INCLUDE_FILE_PATTERNS +INCLUDE_GRAPH +INCLUDE_PATH +INHERIT_DOCS +INLINE_GROUPED_CLASSES +INLINE_INFO +INLINE_INHERITED_MEMB +INLINE_SIMPLE_STRUCTS +INLINE_SOURCES +INPUT +INPUT_ENCODING +INPUT_FILTER +INTERACTIVE_SVG +INTERNAL_DOCS +JAVADOC_AUTOBRIEF +LATEX_BATCHMODE +LATEX_BIB_STYLE +LATEX_CMD_NAME +LATEX_EXTRA_FILES +LATEX_EXTRA_STYLESHEET +LATEX_FOOTER +LATEX_HEADER +LATEX_HIDE_INDICES +LATEX_OUTPUT +LATEX_SOURCE_CODE +LATEX_TIMESTAMP +LAYOUT_FILE +LOOKUP_CACHE_SIZE +MACRO_EXPANSION +MAKEINDEX_CMD_NAME +MAN_EXTENSION +MAN_LINKS +MAN_OUTPUT +MAN_SUBDIR +MARKDOWN_SUPPORT +MATHJAX_CODEFILE +MATHJAX_EXTENSIONS +MATHJAX_FORMAT +MATHJAX_RELPATH +MAX_DOT_GRAPH_DEPTH +MAX_INITIALIZER_LINES +MSCFILE_DIRS +MSCGEN_PATH +MULTILINE_CPP_IS_BRIEF +OPTIMIZE_FOR_FORTRAN +OPTIMIZE_OUTPUT_FOR_C +OPTIMIZE_OUTPUT_JAVA +OPTIMIZE_OUTPUT_VHDL +OUTPUT_DIRECTORY +OUTPUT_LANGUAGE +PAPER_TYPE +PDF_HYPERLINKS +PERLMOD_LATEX +PERLMOD_MAKEVAR_PREFIX +PERLMOD_PRETTY +PERL_PATH +PLANTUML_CFG_FILE +PLANTUML_INCLUDE_PATH +PLANTUML_JAR_PATH +PREDEFINED +PROJECT_BRIEF +PROJECT_LOGO +PROJECT_NAME +PROJECT_NUMBER +QCH_FILE +QHG_LOCATION +QHP_CUST_FILTER_ATTRS +QHP_CUST_FILTER_NAME +QHP_NAMESPACE +QHP_SECT_FILTER_ATTRS +QHP_VIRTUAL_FOLDER +QT_AUTOBRIEF +QUIET +RECURSIVE +REFERENCED_BY_RELATION +REFERENCES_LINK_SOURCE +REFERENCES_RELATION +REPEAT_BRIEF +RTF_EXTENSIONS_FILE +RTF_HYPERLINKS +RTF_OUTPUT +RTF_SOURCE_CODE +RTF_STYLESHEET_FILE +SEARCHDATA_FILE +SEARCHENGINE +SEARCHENGINE_URL +SEARCH_INCLUDES +SEPARATE_MEMBER_PAGES +SERVER_BASED_SEARCH +SHORT_NAMES +SHOW_FILES +SHOW_GROUPED_MEMB_INC +SHOW_INCLUDE_FILES +SHOW_NAMESPACES +SHOW_USED_FILES +SIP_SUPPORT +SKIP_FUNCTION_MACROS +SORT_BRIEF_DOCS +SORT_BY_SCOPE_NAME +SORT_GROUP_NAMES +SORT_MEMBERS_CTORS_1ST +SORT_MEMBER_DOCS +SOURCE_BROWSER +SOURCE_TOOLTIPS +STRICT_PROTO_MATCHING +STRIP_CODE_COMMENTS +STRIP_FROM_INC_PATH +STRIP_FROM_PATH +SUBGROUPING +TAB_SIZE +TAGFILES +TCL_SUBST +TEMPLATE_RELATIONS +TOC_EXPAND +TOC_INCLUDE_HEADINGS +TREEVIEW_WIDTH +TYPEDEF_HIDES_STRUCT +UML_LIMIT_NUM_FIELDS +UML_LOOK +USE_HTAGS +USE_MATHJAX +USE_MDFILE_AS_MAINPAGE +USE_PDFLATEX +VERBATIM_HEADERS +WARNINGS +WARN_AS_ERROR +WARN_FORMAT +WARN_IF_DOC_ERROR +WARN_IF_UNDOCUMENTED +WARN_LOGFILE +WARN_NO_PARAMDOC +XML_OUTPUT +XML_PROGRAMLISTING +) + +set(DOXYGEN_CONFIG_FILE "${CMAKE_CURRENT_BINARY_DIR}/doxygen/doxygen.conf" CACHE PATH "Path to generated doxygen configuration file") + +function(add_doxygen_doc) + set(options) + set(oneValueArgs) + set(multiValueArgs DEPENDS ${DOXYGEN_ARGS}) + + cmake_parse_arguments(PARSE "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + + file(WRITE ${DOXYGEN_CONFIG_FILE} "# Auto-generated doxygen configuration file\n") + + foreach(ARG ${DOXYGEN_ARGS}) + if(PARSE_${ARG}) + string(REPLACE ";" " " ARG_VALUE ${PARSE_${ARG}}) + file(APPEND ${DOXYGEN_CONFIG_FILE} "\n${ARG} = ${ARG_VALUE}\n") + endif() + endforeach() + + if(PARSE_OUTPUT_DIRECTORY) + if(NOT EXISTS ${PARSE_OUTPUT_DIRECTORY}) + file(MAKE_DIRECTORY ${PARSE_OUTPUT_DIRECTORY}) + endif() + endif() + + if(DOT_EXECUTABLE) + file(APPEND ${DOXYGEN_CONFIG_FILE} "\nDOT_PATH = \"${DOT_EXECUTABLE}\"\n") + file(APPEND ${DOXYGEN_CONFIG_FILE} "\nHAVE_DOT = YES\n") + else() + file(APPEND ${DOXYGEN_CONFIG_FILE} "\nHAVE_DOT = NO\n") + endif() + + add_custom_target(doxygen + ${DOXYGEN_EXECUTABLE} ${DOXYGEN_CONFIG_FILE} + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + COMMENT "Building documentation with doxygen" + ) + if(PARSE_OUTPUT_DIRECTORY) + clean_doc_output(${PARSE_OUTPUT_DIRECTORY}) + endif() + mark_as_doc(doxygen) + if(PARSE_DEPENDS) + add_dependencies(doxygen ${PARSE_DEPENDS}) + endif() +endfunction() diff --git a/cmake/EnableCompilerWarnings.cmake b/cmake/EnableCompilerWarnings.cmake new file mode 100644 index 0000000000..9f193b2090 --- /dev/null +++ b/cmake/EnableCompilerWarnings.cmake @@ -0,0 +1,110 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# Permission is hereby granted, free of charge, to any person obtaining a copy +# of this software and associated documentation files (the "Software"), to deal +# in the Software without restriction, including without limitation the rights +# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +# copies of the Software, and to permit persons to whom the Software is +# furnished to do so, subject to the following conditions: +# +# The above copyright notice and this permission notice shall be included in all +# copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +# SOFTWARE. +# +################################################################################ +# - Enable warning all for gcc/clang or use /W4 for visual studio + +## Strict warning level +if (MSVC) + # Use the highest warning level for visual studio. + set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /w") + set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /w") + # set(CMAKE_CXX_WARNING_LEVEL 4) + # if (CMAKE_CXX_FLAGS MATCHES "/W[0-4]") + # string(REGEX REPLACE "/W[0-4]" "/W4" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}") + # else () + # set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} /W4") + # endif () + + # set(CMAKE_C_WARNING_LEVEL 4) + # if (CMAKE_C_FLAGS MATCHES "/W[0-4]") + # string(REGEX REPLACE "/W[0-4]" "/W4" CMAKE_C_FLAGS "${CMAKE_C_FLAGS}") + # else () + # set(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} /W4") + # endif () + +else() + foreach(COMPILER C CXX) + set(CMAKE_COMPILER_WARNINGS) + # use -Wall for gcc and clang + list(APPEND CMAKE_COMPILER_WARNINGS + -Wall + -Wextra + -Wcomment + -Wendif-labels + -Wformat + -Winit-self + -Wreturn-type + -Wsequence-point + # Shadow is broken on gcc when using lambdas + # -Wshadow + -Wswitch + -Wtrigraphs + -Wundef + -Wuninitialized + -Wunreachable-code + -Wunused + + -Wno-sign-compare + -Wno-extra-semi-stmt + ) + if (CMAKE_${COMPILER}_COMPILER_ID MATCHES "Clang") + list(APPEND CMAKE_COMPILER_WARNINGS + -Weverything + -Wno-c++98-compat + -Wno-c++98-compat-pedantic + -Wno-conversion + -Wno-double-promotion + -Wno-exit-time-destructors + -Wno-extra-semi + -Wno-float-conversion + -Wno-gnu-anonymous-struct + -Wno-gnu-zero-variadic-macro-arguments + -Wno-missing-prototypes + -Wno-nested-anon-types + -Wno-padded + -Wno-return-std-move-in-c++11 + -Wno-shorten-64-to-32 + -Wno-sign-conversion + -Wno-unknown-warning-option + -Wno-unused-command-line-argument + -Wno-weak-vtables + -Wno-covered-switch-default + ) + else() + if (CMAKE_${COMPILER}_COMPILER_ID MATCHES "GNU" AND ${COMPILER} MATCHES "CXX") + # cmake 3.5.2 does not support >=. + if(NOT CMAKE_CXX_COMPILER_VERSION VERSION_LESS "6.1") + list(APPEND CMAKE_COMPILER_WARNINGS + -Wno-ignored-attributes) + endif() + endif() + list(APPEND CMAKE_COMPILER_WARNINGS + -Wno-missing-field-initializers + -Wno-deprecated-declarations + ) + endif() + add_definitions(${CMAKE_COMPILER_WARNINGS}) + endforeach() +endif () diff --git a/cmake/FindOpenCL.cmake b/cmake/FindOpenCL.cmake new file mode 100644 index 0000000000..07a986226c --- /dev/null +++ b/cmake/FindOpenCL.cmake @@ -0,0 +1,86 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +find_path(OPENCL_INCLUDE_DIRS + NAMES OpenCL/cl.h CL/cl.h + HINTS + ${OPENCL_ROOT}/include + $ENV{AMDAPPSDKROOT}/include + $ENV{CUDA_PATH}/include + PATHS + /usr/include + /usr/local/include + /usr/local/cuda/include + /opt/cuda/include + /opt/rocm/opencl/include + ${CMAKE_INSTALL_PREFIX}/opencl/include + DOC "OpenCL header file path" + ) +mark_as_advanced( OPENCL_INCLUDE_DIRS ) + +if("${CMAKE_SIZEOF_VOID_P}" EQUAL "8") + find_library( OPENCL_LIBRARIES + NAMES OpenCL + HINTS + ${OPENCL_ROOT}/lib + $ENV{AMDAPPSDKROOT}/lib + $ENV{CUDA_PATH}/lib + DOC "OpenCL dynamic library path" + PATH_SUFFIXES x86_64 x64 x86_64/sdk + PATHS + /usr/lib + /usr/local/cuda/lib + /opt/cuda/lib + /opt/rocm/opencl/lib + ${CMAKE_INSTALL_PREFIX}/opencl/lib + ) +else( ) + find_library( OPENCL_LIBRARIES + NAMES OpenCL + HINTS + ${OPENCL_ROOT}/lib + $ENV{AMDAPPSDKROOT}/lib + $ENV{CUDA_PATH}/lib + DOC "OpenCL dynamic library path" + PATH_SUFFIXES x86 Win32 + + PATHS + /usr/lib + /usr/local/cuda/lib + /opt/cuda/lib + ) +endif( ) +mark_as_advanced( OPENCL_LIBRARIES ) + +include( FindPackageHandleStandardArgs ) +find_package_handle_standard_args( OPENCL DEFAULT_MSG OPENCL_LIBRARIES OPENCL_INCLUDE_DIRS ) + +set(OpenCL_FOUND ${OPENCL_FOUND} CACHE INTERNAL "") +set(OpenCL_LIBRARIES ${OPENCL_LIBRARIES} CACHE INTERNAL "") +set(OpenCL_INCLUDE_DIRS ${OPENCL_INCLUDE_DIRS} CACHE INTERNAL "") + +if( NOT OPENCL_FOUND ) + message( STATUS "FindOpenCL looked for libraries named: OpenCL" ) +endif() diff --git a/cmake/MainDoc.cmake b/cmake/MainDoc.cmake new file mode 100644 index 0000000000..8a6cbe98b2 --- /dev/null +++ b/cmake/MainDoc.cmake @@ -0,0 +1,37 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ + +if(NOT TARGET doc) + add_custom_target(doc) +endif() + +function(mark_as_doc) + add_dependencies(doc ${ARGN}) +endfunction() + +function(clean_doc_output DIR) + set_property(DIRECTORY APPEND PROPERTY ADDITIONAL_MAKE_CLEAN_FILES ${DIR}) +endfunction() diff --git a/cmake/SphinxDoc.cmake b/cmake/SphinxDoc.cmake new file mode 100644 index 0000000000..11aa533b48 --- /dev/null +++ b/cmake/SphinxDoc.cmake @@ -0,0 +1,90 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +include(CMakeParseArguments) +include(MainDoc) +include(DoxygenDoc) + +find_program(SPHINX_EXECUTABLE NAMES sphinx-build + HINTS + $ENV{SPHINX_DIR} + PATH_SUFFIXES bin + DOC "Sphinx documentation generator" +) + +mark_as_advanced(SPHINX_EXECUTABLE) + +set(BINARY_BUILD_DIR "${CMAKE_CURRENT_BINARY_DIR}/sphinx/_build") + +# Sphinx cache with pickled ReST documents +set(SPHINX_CACHE_DIR "${CMAKE_CURRENT_BINARY_DIR}/sphinx/_doctrees") + +# HTML output directory +set(SPHINX_DEFAULT_HTML_DIR "${CMAKE_CURRENT_BINARY_DIR}/sphinx/html") +function(add_sphinx_doc SRC_DIR) + set(options) + set(oneValueArgs BUILDER OUTPUT_DIR) + set(multiValueArgs DEPENDS VARS TEMPLATE_VARS) + + cmake_parse_arguments(PARSE "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGN}) + + string(TOUPPER ${PARSE_BUILDER} BUILDER) + + set(ADDITIONAL_ARGS) + foreach(VAR ${PARSE_VARS}) + list(APPEND ADDITIONAL_ARGS -D ${VAR}) + endforeach() + foreach(VAR ${PARSE_TEMPLATE_VARS}) + list(APPEND ADDITIONAL_ARGS -A ${VAR}) + endforeach() + + if(PARSE_OUTPUT_DIR) + get_filename_component(OUTPUT_DIR ${PARSE_OUTPUT_DIR} ABSOLUTE) + set(SPHINX_${BUILDER}_DIR ${OUTPUT_DIR} CACHE PATH "Path to ${PARSE_BUILDER} output") + else() + set(SPHINX_${BUILDER}_DIR "${CMAKE_CURRENT_BINARY_DIR}/sphinx/${PARSE_BUILDER}" CACHE PATH "Path to ${PARSE_BUILDER} output") + endif() + + add_custom_target(sphinx-${BUILDER} + ${SPHINX_EXECUTABLE} + -b ${PARSE_BUILDER} + -d "${SPHINX_CACHE_DIR}" + ${ADDITIONAL_ARGS} + "${SRC_DIR}" + "${SPHINX_${BUILDER}_DIR}" + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR} + COMMENT "Building ${PARSE_BUILDER} documentation with Sphinx" + ) + clean_doc_output(${SPHINX_${BUILDER}_DIR}) + clean_doc_output(${SPHINX_CACHE_DIR}) + clean_doc_output(${BINARY_BUILD_DIR}) + mark_as_doc(sphinx-${BUILDER}) + if(PARSE_DEPENDS) + add_dependencies(sphinx-${BUILDER} ${PARSE_DEPENDS}) + endif() + +endfunction() + + diff --git a/cmake/TargetFlags.cmake b/cmake/TargetFlags.cmake new file mode 100644 index 0000000000..4f83fb5d39 --- /dev/null +++ b/cmake/TargetFlags.cmake @@ -0,0 +1,50 @@ + +function(get_target_property2 VAR TARGET PROPERTY) + get_target_property(_pflags ${TARGET} ${PROPERTY}) + if(_pflags) + set(${VAR} ${_pflags} PARENT_SCOPE) + else() + set(${VAR} "" PARENT_SCOPE) + endif() +endfunction() + + +macro(append_flags FLAGS TARGET PROPERTY PREFIX) + get_target_property2(_pflags ${TARGET} ${PROPERTY}) + foreach(FLAG ${_pflags}) + if(TARGET ${FLAG}) + target_flags(_pflags2 ${FLAG}) + string(APPEND ${FLAGS} " ${_pflags2}") + else() + string(APPEND ${FLAGS} " ${PREFIX}${FLAG}") + endif() + endforeach() +endmacro() + +macro(append_link_flags FLAGS TARGET PROPERTY) + get_target_property2(_pflags ${TARGET} ${PROPERTY}) + foreach(FLAG ${_pflags}) + if(TARGET ${FLAG}) + target_flags(_pflags2 ${FLAG}) + string(APPEND ${FLAGS} " ${_pflags2}") + elseif(FLAG MATCHES "^-.*") + string(APPEND ${FLAGS} " ${FLAG}") + elseif(EXISTS ${FLAG}) + string(APPEND ${FLAGS} " ${FLAG}") + else() + string(APPEND ${FLAGS} " -l${FLAG}") + endif() + endforeach() +endmacro() + +function(target_flags FLAGS TARGET) + set(_flags) + append_flags(_flags ${TARGET} "INTERFACE_COMPILE_OPTIONS" "") + append_flags(_flags ${TARGET} "INTERFACE_COMPILE_DEFINITIONS" "-D") + append_flags(_flags ${TARGET} "INTERFACE_INCLUDE_DIRECTORIES" "-isystem ") + append_flags(_flags ${TARGET} "INTERFACE_LINK_DIRECTORIES" "-L ") + append_flags(_flags ${TARGET} "INTERFACE_LINK_OPTIONS" "") + append_link_flags(_flags ${TARGET} "INTERFACE_LINK_LIBRARIES" "") + # message("_flags: ${_flags}") + set(${FLAGS} ${_flags} PARENT_SCOPE) +endfunction() diff --git a/cmake/hip-config.cmake b/cmake/hip-config.cmake new file mode 100644 index 0000000000..279de67bba --- /dev/null +++ b/cmake/hip-config.cmake @@ -0,0 +1,122 @@ +get_filename_component(PACKAGE_PREFIX_DIR "${CMAKE_CURRENT_LIST_DIR}/../../../" ABSOLUTE) + +macro(set_and_check _var _file) + set(${_var} "${_file}") + if(NOT EXISTS "${_file}") + message(FATAL_ERROR "File or directory ${_file} referenced by variable ${_var} does not exist !") + endif() +endmacro() + +macro(check_required_components _NAME) + foreach(comp ${${_NAME}_FIND_COMPONENTS}) + if(NOT ${_NAME}_${comp}_FOUND) + if(${_NAME}_FIND_REQUIRED_${comp}) + set(${_NAME}_FOUND FALSE) + endif() + endif() + endforeach() +endmacro() + +#################################################################################### + +include(CMakeFindDependencyMacro OPTIONAL RESULT_VARIABLE _CMakeFindDependencyMacro_FOUND) +if (NOT _CMakeFindDependencyMacro_FOUND) + macro(find_dependency dep) + if (NOT ${dep}_FOUND) + set(cmake_fd_version) + if (${ARGC} GREATER 1) + set(cmake_fd_version ${ARGV1}) + endif() + set(cmake_fd_exact_arg) + if(${CMAKE_FIND_PACKAGE_NAME}_FIND_VERSION_EXACT) + set(cmake_fd_exact_arg EXACT) + endif() + set(cmake_fd_quiet_arg) + if(${CMAKE_FIND_PACKAGE_NAME}_FIND_QUIETLY) + set(cmake_fd_quiet_arg QUIET) + endif() + set(cmake_fd_required_arg) + if(${CMAKE_FIND_PACKAGE_NAME}_FIND_REQUIRED) + set(cmake_fd_required_arg REQUIRED) + endif() + find_package(${dep} ${cmake_fd_version} + ${cmake_fd_exact_arg} + ${cmake_fd_quiet_arg} + ${cmake_fd_required_arg} + ) + string(TOUPPER ${dep} cmake_dep_upper) + if (NOT ${dep}_FOUND AND NOT ${cmake_dep_upper}_FOUND) + set(${CMAKE_FIND_PACKAGE_NAME}_NOT_FOUND_MESSAGE "${CMAKE_FIND_PACKAGE_NAME} could not be found because dependency ${dep} could not be found.") + set(${CMAKE_FIND_PACKAGE_NAME}_FOUND False) + return() + endif() + set(cmake_fd_version) + set(cmake_fd_required_arg) + set(cmake_fd_quiet_arg) + set(cmake_fd_exact_arg) + endif() + endmacro() +endif() + +set(HIP_COMPILER "clang") +set(HIP_RUNTIME "VDI") + +set_and_check( hip_INCLUDE_DIR "${PACKAGE_PREFIX_DIR}/include" ) +set_and_check( hip_INCLUDE_DIRS "${hip_INCLUDE_DIR}" ) +set_and_check( hip_LIB_INSTALL_DIR "${PACKAGE_PREFIX_DIR}/lib" ) +set_and_check( hip_BIN_INSTALL_DIR "${PACKAGE_PREFIX_DIR}/bin" ) + +set_and_check(hip_HIPCC_EXECUTABLE "${hip_BIN_INSTALL_DIR}/hipcc") +set_and_check(hip_HIPCONFIG_EXECUTABLE "${hip_BIN_INSTALL_DIR}/hipconfig") + +get_filename_component(HIP_CLANG_ROOT "${CMAKE_CXX_COMPILER}" PATH) +get_filename_component(HIP_CLANG_ROOT "${HIP_CLANG_ROOT}" PATH) +file(GLOB HIP_CLANG_INCLUDE_SEARCH_PATHS ${HIP_CLANG_ROOT}/lib/clang/*/include) +find_path(HIP_CLANG_INCLUDE_PATH stddef.h + HINTS + ${HIP_CLANG_INCLUDE_SEARCH_PATHS} + NO_DEFAULT_PATH) + +find_dependency(amd_comgr) +find_dependency(AMDDeviceLibs) +set(AMDGPU_TARGETS "gfx900;gfx906" CACHE STRING "AMD GPU targets to compile for") +set(GPU_TARGETS "${AMDGPU_TARGETS}" CACHE STRING "GPU targets to compile for") + +include( "${CMAKE_CURRENT_LIST_DIR}/hip-targets.cmake" ) + +set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_COMPILE_OPTIONS -x hip --hip-device-lib-path=${AMD_DEVICE_LIBS_PREFIX}/lib +) + +set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_LINK_LIBRARIES --hip-device-lib-path=${AMD_DEVICE_LIBS_PREFIX}/lib --hip-link +) + +set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_INCLUDE_DIRECTORIES "${HIP_CLANG_INCLUDE_PATH}" +) + +set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_SYSTEM_INCLUDE_DIRECTORIES "${HIP_CLANG_INCLUDE_PATH}" +) + +foreach(GPU_TARGET ${GPU_TARGETS}) + set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_COMPILE_OPTIONS "--cuda-gpu-arch=${GPU_TARGET}" + ) + set_property(TARGET hip::device APPEND PROPERTY + INTERFACE_LINK_LIBRARIES "--cuda-gpu-arch=${GPU_TARGET}" + ) +endforeach() + +set( hip_LIBRARIES hip::host hip::device) +set( hip_LIBRARY ${hip_LIBRARIES}) + +set(HIP_INCLUDE_DIR ${hip_INCLUDE_DIR}) +set(HIP_INCLUDE_DIRS ${hip_INCLUDE_DIRS}) +set(HIP_LIB_INSTALL_DIR ${hip_LIB_INSTALL_DIR}) +set(HIP_BIN_INSTALL_DIR ${hip_BIN_INSTALL_DIR}) +set(HIP_LIBRARIES ${hip_LIBRARIES}) +set(HIP_LIBRARY ${hip_LIBRARY}) +set(HIP_HIPCC_EXECUTABLE ${hip_HIPCC_EXECUTABLE}) +set(HIP_HIPCONFIG_EXECUTABLE ${hip_HIPCONFIG_EXECUTABLE}) diff --git a/cmake/mingw-toolchain.cmake b/cmake/mingw-toolchain.cmake new file mode 100644 index 0000000000..62d387da6a --- /dev/null +++ b/cmake/mingw-toolchain.cmake @@ -0,0 +1,50 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2017 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +set(TOOLCHAIN_PREFIX x86_64-w64-mingw32) +set(CMAKE_SYSTEM_NAME Windows) + +# cross compilers to use for C and C++ +set(CMAKE_C_COMPILER ${TOOLCHAIN_PREFIX}-gcc) +set(CMAKE_CXX_COMPILER ${TOOLCHAIN_PREFIX}-g++) +set(CMAKE_RC_COMPILER ${TOOLCHAIN_PREFIX}-windres) + +# target environment on the build host system +# set 1st to dir with the cross compiler's C/C++ headers/libs +# set 2nd to dir containing personal cross development headers/libs +set(CMAKE_FIND_ROOT_PATH /usr/${TOOLCHAIN_PREFIX} /usr/local/${TOOLCHAIN_PREFIX}) + +# modify default behavior of FIND_XXX() commands to +# search for headers/libs in the target environment and +# search for programs in the build host environment +set(CMAKE_FIND_ROOT_PATH_MODE_PROGRAM NEVER) +set(CMAKE_FIND_ROOT_PATH_MODE_PACKAGE ONLY) +set(CMAKE_FIND_ROOT_PATH_MODE_LIBRARY ONLY) +set(CMAKE_FIND_ROOT_PATH_MODE_INCLUDE ONLY) + +include_directories(/usr/local/${TOOLCHAIN_PREFIX}/include) +set(CMAKE_WINDOWS_EXPORT_ALL_SYMBOLS On CACHE BOOL "Export windows symbols") + +set(CMAKE_CXX_FLAGS "$ENV{CXXFLAGS} -static-libgcc -static-libstdc++" CACHE STRING "") diff --git a/cmake/rocm-path.cmake b/cmake/rocm-path.cmake new file mode 100644 index 0000000000..d0ae6c8883 --- /dev/null +++ b/cmake/rocm-path.cmake @@ -0,0 +1,29 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2019 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ + +# Find the compiler path when building rocBLAS +list(APPEND CMAKE_PREFIX_PATH /opt/rocm) + diff --git a/install_deps.cmake b/install_deps.cmake new file mode 100755 index 0000000000..e403bd47c3 --- /dev/null +++ b/install_deps.cmake @@ -0,0 +1,90 @@ +#!/usr/bin/cmake -P + +set(ARGS) +foreach(i RANGE 3 ${CMAKE_ARGC}) + list(APPEND ARGS ${CMAKE_ARGV${i}}) +endforeach() + +include(CMakeParseArguments) + +set(options help --minimum) +set(oneValueArgs --prefix) +set(multiValueArgs) + +cmake_parse_arguments(PARSE "${options}" "${oneValueArgs}" "${multiValueArgs}" ${ARGS}) + +if(PARSE_help) +message("Usage: install_deps.cmake [options] [cmake-args]") +message("") +message("Options:") +message(" --prefix Set the prefix to install the dependencies.") +message("") +message("Commands:") +message(" help Show this message and exit.") +message("") +message(" --minimum Install minimum dependencies.") +message("") +return() +endif() + +set(_PREFIX /usr/local) +if(PARSE_--prefix) + set(_PREFIX ${PARSE_--prefix}) +endif() + +get_filename_component(PREFIX ${_PREFIX} ABSOLUTE) + +find_package(CMakeGet QUIET PATHS ${PREFIX}) + +if(NOT CMakeGet_FOUND) + set(FILENAME ${PREFIX}/tmp/cmake-get-install.cmake) + file(DOWNLOAD https://raw.githubusercontent.com/pfultz2/cmake-get/master/install.cmake ${FILENAME} STATUS RESULT_LIST) + list(GET RESULT_LIST 0 RESULT) + list(GET RESULT_LIST 1 RESULT_MESSAGE) + if(NOT RESULT EQUAL 0) + message(FATAL_ERROR "Download for install.cmake failed: ${RESULT_MESSAGE}") + endif() + execute_process(COMMAND ${CMAKE_COMMAND} -P ${FILENAME} ${PREFIX}) + file(REMOVE ${FILENAME}) + find_package(CMakeGet REQUIRED PATHS ${PREFIX}) +endif() + +# Set compiler to hcc if not set +if(NOT DEFINED ENV{CXX} AND NOT DEFINED CMAKE_CXX_COMPILER AND NOT DEFINED CMAKE_TOOLCHAIN_FILE) + find_program(HCC hcc + PATHS + /opt/rocm/hcc + /opt/rocm + PATH_SUFFIXES + bin + ) + if(HCC) + set(ENV{CXX} ${HCC}) + else() + message(STATUS "Cannot find hcc") + find_program(CLANGXX clang++ + PATHS + /opt/rocm/llvm + /opt/rocm + PATH_SUFFIXES + bin + ) + if(CLANGXX) + set(ENV{CXX} ${CLANGXX}) + else() + message(FATAL_ERROR "Cannot find clang++") + endif() + endif() +endif() + +cmake_get(pfultz2/rocm-recipes PREFIX ${PREFIX} CMAKE_ARGS ${PARSE_UNPARSED_ARGUMENTS}) + +if(PARSE_--minimum) + message(STATUS "MIOpen minimum dependency install.") + set(REQFILE ${CMAKE_CURRENT_LIST_DIR}/min-requirements.txt) +else() + message(STATUS "MIOpen normal dependency install.") + set(REQFILE ${CMAKE_CURRENT_LIST_DIR}/requirements.txt) +endif() + +cmake_get_from(${REQFILE} PREFIX ${PREFIX} CMAKE_ARGS -DCMAKE_INSTALL_RPATH=${PREFIX}/lib ${PARSE_UNPARSED_ARGUMENTS}) diff --git a/requirements.txt b/requirements.txt new file mode 100644 index 0000000000..1e6a738892 --- /dev/null +++ b/requirements.txt @@ -0,0 +1,5 @@ +RadeonOpenCompute/rocm-cmake@cdd0f632b3a65bd4411593bb827eb664e25c80bc --build +# ROCmSoftwarePlatform/MIOpen@9b2d37f9f1e4b5492ef8256cf8168363ca5fd2da +nlohmann/json +#ROCmSoftwarePlatform/rocBLAS@9790a8658341bc665c11c311129ad0dfc533d5c4 + diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt new file mode 100644 index 0000000000..84875c15c5 --- /dev/null +++ b/src/CMakeLists.txt @@ -0,0 +1,50 @@ +################################################################################ +# +# MIT License +# +# Copyright (c) 2020 Advanced Micro Devices, Inc. +# +# 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. +# +################################################################################ +cmake_minimum_required( VERSION 2.8.12 ) +list(APPEND CMAKE_PREFIX_PATH /opt/rocm /opt/rocm/hip /opt/rocm/hcc /opt/rocm/opencl) +find_package(miopen) + +find_package(Threads REQUIRED) + +configure_file("${PROJECT_SOURCE_DIR}/src/include/config.h.in" "${PROJECT_BINARY_DIR}/src/include/config.h") + +include_directories(include "${PROJECT_BINARY_DIR}/src/include") +add_executable(fin main.cpp fin.cpp base64.cpp) +target_compile_definitions( fin PRIVATE -D__HIP_PLATFORM_HCC__=1 ) +target_link_libraries(fin MIOpen ${Boost_LIBRARIES}) +target_link_libraries(fin ${CMAKE_THREAD_LIBS_INIT}) +if(rocblas_FOUND) + target_link_libraries( fin $ ) + # target_link_libraries( fin PRIVATE roc::rocblas ) +endif() + +# Cmake does not add flags correctly for gcc +if(CMAKE_CXX_COMPILER_ID MATCHES "GNU") + set_target_properties(fin PROPERTIES COMPILE_FLAGS -pthread LINK_FLAGS -pthread) +endif() +install(TARGETS fin + OPTIONAL + RUNTIME DESTINATION bin) diff --git a/src/base64.cpp b/src/base64.cpp new file mode 100644 index 0000000000..6e88a96a74 --- /dev/null +++ b/src/base64.cpp @@ -0,0 +1,254 @@ +/* + base64.cpp and base64.h + + base64 encoding and decoding with C++. + More information at + https://renenyffenegger.ch/notes/development/Base64/Encoding-and-decoding-base-64-with-cpp + + Version: 2.rc.07 (release candidate) + + Copyright (C) 2004-2017, 2020 René Nyffenegger + + This source code is provided 'as-is', without any express or implied + warranty. In no event will the author be held liable for any damages + arising from the use of this software. + + Permission is granted to anyone to use this software for any purpose, + including commercial applications, and to alter it and redistribute it + freely, subject to the following restrictions: + + 1. The origin of this source code must not be misrepresented; you must not + claim that you wrote the original source code. If you use this source code + in a product, an acknowledgment in the product documentation would be + appreciated but is not required. + + 2. Altered source versions must be plainly marked as such, and must not be + misrepresented as being the original source code. + + 3. This notice may not be removed or altered from any source distribution. + + René Nyffenegger rene.nyffenegger@adp-gmbh.ch + +*/ + +#include "base64.hpp" + +#include +#include + + // + // Depending on the url parameter in base64_chars, one of + // two sets of base64 characters needs to be chosen. + // They differ in their last two characters. + // +static const char* base64_chars[2] = { + "ABCDEFGHIJKLMNOPQRSTUVWXYZ" + "abcdefghijklmnopqrstuvwxyz" + "0123456789" + "+/", + + "ABCDEFGHIJKLMNOPQRSTUVWXYZ" + "abcdefghijklmnopqrstuvwxyz" + "0123456789" + "-_"}; + +static unsigned int pos_of_char(const unsigned char chr) { + // + // Return the position of chr within base64_encode() + // + + if (chr >= 'A' && chr <= 'Z') return chr - 'A'; + else if (chr >= 'a' && chr <= 'z') return chr - 'a' + ('Z' - 'A') + 1; + else if (chr >= '0' && chr <= '9') return chr - '0' + ('Z' - 'A') + ('z' - 'a') + 2; + else if (chr == '+' || chr == '-') return 62; // Be liberal with input and accept both url ('-') and non-url ('+') base 64 characters ( + else if (chr == '/' || chr == '_') return 63; // Ditto for '/' and '_' + else + // + // 2020-10-23: Throw std::exception rather than const char* + //(Pablo Martin-Gomez, https://github.com/Bouska) + // + throw std::runtime_error("Input is not valid base64-encoded data."); +} + +static std::string insert_linebreaks(std::string str, size_t distance) { + // + // Provided by https://github.com/JomaCorpFX, adapted by me. + // + if (!str.length()) { + return ""; + } + + size_t pos = distance; + + while (pos < str.size()) { + str.insert(pos, "\n"); + pos += distance + 1; + } + + return str; +} + +template +static std::string encode_with_line_breaks(String s) { + return insert_linebreaks(base64_encode(s, false), line_length); +} + +template +static std::string encode_pem(String s) { + return encode_with_line_breaks(s); +} + +template +static std::string encode_mime(String s) { + return encode_with_line_breaks(s); +} + +template +static std::string encode(String s, bool url) { + return base64_encode(reinterpret_cast(s.data()), s.length(), url); +} + +std::string base64_encode(unsigned char const* bytes_to_encode, size_t in_len, bool url) { + + size_t len_encoded = (in_len +2) / 3 * 4; + + unsigned char trailing_char = url ? '.' : '='; + + // + // Choose set of base64 characters. They differ + // for the last two positions, depending on the url + // parameter. + // A bool (as is the parameter url) is guaranteed + // to evaluate to either 0 or 1 in C++ therefore, + // the correct character set is chosen by subscripting + // base64_chars with url. + // + const char* base64_chars_ = base64_chars[url]; + + std::string ret; + ret.reserve(len_encoded); + + unsigned int pos = 0; + + while (pos < in_len) { + ret.push_back(base64_chars_[(bytes_to_encode[pos + 0] & 0xfc) >> 2]); + + if (pos+1 < in_len) { + ret.push_back(base64_chars_[((bytes_to_encode[pos + 0] & 0x03) << 4) + ((bytes_to_encode[pos + 1] & 0xf0) >> 4)]); + + if (pos+2 < in_len) { + ret.push_back(base64_chars_[((bytes_to_encode[pos + 1] & 0x0f) << 2) + ((bytes_to_encode[pos + 2] & 0xc0) >> 6)]); + ret.push_back(base64_chars_[ bytes_to_encode[pos + 2] & 0x3f]); + } + else { + ret.push_back(base64_chars_[(bytes_to_encode[pos + 1] & 0x0f) << 2]); + ret.push_back(trailing_char); + } + } + else { + + ret.push_back(base64_chars_[(bytes_to_encode[pos + 0] & 0x03) << 4]); + ret.push_back(trailing_char); + ret.push_back(trailing_char); + } + + pos += 3; + } + + + return ret; +} + +template +static std::string decode(String encoded_string, bool remove_linebreaks) { + // + // decode(…) is templated so that it can be used with String = const std::string& + // or std::string_view (requires at least C++17) + // + + if (encoded_string.empty()) return std::string(); + + if (remove_linebreaks) { + + std::string copy(encoded_string); + + copy.erase(std::remove(copy.begin(), copy.end(), '\n'), copy.end()); + + return base64_decode(copy, false); + } + + size_t length_of_string = encoded_string.length(); + size_t pos = 0; + + // + // The approximate length (bytes) of the decoded string might be one or + // two bytes smaller, depending on the amount of trailing equal signs + // in the encoded string. This approximation is needed to reserve + // enough space in the string to be returned. + // + size_t approx_length_of_decoded_string = length_of_string / 4 * 3; + std::string ret; + ret.reserve(approx_length_of_decoded_string); + + while (pos < length_of_string) { + + unsigned int pos_of_char_1 = pos_of_char(encoded_string[pos+1] ); + + ret.push_back(static_cast( ( (pos_of_char(encoded_string[pos+0]) ) << 2 ) + ( (pos_of_char_1 & 0x30 ) >> 4))); + + if (encoded_string[pos+2] != '=' && encoded_string[pos+2] != '.') { // accept URL-safe base 64 strings, too, so check for '.' also. + + unsigned int pos_of_char_2 = pos_of_char(encoded_string[pos+2] ); + ret.push_back(static_cast( (( pos_of_char_1 & 0x0f) << 4) + (( pos_of_char_2 & 0x3c) >> 2))); + + if (encoded_string[pos+3] != '=' && encoded_string[pos+3] != '.') { + ret.push_back(static_cast( ( (pos_of_char_2 & 0x03 ) << 6 ) + pos_of_char(encoded_string[pos+3]) )); + } + } + + pos += 4; + } + + return ret; +} + +std::string base64_decode(std::string const& s, bool remove_linebreaks) { + return decode(s, remove_linebreaks); +} + +std::string base64_encode(std::string const& s, bool url) { + return encode(s, url); +} + +std::string base64_encode_pem (std::string const& s) { + return encode_pem(s); +} + +std::string base64_encode_mime(std::string const& s) { + return encode_mime(s); +} + +#if __cplusplus >= 201703L +// +// Interface with std::string_view rather than const std::string& +// Requires C++17 +// Provided by Yannic Bonenberger (https://github.com/Yannic) +// + +std::string base64_encode(std::string_view s, bool url) { + return encode(s, url); +} + +std::string base64_encode_pem(std::string_view s) { + return encode_pem(s); +} + +std::string base64_encode_mime(std::string_view s) { + return encode_mime(s); +} + +std::string base64_decode(std::string_view s, bool remove_linebreaks) { + return decode(s, remove_linebreaks); +} + +#endif // __cplusplus >= 201703L diff --git a/src/fin.cpp b/src/fin.cpp new file mode 100644 index 0000000000..ef49d25fd9 --- /dev/null +++ b/src/fin.cpp @@ -0,0 +1,60 @@ +#include "fin.hpp" + +namespace fin { + +template <> +miopenDataType_t GetDataType() +{ + return miopenInt8; +} +template <> +miopenDataType_t GetDataType() +{ + return miopenFloat; +} +template <> +miopenDataType_t GetDataType() +{ + return miopenHalf; +} +template <> +miopenDataType_t GetDataType() +{ + return miopenBFloat16; +} +[[gnu::noreturn]] void Fin::Usage() +{ + std::cout << "Usage: ./MIOpenFin *base_arg* *other_args*\n"; + std::cout << "Supported Base Arguments: conv[fp16][bfp16]\n"; + exit(0); +} +void PadBufferSize(size_t& sz, int datatype_sz) +{ + size_t page_sz = (2 * 1024 * 1024) / datatype_sz; + if(sz % page_sz != 0) + { + sz = ((sz + page_sz) / page_sz) * page_sz; + } +} + +std::string Fin::ParseBaseArg(const int argc, const char* argv[]) +{ + if(argc < 2) + { + std::cout << "Invalid Number of Input Arguments\n"; + Usage(); + } + + std::string arg = argv[1]; + + if(arg != "conv" && arg != "convfp16" && arg != "convbfp16") + { + std::cout << "Invalid Base Input Argument\n"; + Usage(); + } + else if(arg == "-h" || arg == "--help" || arg == "-?") + Usage(); + else + return arg; +} +} // namespace fin diff --git a/src/include/base64.hpp b/src/include/base64.hpp new file mode 100644 index 0000000000..09f75a8a33 --- /dev/null +++ b/src/include/base64.hpp @@ -0,0 +1,35 @@ +// +// base64 encoding and decoding with C++. +// Version: 2.rc.07 (release candidate) +// + +#ifndef BASE64_H_C0CE2A47_D10E_42C9_A27C_C883944E704A +#define BASE64_H_C0CE2A47_D10E_42C9_A27C_C883944E704A + +#include + +#if __cplusplus >= 201703L +#include +#endif // __cplusplus >= 201703L + +std::string base64_encode (std::string const& s, bool url = false); +std::string base64_encode_pem (std::string const& s); +std::string base64_encode_mime(std::string const& s); + +std::string base64_decode(std::string const& s, bool remove_linebreaks = false); +std::string base64_encode(unsigned char const*, size_t len, bool url = false); + +#if __cplusplus >= 201703L +// +// Interface with std::string_view rather than const std::string& +// Requires C++17 +// Provided by Yannic Bonenberger (https://github.com/Yannic) +// +std::string base64_encode (std::string_view s, bool url = false); +std::string base64_encode_pem (std::string_view s); +std::string base64_encode_mime(std::string_view s); + +std::string base64_decode(std::string_view s, bool remove_linebreaks = false); +#endif // __cplusplus >= 201703L + +#endif /* BASE64_H_C0CE2A47_D10E_42C9_A27C_C883944E704A */ diff --git a/src/include/config.h.in b/src/include/config.h.in new file mode 100644 index 0000000000..b557c86394 --- /dev/null +++ b/src/include/config.h.in @@ -0,0 +1,32 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2017 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#ifndef GUARD_FIN_CONFIG_H_IN +#define GUARD_FIN_CONFIG_H_IN + +#cmakedefine01 FIN_BACKEND_OPENCL +#cmakedefine01 FIN_BACKEND_HIP + +#endif diff --git a/src/include/conv_fin.hpp b/src/include/conv_fin.hpp new file mode 100644 index 0000000000..7ca262e1da --- /dev/null +++ b/src/include/conv_fin.hpp @@ -0,0 +1,1307 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2020 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#ifndef GUARD_CONV_FIN_HPP +#define GUARD_CONV_FIN_HPP + +#include "base64.hpp" +#include "error.hpp" +#include "fin.hpp" +#include "random.hpp" +#include "tensor.hpp" + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#if MIOPEN_MODE_NOGPU +#include +#include +#endif + +#include +#include + +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include +#include + +namespace fin { + +using json = nlohmann::json; +// TODO: Create a config class to encapsulate config +// related code, such as checking direction etc +template +class ConvFin : public Fin +{ + public: + ConvFin() : Fin() {} + ConvFin(json _job) : Fin(), job(_job) + { + VerifyDevProps(); + command = _job["config"]; + command["bias"] = 0; + // timing is always enabled + is_fwd = (_job["direction"].get() == 0 || _job["direction"].get() & 1); + is_bwd = (_job["direction"].get() == 0 || _job["direction"].get() & 2); + is_wrw = (_job["direction"].get() == 0 || _job["direction"].get() & 4); + SetConvDescriptor(); + // workspace_dev = nullptr; // TODO: replaced with a tensor class + // the variable name is implementation dependent, checking size instead + } + void VerifyDevProps() + { + std::cerr << "Verifying device properties" << std::endl; + std::string arch = job["arch"]; + arch = arch.substr(0, arch.find(':')); + const size_t num_cu = job["num_cu"]; + if(arch == "gfx900") + { + assert(num_cu == 56 || num_cu == 64); + } + else if(arch == "gfx906") + { + assert(num_cu == 60 || num_cu == 64); + } + else if(arch == "gfx908") + { + assert(num_cu == 120); + } + else if(arch == "gfx1030") + { + assert(num_cu == 72 || num_cu == 36); + } + else + throw std::runtime_error("Invalid Arch Name"); + } + + // Getters and setters + std::vector GetInputTensorLengths(); + std::vector GetWeightTensorLengths(); + std::vector GetBiasTensorLengths(); + int SetConvDescriptor(); + std::vector GetOutputTensorLengths() const; + miopenDataType_t GetOutputType() const + { + return (data_type == miopenInt8 || data_type == miopenInt8x4) ? miopenFloat : data_type; + } + miopen::conv::Direction GetDirection() const; + + int ProcessStep(const std::string& step_name) override; + + // Steps + int AllocateBuffers(); + int CalcWorkspace(); + int FillBuffers(); + int CopyToDevice(); + int CopyFromDevice(); + int RunGPU(); + int TestApplicability(); + int GetandSetData(); + int GetSolverList(); + int MIOpenFind(); + int MIOpenFindCompile(); + int MIOpenFindEval(); + + // Utility functions + bool IsInputTensorTransform() const; + void InitNoGpuHandle(miopen::Handle& handle); + json command; + json job; + + tensor inputTensor; + tensor inputTensor_vect4; + tensor outputTensor; + tensor weightTensor; + tensor weightTensor_vect4; + tensor biasTensor; + tensor workspace; + miopen::ConvolutionDescriptor convDesc; + + bool wrw_allowed = 0, bwd_allowed = 0, forward_allowed = 1; + bool is_fwd = true; + bool is_bwd = false; + bool is_wrw = false; // TODO: check redundancy with above + int immediate_solution = 0; + std::vector steps_processed; +}; + +template +miopen::conv::Direction ConvFin::GetDirection() const +{ + return is_fwd ? miopen::conv::Direction::Forward + : (is_bwd ? miopen::conv::Direction::BackwardData + : miopen::conv::Direction::BackwardWeights); +} + +template +void ConvFin::InitNoGpuHandle(miopen::Handle& handle) +{ +#if MIOPEN_MODE_NOGPU + handle.impl->device_name = job["arch"]; + handle.impl->num_cu = job["num_cu"]; + handle.impl->max_mem_alloc_size = 32UL * 1024 * 1024 * 1024; // 32 GB + handle.impl->global_mem_size = 32UL * 1024 * 1024 * 1024; + handle.impl->target_properties.Init(&handle); +#else + std::ignore = handle; +#endif +} +template +int ConvFin::MIOpenFindCompile() +{ + std::cerr << "MIOpenFindCompile" << std::endl; + std::cerr << "Processing command: " << command << std::endl; +#if MIOPEN_MODE_NOGPU + GetandSetData(); +#else + throw std::runtime_error( + "Unable to perform MIOpenFindCompile MIOpen was not compiled using HIPNOGPU backend"); +#endif + const auto conv_dir = GetDirection(); + const miopen::ProblemDescription problem( + inputTensor.desc, weightTensor.desc, outputTensor.desc, convDesc, conv_dir); + GetHandle().EnableProfiling(true); + auto ctx = miopen::ConvolutionContext{problem}; + auto handle = miopen::Handle{}; +#if MIOPEN_MODE_NOGPU + InitNoGpuHandle(handle); +#else + throw std::runtime_error("MIOpen needs to be compiled with the NOGPU backend " + "for MIOpenFindCompile"); +#endif + ctx.SetStream(&handle); + ctx.DetectRocm(); + ctx.SetupFloats(); + + const auto network_config = ctx.BuildConfKey(); + const bool is_winograd_only = convDesc.IsWinograd3x3SupportedAndFast(ctx); + output["is_winograd_only"] = is_winograd_only; + output["network_config"] = network_config; + std::ostringstream ss; + problem.Serialize(ss); + output["db_key"] = ss.str(); + + auto db = GetDb(ctx); + json find_result; + const auto& tgt_props = handle.GetTargetProperties(); + const std::string arch = tgt_props.Name(); + const size_t num_cu = handle.GetMaxComputeUnits(); + std::cerr << "Job Arch: " << job["arch"] << ": Handle Arch: " << arch << std::endl; + std::cerr << "Job Num CU: " << job["num_cu"] << ": Handle Num Cu: " << num_cu << std::endl; + // since applicability has been run, the solver list should come from Tuna + for(const auto& solver_id : + miopen::solver::GetSolversByPrimitive(miopen::solver::Primitive::Convolution)) + { + json res_item; + // remove the user db files + boost::filesystem::remove_all(miopen::GetCachePath(false)); + auto process_solver = [&]() -> bool { + std::cerr << "Processing Solver: " << solver_id.ToString() << std::endl; + res_item["solver_id"] = solver_id.ToString(); + if(res_item["solver_id"] == "ConvBiasActivAsm1x1U") + { + std::cerr << "Skipping fused solvers" << std::endl; + return false; + } + const auto& s = solver_id.GetSolver(); + const auto algo = solver_id.GetAlgo(conv_dir); + res_item["algorithm"] = algo; + if(s.IsEmpty()) + { + res_item["reason"] = "Empty Solver"; + std::cerr << "Skipping invalid solver: " << solver_id.ToString() << std::endl; + return false; + } + if(!s.IsApplicable(ctx)) + { + res_item["reason"] = "Not Applicable"; + std::cerr << "Skipping inapplicable solver: " << solver_id.ToString() << std::endl; + return false; + } + miopen::solver::ConvSolution solution; + try + { + solution = s.FindSolution(ctx, db, {}); // auto tune is not expected here + } + catch(const std::exception& e) + { + res_item["reason"] = std::string("Solver throws exception") + e.what(); + std::cerr << "Exception during solution construction, solver_name: " + << solver_id.ToString() << e.what() << std::endl; + return true; + } + res_item["reason"] = "Success"; + res_item["workspace"] = solution.workspce_sz; + // Get the binary + json kernel_list = json::array(); + for(const auto& k : solution.construction_params) + { + json kernel; + auto comp_opts = k.comp_options; + // if(comp_opts[0] != ' ') + // comp_opts = ' ' + comp_opts; + auto p = handle.LoadProgram(k.kernel_file, comp_opts, false, ""); + const auto hsaco = p.IsCodeObjectInMemory() + ? p.GetCodeObjectBlob() + : miopen::LoadFile(p.GetCodeObjectPathname().string()); + if(hsaco.empty()) + { + std::cerr << "Got empty code object" << std::endl; + throw std::runtime_error("Got empty code object"); + } + // Compress the blob + auto md5_sum = miopen::md5(hsaco); + auto size = hsaco.size(); + bool success = false; + auto compressed_hsaco = miopen::compress(hsaco, &success); + const auto encoded_hsaco = base64_encode(compressed_hsaco); + kernel["kernel_file"] = k.kernel_file; + kernel["comp_options"] = k.comp_options; + if(success) + { + kernel["uncompressed_size"] = size; + kernel["md5_sum"] = md5_sum; + kernel["blob"] = encoded_hsaco; + } + else + { + kernel["md5_sum"] = "Failed to compress kernel"; + kernel["uncompressed_size"] = 0; + kernel["blob"] = ""; + } + kernel_list.push_back(kernel); + std::cerr << "Successfully added new kernel" << std::endl; + } + res_item["kernel_objects"] = kernel_list; + return true; + }; + + auto res = process_solver(); + if(res) + { + res_item["find_compiled"] = res; + find_result.push_back(res_item); + } + } + output["miopen_find_compile_result"] = find_result; + return 1; +} + +template +int ConvFin::MIOpenFindEval() +{ + std::cerr << "MIOpenFindEval" << std::endl; + std::cerr << "Processing command: " << command << std::endl; +// Before this step is executed, the following steps should have been evaluated +// alloc_buf only if only timing is required +// alloc_buf, fill_buf and copy_buf_to_device if numerical accuracy would be +// checked ?? +#if MIOPEN_MODE_NOGPU + throw std::runtime_error("Unable to run MIOpenFindEval, Invalid MIOpen backend: HIPNOGPU"); +#endif + const auto conv_dir = GetDirection(); + // The first arg to the DataInvokeParams changes based on direction + const miopen::ProblemDescription problem( + inputTensor.desc, weightTensor.desc, outputTensor.desc, convDesc, conv_dir); + GetHandle().EnableProfiling(true); + auto ctx = miopen::ConvolutionContext{problem}; + auto& h = GetHandle(); + ctx.SetStream(&(h)); + ctx.DetectRocm(); + ctx.SetupFloats(); + + const auto network_config = ctx.BuildConfKey(); + const bool is_winograd_only = convDesc.IsWinograd3x3SupportedAndFast(ctx); + output["is_winograd_only"] = is_winograd_only; + output["network_config"] = network_config; + std::ostringstream ss; + problem.Serialize(ss); + output["db_key"] = ss.str(); + + auto db = GetDb(ctx); + json find_result; + const auto& tgt_props = h.GetTargetProperties(); + const std::string arch = tgt_props.Name(); + const size_t num_cu = h.GetMaxComputeUnits(); + std::cerr << "Job Arch: " << job["arch"] << ": Handle Arch: " << arch << std::endl; + std::cerr << "Job Num CU: " << job["num_cu"] << ": Handle Num Cu: " << num_cu << std::endl; + for(const auto& kinder : + job["miopen_find_compile_result"]) // The "miopen_find_compile_result" list generated + // by miopen_find_compile operation + { + // Somehow the direction changes mid loop ! + json res_item; + boost::system::error_code ec; + boost::filesystem::remove_all(miopen::GetCachePath(false), ec); + // boost::filesystem::remove_all(miopen::GetCachePath(true), ec); + if(ec) + { + std::cerr << "Error while removing MIOpen cache: " << ec.message(); + } + auto process_solver = [&]() -> bool { + const std::string solver_name = kinder["solver_id"]; + std::cerr << "Processing solver: " << solver_name << std::endl; + const auto solver_id = miopen::solver::Id{solver_name}; + const auto& s = solver_id.GetSolver(); + res_item["solver_name"] = solver_name; + const auto algo = solver_id.GetAlgo(conv_dir); + res_item["algorithm"] = algo; + if(s.IsEmpty()) + { + std::cerr << "Skipping invalid solver: " << solver_id.ToString() << std::endl; + return false; + } + if(!s.IsApplicable(ctx)) + { + std::cerr << "Solver inapplicable: " << solver_name << std::endl; + throw std::runtime_error( + "InApplicable solver was sent to fin, check Tuna for errors"); + return false; + } + std::cerr << solver_name << " is applicable" << std::endl; + const auto solution = s.FindSolution(ctx, db, {}); // auto tune is not expected here + res_item["workspace"] = solution.workspce_sz; + // Get the binary + std::cerr << "loading binaries from fin input" << std::endl; + for(const auto& kernel_obj : kinder["kernel_objects"]) + { + const auto size = kernel_obj["uncompressed_size"]; + const auto md5_sum = kernel_obj["md5_sum"]; + const auto encoded_hsaco = kernel_obj["blob"]; + const auto decoded_hsaco = base64_decode(encoded_hsaco); + const auto hsaco = miopen::decompress(decoded_hsaco, size); + std::string comp_opts = kernel_obj["comp_options"]; + std::string kernel_file = kernel_obj["kernel_file"]; + if(miopen::md5(hsaco) == md5_sum) + { + auto p = miopen::Program{kernel_file, hsaco}; + h.AddProgram(p, kernel_file, comp_opts); + } + else + { + std::cerr << "Corrupt Binary Object" << std::endl; + throw std::runtime_error("Corrupt binary object"); + return false; + } + } + for(const auto& kern : solution.construction_params) + { + if(!h.HasProgram(kern.kernel_file, kern.comp_options)) + { + std::cerr << "Binary object check failed, either tuning params have changed or " + "fin is unable to write binary to program cache" + << std::endl; + } + } + std::cerr << "Checking for workspace" << std::endl; + if(solution.workspce_sz > workspace.desc.GetNumBytes()) + { + std::cerr << "Allocating " << solution.workspce_sz << " bytes for workspace" + << std::endl; + workspace = tensor{ + q, + std::vector{static_cast(solution.workspce_sz / sizeof(Tgpu))}, + false, + false}; + workspace.AllocateBuffers(); + } + if(!solution.invoker_factory) + { + std::cerr << "Invoker not implemeted" << std::endl; + res_item["reason"] = "Invoker not implemented"; + return false; + } + try + { + std::cerr << "Preparing invokers" << std::endl; + const auto invoker = + h.PrepareInvoker(*solution.invoker_factory, solution.construction_params); + // This is required because DataInvokeParams switches tensor order due to + // direction and it does not have a + // copy constructor or a default constructor + std::cerr << "Finished preparing invokers" << std::endl; + if(conv_dir == miopen::conv::Direction::Forward) + { + const auto invoke_ctx = + miopen::conv::DataInvokeParams{{inputTensor.desc, + inputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get(), + outputTensor.desc, + outputTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else if(conv_dir == miopen::conv::Direction::BackwardData) + { + const auto invoke_ctx = + miopen::conv::DataInvokeParams{{outputTensor.desc, + outputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get(), + inputTensor.desc, + inputTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else if(conv_dir == miopen::conv::Direction::BackwardWeights) + { + const auto invoke_ctx = + miopen::conv::WrWInvokeParams{{outputTensor.desc, + outputTensor.gpuData.buf.get(), + inputTensor.desc, + inputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else + { + throw std::runtime_error("Invalid Direction"); + } + } + catch(const std::exception& e) + { + res_item["reason"] = std::string("Invoker exeception: ") + e.what(); + return false; + } + const auto time = h.GetKernelTime(); + res_item["time"] = time; + res_item["reason"] = "Success"; + + return true; + + }; + + auto res = process_solver(); + res_item["evaluated"] = res; + find_result.push_back(res_item); + } + output["miopen_find_eval_result"] = find_result; + return 1; +} + +template +int ConvFin::MIOpenFind() +{ + // Before this step is executed, the following steps should have been evaluted + // alloc_buf only if only timing is required + // alloc_buf, fill_buf and copy_buf_to_device if numerical accuracy would be checked ?? + const auto conv_dir = GetDirection(); + // assert(conv_dir == miopen::conv::Direction::Forward); + // The first arg to the DataInvokeParams changes based on direction + const miopen::ProblemDescription problem( + inputTensor.desc, weightTensor.desc, outputTensor.desc, convDesc, conv_dir); + GetHandle().EnableProfiling(true); + auto ctx = miopen::ConvolutionContext{problem}; + auto& h = GetHandle(); + ctx.SetStream(&(h)); + ctx.DetectRocm(); + ctx.SetupFloats(); + + const auto network_config = ctx.BuildConfKey(); + const bool is_winograd_only = convDesc.IsWinograd3x3SupportedAndFast(ctx); + output["is_winograd_only"] = is_winograd_only; + output["network_config"] = network_config; + std::ostringstream ss; + problem.Serialize(ss); + output["db_key"] = ss.str(); + miopen::ConvolutionUserBuffers bufs(workspace.gpuData.buf.get(), workspace.desc.GetNumBytes()); + if(conv_dir == miopen::conv::Direction::Forward) + bufs.SetFwd(inputTensor.gpuData.buf.get(), + weightTensor.gpuData.buf.get(), + outputTensor.gpuData.buf.get()); + else if(conv_dir == miopen::conv::Direction::BackwardData) + bufs.SetBwd(inputTensor.gpuData.buf.get(), + weightTensor.gpuData.buf.get(), + outputTensor.gpuData.buf.get()); + else if(conv_dir == miopen::conv::Direction::BackwardWeights) + bufs.SetWrW(inputTensor.gpuData.buf.get(), + weightTensor.gpuData.buf.get(), + outputTensor.gpuData.buf.get()); + + ctx.SetBufs(bufs); + + auto db = GetDb(ctx); + json find_result; + const auto& tgt_props = h.GetTargetProperties(); + const std::string arch = tgt_props.Name(); + assert(arch == job["arch"]); + const size_t num_cu = h.GetMaxComputeUnits(); + assert(num_cu == job["num_cu"]); + for(const auto& solver_id : + miopen::solver::GetSolversByPrimitive(miopen::solver::Primitive::Convolution)) + { + json res_item; + auto process_solver = [&]() -> bool { + res_item["solver_id"] = solver_id.ToString(); + const auto& s = solver_id.GetSolver(); + const auto algo = solver_id.GetAlgo(conv_dir); + res_item["algorithm"] = algo; + if(s.IsEmpty()) + { + res_item["reason"] = "Empty Solver"; + std::cerr << "Skipping invalid solver: " << solver_id.ToString() << std::endl; + return false; + } + if(!s.IsApplicable(ctx)) + { + res_item["reason"] = "Not Applicable"; + return false; + } + const auto solution = s.FindSolution(ctx, db, {}); // auto tune is not expected here + res_item["workspace"] = solution.workspce_sz; + // Get the binary + miopen::solver::PrecompileKernels(h, solution.construction_params); + json kernel_list = json::array(); + for(const auto& k : solution.construction_params) + { + json kernel; + const auto hsaco = miopen::LoadBinary( + tgt_props, num_cu, k.kernel_file, k.comp_options + " -mcpu=" + arch, false); + if(hsaco.empty()) + throw std::runtime_error("Got empty code object"); + // Compress the blob + auto md5_sum = miopen::md5(hsaco); + kernel["md5_sum"] = md5_sum; + auto size = hsaco.size(); + bool success = false; + auto compressed_hsaco = miopen::compress(hsaco, &success); + if(success) + { + const auto encoded_hsaco = base64_encode(compressed_hsaco); + kernel["uncompressed_size"] = size; + kernel["blob"] = encoded_hsaco; + } + else + { + const auto encoded_hsaco = base64_encode(hsaco); + kernel["uncompressed_size"] = 0; + kernel["blob"] = encoded_hsaco; + } + kernel_list.push_back(kernel); + } + res_item["kernel_objects"] = kernel_list; + if(solution.workspce_sz > workspace.desc.GetNumBytes()) + { + res_item["reason"] = "Insufficient Workspace"; + return false; + } + if(!solution.invoker_factory) + { + res_item["reason"] = "Invoker not implemented"; + return false; + } + try + { + const auto invoker = + h.PrepareInvoker(*solution.invoker_factory, solution.construction_params); + // This required because DataInvokeParams switches tensor order + // due to direction and it does not have a + // copy constructor or a default constructor + if(conv_dir == miopen::conv::Direction::Forward) + { + const auto invoke_ctx = + miopen::conv::DataInvokeParams{{inputTensor.desc, + inputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get(), + outputTensor.desc, + outputTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else if(conv_dir == miopen::conv::Direction::BackwardData) + { + const auto invoke_ctx = + miopen::conv::DataInvokeParams{{outputTensor.desc, + outputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get(), + inputTensor.desc, + inputTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else if(conv_dir == miopen::conv::Direction::BackwardWeights) + { + const auto invoke_ctx = + miopen::conv::WrWInvokeParams{{outputTensor.desc, + outputTensor.gpuData.buf.get(), + inputTensor.desc, + inputTensor.gpuData.buf.get(), + weightTensor.desc, + weightTensor.gpuData.buf.get()}, + workspace.gpuData.buf.get(), + workspace.desc.GetNumBytes()}; + invoker(h, invoke_ctx); + } + else + { + throw std::runtime_error("Invalid Direction"); + } + } + catch(const std::exception& e) + { + res_item["reason"] = std::string("Invoker exeception: ") + e.what(); + return false; + } + const auto time = h.GetKernelTime(); + res_item["time"] = time; + res_item["reason"] = "Success"; + + return true; + + }; + + auto res = process_solver(); + res_item["evaluated"] = res; + find_result.push_back(res_item); + } + + output["miopen_find_result"] = find_result; + return 1; +} + +template +int ConvFin::TestApplicability() +{ +#if MIOPEN_MODE_NOGPU + GetandSetData(); +#else + throw std::runtime_error("MIOpen needs to be compiled with the NOGPU backend " + "to test applicability"); +#endif + const auto conv_dir = GetDirection(); + const miopen::ProblemDescription problem( + inputTensor.desc, weightTensor.desc, outputTensor.desc, convDesc, conv_dir); + auto ctx = miopen::ConvolutionContext{problem}; + auto handle = miopen::Handle{}; +#if MIOPEN_MODE_NOGPU + InitNoGpuHandle(handle); +#else + throw std::runtime_error("MIOpen needs to be compiled with the NOGPU backend " + "to test applicability"); +#endif + + ctx.SetStream(&handle); + ctx.DetectRocm(); + ctx.SetupFloats(); + const auto network_config = ctx.BuildConfKey(); + std::vector app_solvers; + for(const auto& id : + miopen::solver::GetSolversByPrimitive(miopen::solver::Primitive::Convolution)) + { + std::cerr << "Testing: " << id.ToString() << std::endl; + auto solver = id.GetSolver(); + if(id.IsValid() && !solver.IsEmpty()) + { + try + { + if(solver.IsApplicable(ctx)) + app_solvers.push_back(id.ToString()); + } + catch(...) + { + std::cerr << id.ToString() << "(" << id.Value() << ")" + << " raised an exception" + << "for " << std::string(network_config) << " config: " << job + << std::endl; + } + } + else + { + std::cerr << "Solver: " << id.ToString() << " is invalid or empty" << std::endl; + } + } + output["applicable_solvers"] = app_solvers; + return 0; +} + +template +int ConvFin::GetSolverList() +{ + // pair.first = id, pair. second = string id + std::vector> solvers; + for(const auto& id : + miopen::solver::GetSolversByPrimitive(miopen::solver::Primitive::Convolution)) + solvers.push_back(std::make_pair(id.Value(), id.ToString())); + output["all_solvers"] = solvers; + return 0; +} + +template +int ConvFin::RunGPU() +{ + assert(false); + return 0; +} + +template +int ConvFin::CopyToDevice() +{ +#if MIOPEN_MODE_NOGPU + throw std::runtime_error("Unable to copy buffers to device with NOGPU backend"); + return -1; +#else + auto status = inputTensor.ToDevice(); + status |= inputTensor_vect4.ToDevice(); + status |= weightTensor.ToDevice(); + status |= outputTensor.ToDevice(); + status |= biasTensor.ToDevice(); + status |= workspace.ToDevice(); + return status; +#endif +} + +template +int ConvFin::CopyFromDevice() +{ +#if MIOPEN_MODE_NOGPU + throw std::runtime_error("Unable to copy buffers to device with NOGPU backend"); + return -1; +#else + auto status = inputTensor.FromDevice(); + status |= inputTensor_vect4.FromDevice(); + status |= weightTensor.FromDevice(); + status |= outputTensor.FromDevice(); + status |= biasTensor.FromDevice(); + status |= workspace.FromDevice(); + return status; +#endif +} + +template +int ConvFin::ProcessStep(const std::string& step_name) +{ + steps_processed.push_back(step_name); + if(step_name == "alloc_buf") + return AllocateBuffers(); + if(step_name == "fill_buf") + return FillBuffers(); + if(step_name == "copy_buf_to_device") + return CopyToDevice(); + if(step_name == "copy_buf_from_device") + return CopyFromDevice(); + if(step_name == "applicability") + return TestApplicability(); + if(step_name == "get_solvers") + return GetSolverList(); + if(step_name == "miopen_find") + return MIOpenFind(); + if(step_name == "miopen_find_compile") + return MIOpenFindCompile(); + if(step_name == "miopen_find_eval") + return MIOpenFindEval(); + return 0; +} + +template +int ConvFin::GetandSetData() +{ + auto in_len = GetInputTensorLengths(); + auto wei_len = GetWeightTensorLengths(); + + // auto y_type = GetOutputType(); + + inputTensor = {GetHandle().GetStream(), in_len, (is_fwd || is_wrw), is_bwd}; + + weightTensor = {GetHandle().GetStream(), wei_len, (is_fwd || is_bwd), is_wrw}; + // conv, input and weight tensor descriptors need to be set before we can know the + // output lengths + auto out_len = GetOutputTensorLengths(); + outputTensor = {GetHandle().GetStream(), out_len, (is_bwd || is_wrw), is_fwd}; + + if(IsInputTensorTransform()) + { + std::vector in_len_v4(in_len.begin(), in_len.end()); + in_len_v4[1] = ((in_len[1] + 3) / 4) * 4; + std::vector wei_len_v4(wei_len.begin(), wei_len.end()); + wei_len_v4[1] = ((wei_len[1] + 3) / 4) * 4; + + inputTensor_vect4 = {GetHandle().GetStream(), in_len_v4, (is_fwd || is_wrw), is_bwd}; + weightTensor_vect4 = {GetHandle().GetStream(), wei_len_v4, (is_fwd || is_bwd), is_wrw}; + } + + // Conv Desc is already setup from the job descriptor + + if(command["bias"].get() != 0) + { + auto bias_len = GetBiasTensorLengths(); + biasTensor = {GetHandle().GetStream(), bias_len, true, true}; + } + // TODO: further investigate the warmup iteration, I dont think its necessary and can be + // GetHandle()d in the main execution loop + + return (0); +} + +template +std::vector ConvFin::GetInputTensorLengths() +{ + std::vector in_lens; + + int spatial_dim = command["spatial_dim"]; + in_lens.resize(2 + spatial_dim); + + in_lens[0] = command["batchsize"]; + in_lens[1] = command["in_channels"]; + + auto in_spatial_lens = boost::adaptors::slice(in_lens, 2, 2 + spatial_dim); + + if(spatial_dim == 2) + { + in_spatial_lens[0] = command["in_h"]; + in_spatial_lens[1] = command["in_w"]; + } + else if(spatial_dim == 3) + { + in_spatial_lens[0] = command["in_d"]; + in_spatial_lens[1] = command["in_h"]; + in_spatial_lens[2] = command["in_w"]; + } + else + { + FIN_THROW("unsupported convolution dimension"); + } + + return in_lens; +} + +template +std::vector ConvFin::GetWeightTensorLengths() +{ + std::vector wei_lens; + + int spatial_dim = command["spatial_dim"]; + wei_lens.resize(2 + spatial_dim); + + auto wei_spatial_lens = boost::adaptors::slice(wei_lens, 2, 2 + spatial_dim); + + int group_count = std::max(int(command["group_count"]), 1); + + int wei_k_len = command["out_channels"]; + int wei_c_len = command["in_channels"]; + + if(spatial_dim == 2) + { + wei_spatial_lens[0] = command["fil_h"]; + wei_spatial_lens[1] = command["fil_w"]; + } + else if(spatial_dim == 3) + { + wei_spatial_lens[0] = command["fil_d"]; + wei_spatial_lens[1] = command["fil_h"]; + wei_spatial_lens[2] = command["fil_w"]; + } + else + { + FIN_THROW("unsupported convolution dimension"); + } + + if(group_count > 1) + { + if(wei_c_len % group_count != 0 || wei_k_len % group_count != 0 || + group_count > wei_c_len || group_count > wei_k_len) + { + FIN_THROW("Invalid group number\n"); + } + } + + miopenConvolutionMode_t mode; + if((command["conv_mode"]) == "conv") + { + mode = miopenConvolution; + } + else if((command["conv_mode"]) == "trans") + { + mode = miopenTranspose; + } + else + { + FIN_THROW("Incorrect Convolution Mode\n"); + } + + if(mode == miopenTranspose) + { + wei_lens[0] = wei_c_len; + wei_lens[1] = wei_k_len / group_count; + } + else + { + wei_lens[0] = wei_k_len; + wei_lens[1] = wei_c_len / group_count; + } + + return wei_lens; +} + +template +std::vector ConvFin::GetBiasTensorLengths() +{ + int spatial_dim = command["spatial_dim"]; + + std::vector bias_lens(2 + spatial_dim, 1); + + bias_lens[1] = command["out_channels"]; + + return bias_lens; +} + +template +int ConvFin::SetConvDescriptor() +{ + size_t spatial_dim = command["spatial_dim"]; + + std::vector in_spatial_lens(spatial_dim); + std::vector wei_spatial_lens(spatial_dim); + std::vector pads(spatial_dim); + std::vector conv_strides(spatial_dim); + std::vector conv_dilations(spatial_dim); + std::vector trans_output_pads(spatial_dim); + + if(spatial_dim == 2) + { + in_spatial_lens[0] = command["in_h"]; + in_spatial_lens[1] = command["in_w"]; + wei_spatial_lens[0] = command["fil_h"]; + wei_spatial_lens[1] = command["fil_w"]; + pads[0] = command["pad_h"]; + pads[1] = command["pad_w"]; + conv_strides[0] = command["conv_stride_h"]; + conv_strides[1] = command["conv_stride_w"]; + conv_dilations[0] = command["dilation_h"]; + conv_dilations[1] = command["dilation_w"]; + trans_output_pads[0] = 0; // command["trans_output_pad_h"]; + trans_output_pads[1] = 0; // command["trans_output_pad_w"]; + } + else if(spatial_dim == 3) + { + in_spatial_lens[0] = command["in_d"]; + in_spatial_lens[1] = command["in_h"]; + in_spatial_lens[2] = command["in_w"]; + wei_spatial_lens[0] = command["fil_d"]; + wei_spatial_lens[1] = command["fil_h"]; + wei_spatial_lens[2] = command["fil_w"]; + pads[0] = command["pad_d"]; + pads[1] = command["pad_h"]; + pads[2] = command["pad_w"]; + conv_strides[0] = command["conv_stride_d"]; + conv_strides[1] = command["conv_stride_h"]; + conv_strides[2] = command["conv_stride_w"]; + conv_dilations[0] = command["dilation_d"]; + conv_dilations[1] = command["dilation_h"]; + conv_dilations[2] = command["dilation_w"]; + trans_output_pads[0] = 0; // command["trans_output_pad_d"]; + trans_output_pads[1] = 0; // command["trans_output_pad_h"]; + trans_output_pads[2] = 0; // command["trans_output_pad_w"]; + } + else + { + FIN_THROW("unsupported convolution dimension"); + } + + int out_c = command["out_channels"]; + int in_c = command["in_channels"]; + int group_count = std::max(int(command["group_count"]), 1); + + if(group_count > 1) + { + if(in_c % group_count != 0 || out_c % group_count != 0 || group_count > in_c || + group_count > out_c) + { + printf("Invalid group number\n"); + exit(0); + } + } + + miopenConvolutionMode_t c_mode; + if((command["conv_mode"]) == "conv") + { + c_mode = miopenConvolution; + } + else if((command["conv_mode"]) == "trans") + { + c_mode = miopenTranspose; + } + else + { + printf("Incorrect Convolution Mode\n"); + exit(0); + } + + miopenPaddingMode_t p_mode = miopenPaddingSame; + if((command["pad_mode"]) == "same") + p_mode = miopenPaddingSame; + else if((command["pad_mode"]) == "valid") + p_mode = miopenPaddingValid; + + // adjust padding based on user-defined padding mode + if(c_mode == miopenConvolution && + (miopen::all_of(conv_dilations, [](auto v) { return v == 1; }) || + miopen::all_of(wei_spatial_lens, [](auto v) { return v == 1; }))) + { + if(p_mode == miopenPaddingSame) + { + for(int i = 0; i < spatial_dim; ++i) + { + pads[i] = + (in_spatial_lens[i] % conv_strides[i] == 0) + ? (std::max((wei_spatial_lens[i] - conv_strides[i]), 0)) + : (std::max((wei_spatial_lens[i] - (in_spatial_lens[i] % conv_strides[i])), + 0)); + pads[i] /= 2; + } + } + else if(p_mode == miopenPaddingValid) + { + for(int i = 0; i < spatial_dim; ++i) + { + pads[i] = 0; + } + } + } + + convDesc = miopen::ConvolutionDescriptor{spatial_dim, + c_mode, + p_mode, + pads, + conv_strides, + conv_dilations, + trans_output_pads, + group_count}; + + return miopenStatusSuccess; +} + +template +std::vector ConvFin::GetOutputTensorLengths() const +{ + return convDesc.GetForwardOutputTensor(inputTensor.desc, weightTensor.desc).GetLengths(); +} + +template +bool ConvFin::IsInputTensorTransform() const +{ + return (data_type == miopenInt8 && int(command["in_channels"]) % 4 != 0) || + data_type == miopenInt8x4; +} + +namespace detail { + +template +T RanGenWeights() +{ + return RAN_GEN(static_cast(-0.5), static_cast(0.5)); +} + +// Shift FP16 distribution towards positive numbers, +// otherwise Winograd FP16 validation fails. +template <> +float16 RanGenWeights() +{ + return RAN_GEN(static_cast(-1.0 / 3.0), static_cast(0.5)); +} + +} // namespace detail + +template +int ConvFin::AllocateBuffers() +{ +#if MIOPEN_MODE_NOGPU + throw std::runtime_error("Unable to allocate buffers with NOGPU backend"); +#else + GetandSetData(); + inputTensor.AllocateBuffers(); + inputTensor_vect4.AllocateBuffers(); + weightTensor.AllocateBuffers(); + outputTensor.AllocateBuffers(); + biasTensor.AllocateBuffers(); + // The workspace is actually allocated when the solver is about to be run + // since it varies from solver to solver + workspace.AllocateBuffers(); +#endif + return 0; +} + +template +int ConvFin::CalcWorkspace() +{ + // if(solver is known) + // Find workspace for solver using the GetSolution mechanism + // else + // if(!immediate_solution) + size_t ws_sizeof_find_fwd = 0; + size_t ws_sizeof_find_wrw = 0; + size_t ws_sizeof_find_bwd = 0; + auto is_transform = IsInputTensorTransform(); + + if(is_wrw) + ws_sizeof_find_wrw = convDesc.BackwardWeightsGetWorkSpaceSize( + GetHandle(), outputTensor.desc, inputTensor.desc, weightTensor.desc); + if(is_bwd) + { + ws_sizeof_find_bwd = + (convDesc.mode == miopenTranspose) + ? convDesc.ForwardGetWorkSpaceSize( + GetHandle(), weightTensor.desc, outputTensor.desc, inputTensor.desc) + : convDesc.BackwardDataGetWorkSpaceSize( + GetHandle(), weightTensor.desc, outputTensor.desc, inputTensor.desc); + } + if(is_fwd) + { + ws_sizeof_find_fwd = (convDesc.mode == miopenTranspose) + ? convDesc.BackwardDataGetWorkSpaceSize( + GetHandle(), + (is_transform ? weightTensor_vect4.desc : weightTensor.desc), + (is_transform ? inputTensor_vect4.desc : inputTensor.desc), + outputTensor.desc) + : convDesc.ForwardGetWorkSpaceSize( + GetHandle(), + (is_transform ? weightTensor_vect4.desc : weightTensor.desc), + (is_transform ? inputTensor_vect4.desc : inputTensor.desc), + outputTensor.desc); + } + + const auto wsSizeof = + std::max(std::max(ws_sizeof_find_bwd, ws_sizeof_find_wrw), ws_sizeof_find_fwd); + if(wsSizeof != 0) + workspace = tensor{q, + std::vector{static_cast( + std::ceil(wsSizeof / sizeof(Tgpu)))}, + true, + false}; + return wsSizeof; +} + +template +Tgpu init_in(bool is_int8, size_t idx) +{ + (void)idx; + if(is_int8) + { + float Data_scale = 127.0; + return static_cast(Data_scale * + RAN_GEN(static_cast(0.0), static_cast(1.0))); + } + else + { + Tgpu Data_scale = static_cast(0.01); + return Data_scale * RAN_GEN(static_cast(0.0), static_cast(1.0)); + } +} + +template +Tgpu init_out(bool is_int8, size_t idx) +{ + (void)idx; + if(is_int8) + { + return static_cast(0); // int8 is inference only + } + else + { + Tgpu Data_scale = static_cast(0.01); + return Data_scale * RAN_GEN(static_cast(0.0), static_cast(1.0)); + } +} + +template +Tgpu init_wei(bool is_int8, size_t idx) +{ + (void)idx; + if(is_int8) + { + float Data_scale = 127.0; + return static_cast(Data_scale * 2 * detail::RanGenWeights()); + } + else + { + Tgpu Data_scale = static_cast(0.01); + return Data_scale * detail::RanGenWeights(); + } +} + +template +Tgpu init_bias(bool is_int8, size_t idx) +{ + (void)idx; + (void)is_int8; + return static_cast(idx % 8) + + RAN_GEN(static_cast(0.0), static_cast(1.0)); +} + +template +int ConvFin::FillBuffers() +{ +#if MIOPEN_MODE_NOGPU + throw std::runtime_error("Unable to fill buffers with NOGPU backend"); +#else + // TODO: Do we need to initialized tensors ? + auto is_int8 = (data_type == miopenInt8 || data_type == miopenInt8x4); + srand(0); + + inputTensor.FillBuffer(std::bind(init_in, is_int8, std::placeholders::_1)); + outputTensor.FillBuffer(std::bind(init_out, is_int8, std::placeholders::_1)); + weightTensor.FillBuffer(std::bind(init_wei, is_int8, std::placeholders::_1)); + if(command["bias"].get() != 0) + { + biasTensor.FillBuffer(std::bind(init_bias, is_int8, std::placeholders::_1)); + } +#endif + return 0; +} +} // namespace fin +#endif // GUARD_MIOPEN_CONV_FIN_HPP diff --git a/src/include/error.hpp b/src/include/error.hpp new file mode 100644 index 0000000000..0279019964 --- /dev/null +++ b/src/include/error.hpp @@ -0,0 +1,27 @@ +#pragma once + +#include +#include +#include + +namespace fin { + +struct Exception : std::exception +{ + std::string message; + Exception(const std::string& msg = "") : message(msg) {} + + Exception SetContext(const std::string& file, int line) + { + message = file + ":" + std::to_string(line) + ": " + message; + return *this; + } + + const char* what() const noexcept override { return message.c_str(); } +}; +} +#define FIN_THROW(...) \ + do \ + { \ + throw fin::Exception(__VA_ARGS__).SetContext(__FILE__, __LINE__); \ + } while(false) diff --git a/src/include/fin.hpp b/src/include/fin.hpp new file mode 100644 index 0000000000..f07aa16774 --- /dev/null +++ b/src/include/fin.hpp @@ -0,0 +1,113 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2020 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#ifndef GUARD_FIN_HPP +#define GUARD_FIN_HPP + +// using float16 = half_float::half; +#include "config.h" +#include "tensor.hpp" + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +using json = nlohmann::json; + +#if FIN_BACKEND_OPENCL +#if defined(__APPLE__) || defined(__MACOSX) +#include +#else +#include +#endif +#elif FIN_BACKEND_HIP +#include +#endif + +namespace fin { +class Fin +{ + public: + Fin() {} + void Usage(); + std::string ParseBaseArg(const int argc, const char* argv[]); + miopen::Handle& GetHandle() + { + static auto handle = miopen::Handle{}; + return handle; + } + miopenDataType_t GetDataType() { return data_type; } + +#if FIN_BACKEND_OPENCL + cl_command_queue& GetStream() { return q; } +#elif FIN_BACKEND_HIP + hipStream_t& GetStream() { return q; } +#endif + virtual ~Fin() {} // TODO: do we need this + + virtual int ProcessStep(const std::string& step_name) = 0; + + json output; + + protected: + template + void InitDataType(); + miopenDataType_t data_type = miopenFloat; // the datatype passed in through the command line + +#if FIN_BACKEND_OPENCL + cl_command_queue q; +#elif FIN_BACKEND_HIP + hipStream_t q; +#endif +}; + +// "std::is_same{}" used to avoid "static_assert" compilation +// error, +// which occurs when the condition does not depend in any way on the template +// parameters. +template +void Fin::InitDataType() +{ + static_assert(std::is_same{}, "unsupported Tgpu"); +} + +template +std::ostream& operator<<(std::ostream& os, const std::vector& vs) +{ + os << "{ size: " << vs.size() << ", entries: "; + for(auto& v : vs) + os << v << " "; + os << "}"; + return os; +} +} // namespace fin +#endif // GUARD_FIN_HPP diff --git a/src/include/gpu_mem.hpp b/src/include/gpu_mem.hpp new file mode 100644 index 0000000000..5ecefe6d9a --- /dev/null +++ b/src/include/gpu_mem.hpp @@ -0,0 +1,121 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2020 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#ifndef GUARD_FIN_GPUMEM_HPP +#define GUARD_FIN_GPUMEM_HPP + +#include "half.hpp" +#include +#include +#include +#include +#include +#include +#include +#include +#include + +#include + +namespace fin { + +struct relMem +{ +#if FIN_BACKEND_OPENCL + void operator()(cl_mem ptr) { clReleaseMemObject(ptr); } +#elif FIN_BACKEND_HIP + void operator()(void* ptr) { hipFree(ptr); } +#endif +}; +#if FIN_BACKEND_OPENCL +using gpu_mem_ptr = std::unique_ptr; +#elif FIN_BACKEND_HIP +using gpu_mem_ptr = std::unique_ptr; +#endif + +struct GPUMem +{ + +#if FIN_BACKEND_OPENCL + GPUMem(){}; + GPUMem(cl_context& ctx, size_t psz, size_t pdata_sz) : sz(psz), data_sz(pdata_sz) + { + buf = gpu_mem_ptr{clCreateBuffer(ctx, CL_MEM_READ_WRITE, data_sz * sz, nullptr, nullptr)}; + } + + int ToGPU(cl_command_queue& q, void* p) + { + return clEnqueueWriteBuffer(q, buf.get(), CL_TRUE, 0, data_sz * sz, p, 0, nullptr, nullptr); + } + int FromGPU(cl_command_queue& q, void* p) + { + return clEnqueueReadBuffer(q, buf.get(), CL_TRUE, 0, data_sz * sz, p, 0, nullptr, nullptr); + } + + cl_mem GetMem() { return buf.get(); } + size_t GetSize() { return sz * data_sz; } + + // ~GPUMem() { clReleaseMemObject(buf); } + + gpu_mem_ptr buf; +#elif FIN_BACKEND_HIP + + GPUMem(){}; + GPUMem(uint32_t ctx, size_t psz, size_t pdata_sz) : _ctx(ctx), sz(psz), data_sz(pdata_sz) + { + void* tmp = nullptr; + hipMalloc(static_cast(&(tmp)), data_sz * sz); + if(tmp == nullptr && sz > 0) + throw std::runtime_error("Unable to allocate GPU memory"); + buf = gpu_mem_ptr{tmp}; + } + + int ToGPU(hipStream_t q, void* p) + { + _q = q; + return static_cast(hipMemcpy(buf.get(), p, data_sz * sz, hipMemcpyHostToDevice)); + } + int FromGPU(hipStream_t q, void* p) + { + hipDeviceSynchronize(); + _q = q; + return static_cast(hipMemcpy(p, buf.get(), data_sz * sz, hipMemcpyDeviceToHost)); + } + + void* GetMem() { return buf.get(); } + size_t GetSize() { return sz * data_sz; } + + // ~GPUMem() { hipFree(buf); } + hipStream_t _q; // Place holder for opencl context + uint32_t _ctx; + gpu_mem_ptr buf; +#endif + size_t sz; + size_t data_sz; +}; + +} // namespace fin +#endif // #define GUARD_FIN_GPUMEM_HPP diff --git a/src/include/random.hpp b/src/include/random.hpp new file mode 100644 index 0000000000..4da92fd877 --- /dev/null +++ b/src/include/random.hpp @@ -0,0 +1,18 @@ +#ifndef GUARD_FIN_RANDOM_GEN_ +#define GUARD_FIN_RANDOM_GEN_ + +template +static T FRAND(void) +{ + double d = static_cast(rand() / (static_cast(RAND_MAX))); + return static_cast(d); +} + +template +static T RAN_GEN(T A, T B) +{ + T r = (FRAND() * (B - A)) + A; + return r; +} + +#endif // GUARD_FIN_RANDOM_GEN_ diff --git a/src/include/tensor.hpp b/src/include/tensor.hpp new file mode 100644 index 0000000000..b6706690db --- /dev/null +++ b/src/include/tensor.hpp @@ -0,0 +1,139 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2020 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#ifndef GUARD_FIN_TENSOR_HPP +#define GUARD_FIN_TENSOR_HPP + +#include +#include + +#include +#include + +namespace fin { + +using half_float::half; +typedef half float16; + +template +miopenDataType_t GetDataType(); + +template <> +miopenDataType_t GetDataType(); +template <> +miopenDataType_t GetDataType(); +template <> +miopenDataType_t GetDataType(); +#if FIN_BACKEND_OPENCL +#define STATUS_SUCCESS CL_SUCCESS +using status_t = cl_int; +#else // FIN_BACKEND_HIP +#define STATUS_SUCCESS 0 +using status_t = int; +#endif + +template +struct tensor +{ +#if FIN_BACKEND_OPENCL + using context_type = cl_context; + using accelerator_stream = cl_command_queue; + context_type ctx; +#elif FIN_BACKEND_HIP + using accelerator_stream = hipStream_t; + using context_type = uint32_t; + context_type ctx = 0; +#endif + miopen::TensorDescriptor desc; + std::vector cpuData; // version of the data for the CPU compute + std::vector deviceData; // home for the GPU data on the CPU side + GPUMem gpuData; // object representing the GPU data ON the GPU + accelerator_stream q; + bool is_input; + bool is_output; + + tensor() {} + // cppcheck-suppress uninitMemberVar + template + tensor(accelerator_stream _q, std::vector _plens, bool _is_input, bool _is_output) + : desc(GetDataType(), _plens), + gpuData(), + q(_q), + is_input(_is_input), + is_output(_is_output) + { +#if FIN_BACKEND_OPENCL + clGetCommandQueueInfo(q, CL_QUEUE_CONTEXT, sizeof(cl_context), &ctx, nullptr); +#endif + } + + status_t FromDevice() + { + status_t status = 0; + if(is_output) + status = gpuData.FromGPU(q, deviceData.data()); + return status; + } + + status_t ToDevice() + { + status_t status = 0; + if(is_input) + status = gpuData.ToGPU(q, cpuData.data()); + else if(is_output) + status = gpuData.ToGPU(q, deviceData.data()); // to set the data to zero on the GPU + return status; + } + + void AllocateBuffers() + { + if(is_input) + // TODO: check if the datatype is correct; + cpuData = std::vector(desc.GetNumBytes(), static_cast(0)); + + if(is_output) + deviceData = std::vector(desc.GetNumBytes(), static_cast(0)); + + gpuData = GPUMem{ctx, desc.GetNumBytes() / sizeof(Tgpu), sizeof(Tgpu)}; + } + template + void FillBuffer(F f) + { + for(int i = 0; i < GetTensorSize(); i++) + { + if(is_input) // is input + cpuData[i] = f(i); + // Data_scale * RAN_GEN(static_cast(0.0), + // static_cast(1.0)); + else /// \ref move_rand + std::ignore = rand(); + } + } + + size_t GetTensorSize() { return desc.GetElementSize(); } +}; +} // namespace fin +#endif // GUARD_FIN_TENSOR_HPP diff --git a/src/main.cpp b/src/main.cpp new file mode 100644 index 0000000000..0994a33363 --- /dev/null +++ b/src/main.cpp @@ -0,0 +1,166 @@ +/******************************************************************************* + * + * MIT License + * + * Copyright (c) 2020 Advanced Micro Devices, Inc. + * + * 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. + * + *******************************************************************************/ +#include + +#include "conv_fin.hpp" +#include "error.hpp" +#include "fin.hpp" + +#include +#include + +using half_float::half; +typedef half float16; + +#include +#include +#include + +#include +#include +#include +#include + +using json = nlohmann::json; + +[[gnu::noreturn]] void Usage() +{ + printf("Usage: ./fin *input_json *output_json\n\n"); + printf("Supported arguments:\n"); + printf("-i *input_json\n"); + printf("-o *output_json\n"); + printf("\n"); + exit(0); +} + +int main(int argc, char* argv[], char* envp[]) +{ + std::vector args(argv, argv + argc); + std::string ifile; + std::string ofile; + std::map MapInputs = {}; + + for(auto& arg : args) + { + if(arg == "--help" || arg == "-help" || arg == "-h") + { + Usage(); + } + } + + if(argc != 5) + { + std::cerr << "Invalid arguments" << std::endl; + Usage(); + } + + for(int i = 0; i < args.size(); i++) + { + if(args[i] == "-i") + { + if(!boost::filesystem::exists(args[i + 1])) + { + std::cerr << "File: " << args[i + 1] << " does not exist" << std::endl; + exit(-1); + } + MapInputs[args[i].back()] = args[i + 1]; + } + if(args[i] == "-o") + { + ofile = args[i + 1]; + MapInputs[args[i].back()] = args[i + 1]; + } + } + + boost::filesystem::path input_filename(MapInputs['i']); + boost::filesystem::path output_filename(MapInputs['o']); + + // The JSON is a list of commands, so we iterate over the list and then + // process each map + std::ifstream i(input_filename.string()); + // TODO: fix the output writing so that interim results are not lost if one of + // the iterations crash + std::ofstream o(output_filename.string()); + json j; // = json::parse(cmd); + i >> j; + i.close(); + json final_output; + // Get the process env + std::vector jenv; + for(auto env = envp; *env != nullptr; env++) + jenv.push_back(*env); + json res_item; + + res_item["process_env"] = jenv; + final_output.push_back(res_item); + // process through the jobs + for(auto& it : j) + { + auto command = it; + fin::Fin* f = nullptr; + // TODO : Move this to a factory function + if(command.contains("config")) + { + if(command["config"]["cmd"] == "conv") + { + f = new fin::ConvFin(command); + } + else if(command["config"]["cmd"] == "convfp16") + { + f = new fin::ConvFin(command); + } + else if(command["config"]["cmd"] == "convbfp16") + { + f = new fin::ConvFin(command); + } + else + { + FIN_THROW("Invalid operation: " + command["config"]["cmd"].get()); + exit(-1); + } + } + else + { + f = new fin::ConvFin(); + } + + for(auto& step_it : command["steps"]) + { + std::string step = step_it.get(); + f->ProcessStep(step); + } + f->output["config_tuna_id"] = command["config_tuna_id"]; + f->output["arch"] = command["arch"]; + f->output["direction"] = command["direction"]; + f->output["input"] = command; + final_output.push_back(f->output); + } + o << std::setw(4) << final_output << std::endl; + o.flush(); + o.close(); + return 0; +} diff --git a/src/tensor.cpp b/src/tensor.cpp new file mode 100644 index 0000000000..7210aa073f --- /dev/null +++ b/src/tensor.cpp @@ -0,0 +1,31 @@ +#include "tensor.hpp" + +namespace fin { + +tensor::randInit(double dataScale, double min, double max) +{ + // different for fwd/wrw and bwd + for(auto& it : cpuData) + { + // it = + } +} + +size_t tensor::size() +{ + // TODO: check that all internal storages have the same size + return desc.GetElementSize(); +} + +size_t tensor::elem_size(miopenDataType_t data_type) +{ + switch(data_type) + { + case miopenFloat: return sizeof(float); + case miopenHalf: return sizeof(float16); + case miopenBFloat16: return sizeof(bfloat16); + case miopenInt8: return sizeof(int8_t); + } +} + +} // namespace fin diff --git a/src/tests/fin_input.json b/src/tests/fin_input.json new file mode 100644 index 0000000000..f0d34520f7 --- /dev/null +++ b/src/tests/fin_input.json @@ -0,0 +1,12 @@ +[ + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 4, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 2, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 1, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 4, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 2, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 1, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 4, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convbfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 2, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convbfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["alloc_buf", "miopen_find"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 1, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convbfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + {"steps":["get_solvers"]} +] diff --git a/src/tests/fin_input_applicability.json b/src/tests/fin_input_applicability.json new file mode 100644 index 0000000000..ef439e12ee --- /dev/null +++ b/src/tests/fin_input_applicability.json @@ -0,0 +1,12 @@ +[ + { "steps": ["applicability"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 4, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["applicability"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 2, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["applicability"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 1, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "conv", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["applicability"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 4, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, "dilation_w" : 1 } }, + { "steps": ["applicability"], "tag" : "resnet50", "label" : "resnet_tuning", "direction" : 2, "arch" : "gfx906", "num_cu" : 60, "config" : { "in_w" : 28, "sources" : [ "issue_1760" ], "pad_d" : 0, "out_channels" : 128, "dilation_d" : 1, "pad_w" : 1, "conv_stride_h" : 1, "conv_stride_d" : 1, "fusion_mode" : -1, "pad_mode" : "default", "in_h" : 28, "tags" : [ "resnet50" ], "in_d" : 1, "cmd" : "convfp16", "activMode" : -1, "fil_h" : 3, "group_count" : 1, "dilation_h" : 1, "in_channels" : 128, "pad_h" : 1, "batchsize" : 32, "conv_stride_w" : 1, "conv_mode" : "conv", "recur" : 0, "fil_w" : 3, "spatial_dim" : 2, "fil_d" : 1, "trans_output_pad_d" : 0, 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b/src/tests/fin_input_find_eval.json new file mode 100644 index 0000000000..3020f523c2 --- /dev/null +++ b/src/tests/fin_input_find_eval.json @@ -0,0 +1,466 @@ +[ + { + "arch": "gfx906", + "config": { + "activMode": -1, + "batchsize": 32, + "cmd": "conv", + "conv_mode": "conv", + "conv_stride_d": 1, + "conv_stride_h": 1, + "conv_stride_w": 1, + "dilation_d": 1, + "dilation_h": 1, + "dilation_w": 1, + "fil_d": 1, + "fil_h": 3, + "fil_w": 3, + "fusion_mode": -1, + "group_count": 1, + "in_channels": 128, + "in_d": 1, + "in_h": 28, + "in_w": 28, + "out_channels": 128, + "pad_d": 0, + "pad_h": 1, + "pad_mode": "default", + "pad_w": 1, + "recur": 0, + "sources": [ + "issue_1760" + ], + "spatial_dim": 2, + "tags": [ + "resnet50" + ], + "trans_output_pad_d": 0 + }, + "config_tuna_id": null, + "direction": 2, + "label": "resnet_tuning", + "num_cu": 60, + "steps": [ + "alloc_buf", + "miopen_find_eval" + ], + "is_winograd_only": true, + "miopen_find_compile_result": [ + { + "algorithm": "miopenConvolutionBwdDataAlgoImplicitGEMM", + "find_compiled": true, + "kernel_objects": [ + { + "blob": 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yMfHxwTHBMtEkclK9GJHDQz8/JiRf75GlCLWn77Hb+JhsJFuiN1My41GrzJ4kS+O4jRm6EtElTQSkCNwLq1YEey7dSIcWdck1BU3dcxzT8WijeCJJJxCuzGDkjZ9VcjBLgJchVtTnTladSFg5e2bsFpabdtq6JrpxecV5WJegngAmnDgRmRiMxaLGueRvBMRyRBswsCHq5UyFdm4aa9Va3U6dNEnIiqKoqqk2DJjvUSc3QI+JFM4OHgey1JjiMjlqVrFULLtRQLscfg1vwWWh4/tbP2eHP2buBXTg8cFKPh4DglsUhTuhwvqgJUBOyKeaXb6rGIRFIhFFIo2bPr4dpILBlzrT3/bX3i3/M5HA/deYWebq5ja/fWzfXCPYNfShAOqZwxmbvqhfCiiKKF+wTsHYmbEiUzN+Sr9ODnFoB7D5TIfUG4Ed1Ml7j5Oxh8kNLl463RZykv3KHZ4Te0X1U5b/Idy9eqnAQz+n7TH66qWnjdluSOapAwCsMnT4vDBLTwZTrW6lVcDNW3l4B2AJWIkS5SA2djSwGPY5GYmOPRDOIAkcRrY8QBNRDfYohr8XuPm8vt+ZryTHuNkVfFYUlC8O15S8SxLjH9SO2sKGVmqIm8w49dNPGv7BUXrJpjFi37X3HyNgE8yLZXbWLaI6I3PFymi6p4dmzZs7aJFv6l/f7rV3O777c9Tc7rqeO/vO/6rzfeYVj5F1UMrIoJlXix3sOotgi+Xi/VdxWvPZZDhrlGfAgwSw0+kIelN2Sbs9z3McrV/NONZpuaPZ96v7257EGpcxPweB1z+tZHqF+pqCml61OBiqCObcifHbM2OSpzNz6C40LWa4BBwLcbSRu5PR2lmj+9FJqUHuLzOXjljtAXfAvlgs/2wX3paBRnOL+A3IeMIsx07R4da5ONKSiEzA7HhNyRVrcI6afcgr2gVoFECwgSGNkcozutRXrYYKMnxFmFviqPh+Vc8UQGlvR3L0ukwbna4YJhgkgCQgSwwyE5ivcAEcWGQwd5Sz+9+G2tfVzX1tS+1ue7HY7GWtdbmsji5WkznZOrdzuBbtzjJBZIKIFkgt6C5BlmdSk69oQVX9WLuIc2OOiCogqIKiCxaALPn7DUgJWHTqUMQn2FBz83iyaUBrt0G3F8DXwNvhr8GQ3Y7rtLLv2zp1qIeDTRE29Xs9p1iC0Pbh7DPYe46fTEWboTzoNW8iIgtI0dnm7LTan3Yei50myoJZ8QzOqIoi3mZp6HVvY3Mhfhh3ypJJFQXzwQOa3cScTYo2c7W+1oblNINjG+bZ6uQGqou+523V5SoqPJxOzcTwyZ/nQ0iWWgYZuAWgC6rQBeNrbkFhWKyt4SM1jkoxPjmjwKYoFihnhgAhis+QUZhisRHA70lbrfHbxOFRZdh1R1GHzRZ6KfpomKL6MNYbwlZIOH4Tf8sgmRx8BZeQYCCMNsKjnHzK3aw6dfEzgWcCzQW1BcDGr7SQW+MiuBiVpHaaJWKmLhO4zc/hIR3oBy2r67s0hGxFElJREYiJdAwVhVJ2eCCsyRt3/nHkAmADqAvHBOSXjAsHp36KMJob+kkkT6Tkkh689A9H8B3DGzCVOxg0q+9SgFaRFZpMpCRGSiAQ4SFBIehgSATkzAkMLARPSTimwCiVQEESe3db+oWOjHwVv6qJUYwkK+fKYRDAJCwBaV4FeBXgV4FbLBjk4WP9BDl7CKIP1KT6iqispo7Ch0TDBLFW0JeYGzUOxil5xvGTnpNLSfomDLM+rTLoK6CugroLIEg+asf421tCmQi99lipJH3MlgjFcRHkD6SFUFYkzngGGEWWYbe6jnmD4QmNJ4yA63j7GZBpVTJz9inagZ6GFhjvzaGoYhBJIOXFKbDYNCvaKVPtkYIZSqBhkPUFBQSR+xhNBRgI7ksChHQSgMALagtqCgfh3+QqTLIWckkc+pZlRjWqifILL1Zvxazzw1h0cozNhOKpeEZdQYvvdbJqmghP9Vv04QARUJ7yGj2NpONl8qtsldhxfKsqnsGIwRgr4K+Cvgt9GtAVrAqhl2QckI8Kmv38N1MvFmqp1ZwZoXiO2RuwWskb9anKZRdEazLXy7IhFNxqpJDPFVWSXJKJFmKLMIoUFSa1SLU4TrAgjStQox8jm9xNw9Pm9hkvasjz1+NxG4mJB0ZeBZwLOBZwLYRjZ6FjXkgvpkMDJIpvaOTu0yHuyFigcdcCGFQo4x1mMWSYYxsZk0m1tkKfHERcZ8o7ITeiQDADp8pC1OFhCYaIiD19JkrWQKViLTloUFpq28Al3RlgssFlgssFoUiQlFIExiO2bhq0m41OTbFCBZTBdvFrBXK22wjRWAhEl5TwkeluofPSiHIaRyKRXrG4zBw+Wi6CugroK6ChKu3RZRsFK0FJFYSE4sMox23HhySQwuzEyNaJF55CIJXkRM8ZVu3Q4KwTGH7Zv5ZE1HVZB6BtHIH1CZjiu58HU6LX+mQOgjqvyUXWgFWirv2Ekii4IUNGwka/wXq5XEAGmicqSRXninRipCSQ8CCZqyI33hqk787AwIMmGJD8vCmxRJGjKwlu3ndnbOTEwgQLaYEfREQfusmJURBMM06dWkOZl3IjkygloJ10NSv8Ck2SKQzw5vrFzxROIZ/c3se433uw/WjZeiq3pf6tXQUz0b6/6WAtw7V1/R13TNooPSJIT7pMxz+xkrzaXlVK8/Gcrm2fNrtNrNHXehs87b2H09Pb5en4dDybXJwpwmsflBc7Oa/XR8wjukZY2bC1AuEapgB8sruEl1uovdgDK3I4jdLMa8vl0uh5fw/B8LwOh8b8f0OPxuBx3IXakfkKRE0opEQslEjIMg2gQ1HZTm+wZArmgmXacKjLm4pKSknbCOzLzJZg0ihE4htSbinE+BS8mkAM0WxuASEiDZPp5hayTu+5cKkJ6DdqLXO9Z8u3HX5FrnYy7LUIxnimiPR6XeV6jxua3nGPtQrJQovZSmL3/CTroSCHWWVYokCW/r2/ncogxv/yU55/GuLyK6tcTpizpPUQAQpFKYg3nHhDjVqvVEkJI9DSzdWgYa4utL4Deb4RrbmCBBvFsOob7sdAwj0oSHtHG8w+CfX+vgQhKboxKAwlARASPaZ6LVDK5eqSLPe6vUYJbzKgkhZn1Ksol5He6xO7FWIcjmHGP4GHaEOV+xKmugkGRm1+Ll+Nfj8LSSqgo1LUW8B695c84K6gz2yYxj6da4Z0cB0ZV1bUFvpBelYaPHI0nv+ARRsH5YzNVOJZGNkERYyBeqgrRXXeDpir5DRzdTa2KmpxMWRCeiZaldm+0oEggXbiJC3Evkpz5IPsUpz07YmB5gHmZmYTMkbubRYRxHOEFxg9xyuX5MqsscD3mwYuEdqNmPnpj0f7TQthGrWFUBXn/VndZrzXmvJypy2FWxxF6XpBJ3fp5S8ixcB/G+y2lIwcBnWB0teB0Bbi1YEg5so4kZe5aHzncs+C/EUIPMXMb1gVIF7qCM+LrUadC9zpM0tbaomY2b3ThZhm50/8cy2i0iMeUFUHo5XFRSPHWNn9lsowAmSqbFal864lErgK/LRpFRmdFlDgo9mS21pbFGjf76XvaxOm8fne1Kx4eWvRwYJlp95SARp9G9fLekj5SpF7uSA45yC/O77VVICKEWO5aUp5PQX8Ivr7EeSNwCM+ybk/uWx6JwjlDGL8qwreDlLP0v1hRvq7CvlELvORvQEMUUHgxbvbSUbE+XQ0OvRSlIKFAYcRDDp9tqO+YTvt6tbsK8O0WmCdn7k9aQ8CKN4eL3RrFmEZAGSA0aszDuWjAqbo8V1BEO3hP47aq1z3wAP69g4gpxwRQWFAAAAONLMMUgYEXBoByWtLNimCY4OnICPd9LxC8wxLAD8zwIIEOEdP/vheXV+BtOS9v1HIsYv1XY1mo5DVcr2Nb06qkpznKk5znKdKSfweU6vkNvrdqY+1fv+xaRMX21KZrrdsI8E06k+QStWQ6yt0YMj0EBSEGw0GJlJOzGQMDClxPWkOvR8iedt6zgCfLPyAA4aSgVtmBkREyPxYTARwRYYpJehRj232IwOYYLjmmC6Q8DO3QbrFMTWZWjrJf53Q67xuH0MypM5Ox7jW2J5JelndeubRo9D/JrHQ4jqFxl2KrfME/f1fzF4O86rrONOL7R5euTM49aTJTieR10ZgfLb5fvX915oQK7KundCU2/YB0Mp0riL5/OizzR7Fkb0YWbyny+FSvKjvclmdbdZrxOKmH11TrIgknhnKm5uM6UavotdkSQH/ICahlq5xjC/64EG+/thvPS17pQWC3EBEOYBDMJJmEdFkL2gTAMC9IHOBOHIJdc5xRB81qucdK+hyPLRXIeddU9fN5hOPPKgNCBi0DIGrvF2VB8sO9SoBR5F7ePCnZaqCayaUGhDKTgyeqUhlWramWKgsDBDZgVYVkiKk4NRa8+6BzpJYwFKNRhi02XXMb3Tw/KKY+/2Z5mQtmT1CUdH8wiNsKPjDDcs8EJhpy0HUJtbb0RyoowA+tfmxnpgEddeuxxp1iiHcZFcytKZ26eHN9MfYSGIiWeHruJVHEBLY1jlEcOrHT+mXe+VstHvzkbYwDMGMcE8U/0LhdzNPuoSWotuzPG8O1AtJVu3wUA2WgcagMZUyo7QzAhM3hIaudto4Ug89gUIhhglYiiupBEyOh8lsUbvN9rbb1/X9EyOquhhCrAj5QHhWjuuSe317IH2Biy1uq4U6wmBmWyc5mG6t9Alju6SU3dJcuPaOIb85MctNoinYWYIhx3cd3Hdx3y7NaF9KiHT98d6askVgzz2VHiiGL6AeU4CdiigcrJyGoVNUJrslduJXS6UGgmTHImTIOBWgQgLP7xX7dzYyjMkRsw0PLoX3GgUQUVGKqjD+3A9Pt7gN/0cvfhzyqVRd3fm1X3fVxD1BhGY80118HB0d9W09SrqeYvDj/nks8IO8kNMocJ5R0epBoNgqsUwZqEKDIhdmTko5SQ2sQuSvefVC4EhTrj2Ra8P3vj83J03cubycsr3v7ne8XW3+S0TK704aQLIL+K3A43d/UFxzRblTvEAQc897usjeI/7LujXsEQ32Dz/ZLOYfpFo3IcTPO2+jQ9o+QeaOLBhPGi2DqxlTvJ5VP5CUW+48S2736bA6ZQZ4kGW/bkmlJlSmZLRCWLo3bws8c7MssZ+aIO4fY/4GmIRrAN8IpG5nbrZZqZTxLRD1xj42OMY5QMf0DXwf2QyOY7+lN+Pt5O12tM6B0pRPHjD1UTPB6dMWZ7Eda4KA2xaCbn0ME5HjetONelFWj18VRv3d3d3d3d3d3d3d/tjoSEhISEkwkwkwkwkwkzDkJnTJMkyTJMkyX/ISSSSSSSmzMarHgbhYr9NRmYPHHLE5vlwbYTqHzkuUBqTuCy7FmOPmGiYKIeEAuz4yyFjBqBkaIhbm7MUcgnjGE0cI/Gd0yR9HiJkQnQJaNEhyTkcH3+s4+eRyekriJECHG095Hru3tu70CqmFhWTNEz8h+g5BwTkHMjBK8popbmcRrE8IVMqaccOhsuWrVoccfLW8ZSEX+QsjAQdsfHaFm6jxkjxcGGGRIAwhDJTkikPMGJwHCeF/+LuSKcKEg7zQHrg=", 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", 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", 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", 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", 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", 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", 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", 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", 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QTHLjryZZKJAvVE4WXbs9HnyWG8x9/yylLCUhB0XBCVS15O7F6SLthDDCTDM0ZPCxnSV8aLXEvOxuN3c/VmWGK42YkXucALbgFxZOJ7pKqdVOB8PpcOK9irfFY6m0GASzYhV16AB6Asjve/+VO4PQm0OnFFn5AR2uYaVCBPaaFJ/KrG+0xvepPeHoNPXLyIthZQQI4txsdj3Vw8Aj8CieGJ9lDjM9NOnTgCnAFSIneGU+Io7AqXV1QUV/aBWSDyLspyFuYeaQdwiLHZprZ09ijrVZQxHTpCJAIn8ECWgRxtumsKXoXrc0Ulm+KVMnl53Z7p6HPSX3QkcfxSrWwA6/OPO/Eu4wS7BLuFWwM45We6DJOy2jmSQw5bjLZYeND5xkT6rABOMCbGJsq5SVar1bO8JeMYzsz+zgw4tDWVoOSOIxjetp31ixXEsJNjY21iWrtvG4AzE80XMeyfc4GJ2FOBKr7Dhvn35yd+zJjY5Hzu++45G+9X0/F5XN1/Lm3vBf1gxuDj3t4WQPuimWhjpkYxLgK4AuaFpUDCpjOgkFQoFQYKhAVuWTcOxSGXguMbp2vItcbqFvukS6h31ub+z1aT/LFYxcrSkAR2NAdstUYYwwmGC44XNjSs+VKiin5Zl4rfMBwAMLbHJ8IM8CR31qw2jVBKqHIWiBO1HgalvcuvReoN4Te1Lap8d7juY+Mqfc3CGnn8jB4tWWfufubcmOpG3DEF2byTpgSHizvM3U+Jc1CtJVwzpQTEI475GuHrrWG13BItMpWCOwje0ASKESU1wAUJJhsYJP6NdnM8BXf2olLOVDSAaCo8PiZTOWYVcHphGxDlFiCRt2Qy7Jbt4cK/t46oeppUi1DnyvO2iXCLs5ShT1OSFHkRyyBqR4jxpt3d3d3eKKtMtNX2rr6DHr6G0vtDhRdFs+Fz+yl5bxo7IpUIZUmDUr3EwFcqSc1J4D2MznckiiVqx5Dl3lvnKstIggyEyCDIMzfvwqrdqc1YprU/uN8nhqzlDutu9N1uu2zmvsDJNRUslSo7RMBaUEVLME4ktKWKOdew3G6kCjYrAez68MhFJCd3fUabqHoNbIzmfTc5yRW3oL74F7ILWf4AvilQFCcQtzm1HiqU4bqodC7vpRnSJoRMC7bTkx6rdNF3kd27WsglkEeBLAJBE2KQb4Vmrbgfp4N/eU/DKMr0NN2QQnP44/lc/4WN3u2rgq4KqCrguLKR5oAkNJOyNdm6GH6mswOjzXRce802/ZOTk08DTVqEq0j5q2Ok1V0d7WWTDABMAEiCwgWxBahhmNPkb9oAVHrR+XBowwzQU0FNBTQVqYCYseWqYCFQuKZrwjihHd5c2sGKAlOmCexqAlQE4IsIExbf3nWXkR2EOHkSiRxMpUXS+b4/eokjqg22rqOr3HZCka4XMLCQ3cnUkkTV6p4OB9jsri+za28Ra1apbvaxuMJE4WZi5+t2L2Dw4H4INBT0kigL+AEDlMnMzhljpWOlQ4wdK1MNXLdLWcbMDJq4qO+11/ZSsrNJKl5mVIac+bqwC3bviua4FrQWTrQX4u2ygVWldqtVRjsd6i580xaUGOBIgL8QAPIhPYIEhEIw98n6A/MhdrF9P5F1eRSL46FfULzkT/Hhaoto0vjOJGxizwDP1iCYPFwyteoNBAfDzYkvmj1lW/bU4C9uAVuAUsArYAqsiBHSBXQkwABcTHeDWEwM3NEUJiWVBzUT7UY6b2LqtO0J8TCu1YE5JYQOFeqjK1wILxkjWv9g+SCYAPrgvxgTkl0QVL83AqThQYGekkS58JJEuDlSVm0jUj4YtqM6Gmw8pKgsVFeYwGrRaRn0UEQJCpaPj3LQF4mwSGK4i9SUGCwFWroII6e1WqzKX0xYaMOou3vES0aoSFgnrsIgjCQroWeYALABYALABRFMwyULD/jQ5fVRNB/Et37DMmgQ9gJxIlWTJBZmbJLvQDasEs1XO+cvZVIkVtqY9E1tCeVwVcFXBVwWEJB89YPoY9MV8hFrMspJHKkUiEV8izOk0kK6LL2uHkAxiMw2PjdPEmG4EzJkZ0MfUbba4TfOVTU40FOy6pjWqFGx4BbNcNtD0MItOZKihViWtr1Kp7RGiGKqQaYTtSoVCoSR9ZCbxRcI7uV9QjgJUC4CXAWOCjPwaOGp7LDWQkkfAoVJKMKrQT5GqPXbeZdvPDUnQyRmas4ol+IxaAxgPacjSNchP5OzThABHmS3kND3WDKNR8otqF4w4vyjJUtgssEIK/BX4K/BaEK1wqk6iGLTByQieHq7p08tl7QUmi4O2C2Q1SF1Jr0hfoz5JcK4jbMt1iXohF042qSQzxRV6ScMmkfFUfFJMhAykgxHmODs8AN0yfmBgy1eXDrE7HPz2rCME659Ndyuu31AjALHBY4LHBbtGDkoWDbSC/TIYGSRdPZuHr0yHuIK0BvV28ECgSO6NxglMiGMHBZNIxqxcI6jDxCRNbLEdZou/FHHg8bYIujm44tWkkWLlCg2Qgs+xMt3aInnW2b4wEnLMQFiAsQFiAtbPJBJFICIsu4F8ba6bfXUjIJkZXGCxbKlNcPI3iM1TkIkW1LCQ9JsJD51o45DSHInl5dmuxRw+VCwCsArAKwCgKOSimjeE+oE9GWEhQZdqwjRkiEkhi50TRyNaOCkhFLckVs8XK1aZtVemCP1jZyZCabpMg6pgOQPqAxXF458HXU1tR246t1+dyCVdkBKr1ZyhERD/lJgPIKgUIhl8BlBQIAGyRLV0gKUwUqEV0JJDwIK7XiIX3hqMrqTp0a5BHR9Tzp1sUuaQXYTK9l/PvTJFTBBerHUdJIj14JwXySCvJKlUPf2q9JgpjDAw5PiBQsR30HWFBDyE+hApvJWcMFihLCyJJbEzNi/4zbQ6y0biNdn0zTyunG9PLQrHH+Tc7fqj1zAvBLgvUD5w32ctkvcmzmsib6GPuMe1tvJ8S18zeQfLt9zssHVw+ZquhvvBlZegE8+1AQ/oPK21XEU7bvy3/ivuYFuDSJ4e0UnCS09FeCgGV9IcQuk1zdJy1shZaQ2232cLK7yEl+LvZdMDlINvDKrfUEICCSIFAVsa6ApIE+Y7JL8flCiGvVAnVSxacfZ4NQMqpGZVCNA8d1UNdR4QimCL7g34oYYM4Dc/naYfosC0zxzygUlIfLOFolCiep+TGMaRfw3GGzB0kZskFplpH6yAdJXCOFMDFSGoajpUv4maz/E54xZXamDGXLwRl/IUBiRSgGcgWoMSQm/i7fxsCIJcr9FiLm8wsxdnRQ/D0eq1IAgEabM9F7XrVyD4LdZiwKt1+Jk0ZhXW/28nyW+V5pt8qNGQZi3zpmhwtaVTSgIOU4zK+0P/f/J0ASToFtA8GcbsFUjP9eNoYOj3ikCzsrFITdTDDsICyy1amfkQslx+BJ/ujdMgw0jRu5bKAhz++VhaSglPAn0f9xvnR8/dUAmTApjQYwHLVrjaVUWkG8RONaBRl6AjdRiNOxv9NgWo7hPRj7NXbe3/MJjmXh9vi6mSuOYdZJpojCYTPGubgkcyW67DibLYZGBsumxZoL2PVqMdfP+fbMNtuojVbTSagiN5C3/9ONkeXpQYwDzMzMJmSO2r5jCO4c4QRMG54XD9CSqjGj4O7LdY8IbFfOwPQ/PaBqptLsVBCv3+zK2+9N6b0jPwd9ahR9Jvg+CMpa1+qcc06FIOzZ4nITVDLqui8xdjew2M0nfvFa9qIGayM4jhEpOcU72u3ZzpwHYCZ2gM1X5AScEznXzseWpT2sHXT6Qp2MJOXcPA05GzNHt4vevKUzAJpoDMFicbAZMTpzTdp95spoAs1l/RcX8+xfB9pzRX5HkYjsyq+FgDCzqP0DL/NEiNaV/Lmj5YUHC2ewE0ZFNv4th20gz17rD5HZp9ezcvytbV+W7Zc7wgjRvMMY9Ly2ZAmCQI7QPLCYh5bsZTmTDwLOQy3nFHCHxjVX48wcsc8JaTZWv2qTcbfNBjf0VytXEvM2J18ghhfx/Hiy46eSdxTlDu0UpSChQF7AQQdp4NhvhvEz8vCY5Cy8oKGonfddoKFEHT9JFG0aab1rBhZMIDDAuFyRmjxLhUGWv9n8OaEjxbR/LlMLE5zrgPK+lCHECbIAJ6L0kVf33rLpwNJM2/jZs5rLm771hRftzs2am83GmO/yomdnT1JT/++aysbO+x6PrtlpUcP30I0+RosnK3NkVaqqdKUnVSlKTpVVOPC0200Wz5LYGPsI9n399Ce9szTtN+sBIgFsTL3gWuQKCfstdrwFA2AIAyErbeG8mJfbpkDAyUm17kg36PWlnJ9xwBLkkvDADuElGV8zAYiIqXv5J4EABIhHKVUI/uX0Hw++GQ278ZChD5EMEgjfGPm1jgGNHL+V2Lv1N12NTOOMPu8nkd2TDtuPP38gSQO4+BFCQwliEl4NG+T5wL+cXrnw9l6Ho5LQJewolOlSxm5Myay2rp3zETq4OlwmpaatbAEA4kG/BTAZCv9kBiEytuAv6WOvEUNV4j46M7rNR3/3mb5bozid15/hf8VsZ/1zoUwQmmiXPLsb9wp6fAuYMb5X8mAmonfr3XcjvlLB/o/8aV12Wtu1BQMUmgSIYCGxJNiOnaF44JgMF9EIgFBCCfsoN6MPoKufKSbuzgl5yVhMilc6+VpKiJy5d1ApMEXoJgrdpvcVEYZEVuoCqCZf24k6XirkUpHNRUKTE5wCcVzmJ2MvqFqsLQgkswOwLCZKxwDv3wc4pEWrdgCtp39Vema1TOM03Abw9WXeFgJuIPtD4uHuB82go0RpmNPGQlFymsikh4Ka+u9GZAowwrlLWFXQgKc8bOFJVwxHWZGlOL5DE92vn4nsDw1eCS1HR93RdsRkCpHRPPJwbEdL+WWucqxUPhmpkE4wBjVAni66t8Y2e03Q1Ftm2OuAtt1Qt8wFhSIFUCLpdIUkgY0vBYrMvobKkg+KxL4FYiBheMssxkgsaOi7h2hvE2e3yPd93a9Yw8myF8K8Qj1wOhWObwT/Hu2QPsDFRr7LQK8xEwbetguyXfdJLPd7dlK+8Pu+SyKqusiMmuUr+IbdZFooVlZBgLUlXUXkiUoIiCIgiIIi+SvR31TIcYBcMomWAoprKolUxF2QROkgpaqciCwpMVRWqxrBm8G43gmCVCkUKEEqFCRu7GDGgvPIHhL4VrASbJdprkZ/UMfhKQxDGobZB5Xr9nye/hsfEyc6tqBGE8J4HaqCsPmeMxF6Hw1MskluF07489VQn0KJNDh96PRlgXrNJF94ldiOV7AaL4MzmMakiK+qh1DNr3jLVxqbq/zPz+AOvau/dIphCGmf7uw01V7mJkT+0ye5wsPm3cZ+8Oj+iNDuxBIgCVD2YOlrrz4gUMzm4Ur5ACDjnK1+Hmo/7LOdeUiON9k+X9Yp4x80qGWHca05Ph/Um/2H5h+UOL0rPGxantoSj8OWXZ9Euyrvuve9TsuDcMDuvDd26pQtUKNF2Y8SGmaWFZGviN4xunO+tLHdz3n9JoCEbgBvKJ5lp0WjGeB4vCDbPBiQwDBgKhjHGdttymHQnxd83ja7+9vLyMPQFYRDvL8xtCllBjZjDeHzu5LJ7JBSGvPsQTxpnjbk8u4Vupm6lXL30RERERERERERERHfkMbGxsbG2htDaG0NobSIJNQ02m02m02m/9ybbbbbbbohGmNJIXa6GNhUkg/7l4S7bS8B0wu6PKM+ZJ6k8EWfhFmGeKOmEa0pFc7c/Kb0WMM4cHTanVnuTUGiZByRiHZHfnhGSeX5RhiGqAv6YjFji0Zo9svZYbuHmZLWKYxwYKFicnCz3HZyLWtoPNtWmeHGXgw/UOHHOCcc2o0SriyimL5siYJ4wqkqlMLN9WuqKKBa3ijeKSAe8US/pIHQnDdTfkSOEJGZGMaLQDEIaV4kYCkw4HTwlJH/i7kinChIBLNt1I=", 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Q4UJSBxTi8V4v8BsHDCFiGIP1F53/PC4tsUPEycXSeA4OB4LJHbg/5gPw3ZP397J10RnyaV4j9T7enXmMzMmZr5CD+EkPMQPJhOf/Iw/KJ658k4o/vdz3XeeRt8cB9sPjE+NEsmi0dGfxj6IoesepSoqVJQ+iVE+iTWtrK5Uqql+R+0Unbg+2AqRmyUnsQsIAmhEqIgWjwrz5cdOoxMOqkHdrj8rI5clP0C4AKBRQkkAROjgAROTgQAIaSewHd989V2VZ9u+rcni/rvOB3EtJ7/3O63DHdeqmM+oAFlyo2tqbVyPo9kDuQFfgpRlSU8RKHcFPNoqUEcCOHOkeW9JqSABDYvPgjubNI00YS8L15L2V06Bav0hegpsSUKmEjxeT536m1nZ+/dFotHRmj1elwDywemAbuTr5M8IYdhtcadoF0XmYCMETS9eSIRRWIyrURqF4ANIAsAOEIHAuOCoo3Vuj2RaJZErlhHfSeRn/I/PwfU0sWzVVqzKJpNPOcX5N+Yca6jRe4qrwqqrJVUto9zxjAMwBWWj63ycDnGNc+tksXlNaPIve/YJDhCSBE0DRoTS/CY4JEeAeBvuGM0AgAAAcAWsdu8jBqW3I95b7v3cNcz7BOw3O74kmGYzTMnIAiEniHiEqif5Im426TcPig3YD7KdPa56TkSVAF5T3drtDjONnl8ugccBbTRpHiTEnJkw0tCCoiKbRBWYLFPAL1+0rMr/XOr5OO413iv9y/ctOZZ6dHRQLdQJhNMk9EH+IAAMQAAANQRJzpEcQJHZZ2HwcD3+NPQ/0wXudrqb68TzcrIlBqQkEkiSwkjiJ6CiwCiHERCUALL5jJnC3nbUmZxqvKn5aY9j/ujlt/3tf5jQPAmE0yTvgpcBaA/UB8STqn0H1E9amlJtVyuUhSBuyfh+npmPl7bJ5uutMfwLHB4nC5Ot+iXlQ2DZsTaoDE4hnwARHgFWkTPe5NFsN/+t40zJ8zD7j+rxWLPZ+fM/G/mX04nGfrg/XAWGc5mTDyZLNsJKyXvY6Crzvyc5nZ0zvc+d7BrczRl/T8wVSTE+Za/dy2XlzlRMWb9UH1QHwBh1ZPvKgxPUf8ctl5cw4bpLs952/j2Xl69L2Bp9yDzAHwL2OTA2pK4ns8xnVv38xmZkzP527aDv5LxMpeXr0vcVdcJ7Qk+eAodDJnyddR7dvHiq1atWzCZjnsbHjmPfvZKUpEeBbkgHuqgg3Deq+CCeI6DtF95vvIPyxoAtWwOd5sEHtwHbv2qaH93fg0AfzUAqBQE7TOThAJwi0YE0m+iFo+kBKR6EH9ZfrRUnzatFZtsVSqpw5PvaqGzsemJXrzXtaABnScLq5IvXbs80l7qmY9Wg7cBrIMKQnKJN2qRE/nbeTGkmPHJFTHQmPHMzzF8INC5Lh8jbXr03hL+l5+6SeKg96A+18T+GVdW2n6T8V9c/jbLbS2J/Dvfx5vpYJHMLcM3CvLtyab3n/idI+jsT8mzicOTn6qc42Xxf7e8njn93MY97N701n8CwyrdUt/622+rwOW4bxEHtwHcf9ZBEwUHjRKd7DwQgVi0Wf8WPEAwE2F3EJB2mFMIY6IbNUJ21ipvyn568gKuxXLlyWtTrFHA3e/383/wt+Tu+BJlOziPfL+U+jMGCYMHtCfctMvceEg8IBpfVkz/TOHC6DpmvJy2ksiNFXDPmh9PHozR0tSThXxdvSTkOR1Dp+nOnZrp+bMbqXU32UUdRgMB1N3QmhvMsm5tNLUVvAQdp4ADzpNq2fPUbUlCXW2KtcUkVKIUSkKTXw45jthPPZlphoS5PPHTnDf7FR+kVq1EolFFZUZqitUlZYWLFEolFFZUWKK1SVlhYsUSiUUVlRYorVJYVq1ChRRQrFZUrUKFFFCsVlStQoUUUKxWVK1ChRRQrFCoooqSoqKIwcDAiMHAwIjBwMCIwcDAooqSoqKKKkqKiiipLmGYdL1qYgmXpru9BoA7sH7QM8HlA70Hrwf6gfIB3wPFB9UH3Qc6g6VB6dBrHoUHsEHaoOwQd+g2kHVIPqIO6QejQdsg+o9qg9qAwbGwA2AGwA2AGwA2AGwA2AGwA2AGwA2AGwA2AHyAGyA2QGyA4ADZAaADZAbIDZAbIDZAbIDZAbIDZAbuIHq4geviBwUfEiB76IHiRA9bED+CIHnRA+5ED8EQPhRA4sQPuxA8mIH4kQPxYgcuIHqYgceIHQxA9nEDlxA7+IHRxA9HED48QPWRA7mIHrIge15GA6l1rhK1cdHJRaixVHNg5ICxJWpFxhkuxWpabUdW6Y3iaOdNfep1P1U61PtfEvvxUzWemMd2EzDxiszMyZnETM92g8YBz3Pf9IjyJM2PnyU+J/XEVSPvP+yjq617DGMsYzfWn5p9D9Q2YR7D94Uf/T2xvvjGNUUYzmGaFGjB/oOgeq5FRyeP5O1XhQ2dmbOymLub2/37fcEh8eFEO/StNvxOh7C6W8EpLm4J54HiqUG7II1scao3PHcHz/+eMbfZZTyuG4EQ+GOfOc/BGe26Z5m9l5KDyQFXo3sb3NuxJmZ/s2/k6XWbE/57uTbSZ2R6Y2MPWGTJdsV11bfbzb66XU/oTZYNNWZiSWkANCFXQEkej5CYJQkkAlzzg2cQZ7EQ7OliWJbcMqWUspZBIVEVEVJENCj4onrtNSUTRdQ7bFSmhlzQ1DxXvjyUHkgLt+d7UbXZVIR8Ae/PfE97EwDjDSIypRFKI2txr4z4B8AnwCeSvgppqWmRc2XKliUxKe+ToG3qyRNmiTc+1/+fqz7XzejS4MwbW9dWdDvt9N9Wtv85pQPkFXXmKksRgy5k5l7zyKONPpZprlZr2dEbaTSTtbfWDUCaRvALXS77pa6669XVmrlGr11OC/MQfmAMDQaI8k8knOOc5yVKqpUqqlSqp+Gnap+3M9XW0VeNsaK8Nr09pS1aGelioZS7uliWlOzN52V2WMXiWsdKS6283hgf5DcbibjZ3DsWe4exq9iEk4KbhLp4kZdLI0pPWc6lvPe2OSlm34NVVWjozR+m4PlA8oBRfht0k3KKmq1M/8URYDr6Ek3Ulmk3VN1TY/puTV47jxGtPEV5szYSdwhq6s1dZpMPOuvbxN2Jqwohn7qahpSblNJNjSnLnAvz7+hoTQ7R3TpMyrCOB3Xa+Ug8oBrN8o0W52SE7LmNxr3UJdCNyIqSTmBm5T8rNtyURrTXfhdh4E/ohJamwm72NibGm4zc7PW7ivdUma1uU2y/YajepquMnqrUjQmrLnoE0NCaFOE898dB8cB9ATFd2pP9WtlzutV+X567imZpZDK6Hop2va12hr5mZF5gwTBzhZTccp8dB8cBxO6Tn95qyXziJ+BzcmMx45j67vW+Z1FMiU7ub9PhX4bZb4FLEwl/6EuZcy8FrgN+9uTxShKFCUKIoUFCgoUFCgSikUUijZcVaKtwpqybvdTHns0zMdGO+0KG/Td72lFLzS06aWYVaVUlKGc21MwtJJ5srO6ze2xq9GeOlViZn87Tnws0RiYn8Wb/f9FwfDAeCAlAFAEt7uSl1msdS3n9p6P4PP2/g+pswgPuUASa4wzVT8xNFN4nYhM0n8XRJitskQNlOqSJSURIK4VJEygklSIoQcWo60StOQLSFkc8hyUpEikSOuCScSxKS3SkUwNAB3SFQ+UlA/kSwBJpi4FhpvD1HIekXFFFCJqqqqoJmZmZmZmZn40n6qbrdU9JDVEUhpQz4emzB1IjCY2aA1RPlJUAaSFAEbQuhbNE6k14xxySgZkOUjuAMjGwbsIvmfomVXCo6/eTxvA4i0kOhRjhbO9jopVadjvNadPldd5epM3GCp59SY0WFlGK3c1kFTtDb1v4Mz1OBP1dSaJv+Xy9ac+cSc6mJlP9fxePyU3fdjoENCIG9UkESd2aRO4iZ++3I6k5hNJaVMpRrC+Vts9KW4m+7InMjk9i9VECjAL0cBLiaYvoqDQiBVREC4pCQi30kS6hxbY46hWYmcrKygzlabUmjKXe2e2atkKnAwopZ8+fJkyf6RN1qNQYBaC46O33UQLJIkzoo1x6UFx9UFzykH/lBuu4zx5eflCXeF3MQPe5kbufOxgzTGC9jQY0FjUUaagSWml3EQOQJrdN9vDdkToccVBoQ7ObpbBmgy81BmoOkxU6n6/qJzPbxA87uM2Madh29KKcPNBmgxoMaD5vTD0FIkyPLPm0U23up7uHrJ2A7rkfWJVeLd9r8VcU7GgfjXr7ufk7jcVuPo6uODbA2yDbIOPr45fl+F+XxyeN6WIFzRcPRjK2+yw4YUYZhDBmgzQZqDNQXud/Tbgwtwm8YoZcrmWHZxAzuFoNCMkmll/DpiqpXiyYO3a2OGOY5qagNy1QaqDVQc8xJjZj84wwwzDMrrIgcXXNRyz+j781ou4VpghgmCZ4LeeDPQZ6DR20mUvJ+V7qd0erN/DLmG/1kQPcvmntHGNGRu5P8GO/advgwwpObtdhhQen5IG/ql2F2VQjrogUkMxmSPfl4HqgPAXoXph7zeM5rpmCTncBehenn4gYnQA3C6P0Vcc9ZtfIs9RsK2HAs/ta1FajH2Fd6EA4Zz6m76g+c3UN58D9j3FVVeREhPMedjXTNRME0qqqQTyImhETFVUSmmnQ+FU9n3foHwPf3Hqyy8rGbwjlHFoeKlvnAVVngClzitGBMgjICXKMTbuiOwlsTiSQ36U5yLZRRt3ADog6VVb5mYZlVqpxGXg8ud4Tx1rZok4QToK8my0YE8CYhOJ33YG3bJAMeSAK74nRCDxEAN3YpKMQdziGWTlkDribbIEEyJYJuEJJXNpCBQCOVJBgSGg55IVaiYg+4UViA1SThNNTuASAASAhG4ipOf5uvpYNC1YAxoMiEQUgBmv0IBwAAoUo5IkgEoXTSRKJqIJFKWgA2WTVEsuaLrc3IJXCL9QZk9K9ZCRfiYQMEyaSS7WSml9wnETMlk6enqE3gzSJRKBZOAVIIFhBDE9LGFIXJyolNqGpatWagjGiiMwkll7VEZpGVJCTBk1ZmBAIN8xNNFpoA48SwADLoMIiCZOYALejdkolkl2SuSoLVJavadcFlCygYOHO3qm77xTsyZuf5/xcX1aVXcU9MNXCWOiXCO1qdplwOVau+qcGz0Oq5fJ2am+pyI027odR1IXoI37b72IuybAIiqI/PWAFuStvVyS9ckqI3smGTHiBFG9wu0//SSSmxsbHcRAt3DQJJklsWP5kRR8A4OgVkzJKSSI++hE3MTNBGDAtVUKKvH0Kk4Nq0aGnmC2SSyUJSgmXVBJ6e3EZVBjjbXyGT92S/vN/eA5rD0e72pLkSl9RebfQ0Wgd1EDe83aNzEkaMWxG5lfPMHg8XzeJWolx4rk3FuofumGDHEqeKiYvvljpllcWxY3rFjIxcwBoRxYlj4pYMWCWMWJYl0MRhkoyUlFJPS7mGtJlIRNeSkRlgV81fp9Jer7nFQXk9b1vJ1A46/AiGtmZZAxS4uKExKRAYOP2qoLgcC9SiGpqqC222ZZAhLi4BVEsBVZGLBd5q3cxrGeVv7bo5VLgYM3TlLdlyEdE3dnA2OglqJbAoz/ccE0A7cUYKuAlgRwpSYGpSxN3wKn0T3lemePbtbleGlV1PlJdOnb50ufW4li7AUZrkXHovRmYUYrl2I69a3JM10L6S9S4vJjXlVsJhs2V0Uv96WVDTRnMqHQ63lWJhZHXRpM8U3Lq3zObcO+q+V83PfN1Lydu2E3LreWNbTVqfqv3Pz5+k786Dp3V9bPN54z37id83ly5P7FHNvAY3M5tJmz8h62IHfHQuB+D70/k/iH0vpT0ok5l52j05t2PooHvMK5hdpfuu0sznZrHPu3sH656O2tZq6hp+Xd9aNJNzLvnDiR0Jxnxk3/0+ek/n+WaLMTlyYZBtBK1jhsQsFcRZEVhMHSc103oalSqqntMdbZiWT23qpSa0z62Rba9bgwx36o5sVkatrmXQ6uwsrNxWdVWWVl+s7Gs3FZXWV1lus9d6nJvjC5mJa1Lj0VkyxE39TaFG+NJ7fOa1Ll85L1hoz1Zi4RlTRGEtVUq4BpNg/w+4B8rncPvhe3SssyrvsDrKFD2ShzqnoVPTV1ctyzQcveb+c7c9pECiTj0nq4UeYdpicg910MccbM4ShQ03BrV1SU1YViSGiRiRpAUGdOid7le7i8vVBF7Recy/WHgPKyvS5lNycRXnb967bJ8Utn7Ltk9tEDuOlHTM/EapaiONDWItZXQ8elLCQ2yG5K4JLsn9rsju11EdrHQfYS4CIwdQ20dgOE/4J0slyI5nZiiZJ7A3MVDnU1LcpvrR0Xs9b1NFjYb3mK2axXNrJLK7m7e2b1vKuroZtjvZS5cdI3DirLhJUhJNlCNS/ENVcyk1DS5ozy5ilKUUTOM5nRFHWtSGUxyU4/t4gX18pQtA7ipWUcCWIsS7bdhHBrKOHLOA0WbIYrPmz6qWNXqlYSzGDJa/qOXctbdrb03x2xxre9RixjHGrNo4fbc0Lh844goyyO431LCWYy2I3VdnnjOlmSuUld7UzJLkm0evEoJtadJTOfC2ofJZTgeofS+tSUm2iNWF4p5tEA4x6dY/RXp0TDF8EiYJixLsBR3F8ivg3NjeNvi3MW/9GfO4Pvqqp1DrOzUUWPzrvDk3Alnk0s4kwb3fVQ4olue9txI9E6FUlV63pskvNSqwOmwTcwNiuRGDe6k5qI5ERvVpIW5PwugSXw+cXrXSybmI8xnrmm61ZJZdLiJbJxbkJdxipmswelSxUcNLA3rh3Po34o4Jms1rGbiZjIUSId4VIiGGSVgGFZE+M6BExlNiqR6OShKSUuYLIi6hKVjotOTR0HJJ6E8rR+Al2k4djFi7duuO7xh3NOIbk1G24M6kVnOr0evpmOfijm83I96lVg6GD08OXSyMod2zVLNRppg3d9UyMqsUdZkY5G7WaMFiMTrjOY6yhyunjKhvXH2mVKf7bQdhrnV3WbWc66is9LI2LBudhSxUt/qUNSMCjJkcg2+GcE30aEvx9Y0YS5PwMN1XoqbAyqZtRxHMz06TE485Tr2aVpQm8JS5wcuqb0ERsxFeuIWExEw7+mmnGtinsWs8xKrUalFdXCjKUpryZUQ28lg5ZmYDJG2/e1fNzcKNSjLpTFp5s4FrNAwnQL0SKmIu8QDzljIXFlA9byCeVJl58TdrdLtS9SuuptdVVWbGam3idJNCiUolKDQ0NDQ080BTqg5vRVVc1Hojw/lQ4X2qVXwZebS59LEsiYpYCbsPu4SEwATUFYDQTRRhNBIgmqqosYDUTUATCBMFZFgEtBISBISIIhiKKKCgAXUEgUDBIVwEHBMEGAVwTkqNSWVLEpiWJbKbtTiXYGN0f3q7K4fXVsZdhdHCzdmewNc5JsRnuUD5uOAm6mCOoYjuLuW7jmYdBGBr0PJ7PQ0ZJgmLDeTcqOn1/n2rN8o2amz18pN9mVtTgijP4vCNUzmpGNd6lhpTuOEnITgJnT2PpxJc5+6br3nU9TO9iBjgg2xuDlbiTwNSfrYcXCaMTnNArwFXeRA7QwSZUn07RSbYqP7fOEiq/8EiT+UhP7ENdbUVkoiLERUElZm7tPLT1k97ORCqA4+g9b40vOdfD9h8Obuft+/v77fLVK/P+BEDDEeCmoE8KI3/oWba/LdwvppD4vv07VxVQ36FBak8b0g90GMNivWmLx9QeJEdtcdLee/dVmqbeVciTxK6muzu37zJeiMHxT9M+rPjn15+meQfLPzT3R8U/HPEPzj8Q9A9kfOMf0z7g8M/iHSPYHtDwj6Q9qf2TmLzV2q/KXzV+Wvdrzl5C/LX9JfLXxF+MXgL74vzC+6L+AeKvLX2i8hetXfLv17te1Xlr168BeCv+tPLp8Kns1eVJ8onoiejJ2ZO5J3RO0J2ZO3JzvPdgEs9JNu0n9XpfSWdnFcrrr9bYLCsnZxOme8fYyew73qJOziKSQ5RJQByEiTlElij5DtXSJElkUivSZrsex2u108OICmoPx/NB6UHfB/GH9dwdBNwcl1LtfZEsLGetpg7hJJNFQDBQSNkMMANhhQ1JIhEwkHU1igjCFcpD2ASUIVQwtCsiPdXqQpR5BEYTCwqipUqKlTSJWVq1RUqVFSp6bGmtpk/LvoVIenEaxJV/jTLkharqUiParWIWCzwh5osAsgSfiba9KSSkRQJYSWFsqJUSolIlImLqGmTyHF2dsT++TvLWzr8F/d7vcqk/+/+0wrtzUwm7bLBbttAUVhOuGcEqshIpKRF1du2Xbq2Wy2opbl1cuXBUgFh7i4FbRiYkNoObJ2At7ynQk3Dhe/J5VHe/BB0x4Or5qvm04/Pp7pKJW+C/INI0SyzSKyuVzGWb3KjpC3OUHcB1gc8anCMN9DflpaWlpaWRB7OP2+8C6e20kijshWqDKRJDMFlHrwmWBpg7habjSsmcWHt058orkLtOmwyeKnfyzKyujnQORmZY5xMLBxkpyJOi8OtUpfpSi6uDFVNBim/m+xzHdOAUmmIsq/RuNp06WnRp8drcG4Nsn3NTzEyETatxz1bLVcm/LWp5G7Q131pMaTKkrdImzTaxDabjYpd2/2NlSijmW5ktJZwuilbUUJKPlVScjHU8NhfuK0rSihR/LOzR46iXbSn8FniLS43XHW4W66LM5bWmgnLH+EaBuhmj7M4uGlKspu3/EWDkHzqXVHWpb6jB/UqrWoYsrEqrKIZVcKfCrK65XrD+JRt2w6zq+nfWc7pp1vPqZBtWJw70XErTn46unK6Ffup1XKWqGsnu7Nl87OVp42FNBM1XQo3DktRqumHBk0KSKv6++5bYfYHJK1HSUHQUVrSoXpLVqinJpHqOJxMIuHPnSnMdjx+acFwBsOeUURfavO3FfVUrdKqsOPJ3nMANQbA/zAKhm9AA2gGGIHEiBaiBciBW9LvKv4FEtc3v046U4vGTgcylVSa7nOvTnedTWTL0E5NE2RRLVcVJJpCWppVq1aVVWVSqV2amTY1gG57bb2wFL4C+A+hlRAyogbaIGSIFiXG1zCdvP1IerzcYDEAxAMQDFEDFEDFEDFEDz5l7dcJ0kKJW1y3rOgdynRnw/d4WaA02cAzgGWAzogZ0QLkQMuIL+VovaT4V7nyQfiVMNvdVh6KfDvL+xB+DUw+B8mFJt9MBpgNMBpgNOIGnEDTiBpxA3t4vALwC8AvAL0QL0QL0QL0QMXCvxI9FMoBgwAMADAAwRAwRAwRAwRAviDe4Z4Amt/jw5YDLAZYDLAZcQMuIGXEDLiB1c6qUpRR7Hg+95o9VSaBx+ezbCZ85uQUoSVE8mvr7JFGWjv8xq07/oavIVp9QeCD6c8iMilbPIwvAOKdkeSfYntztT6w1zePCPXHbH2x8E+1PenrjlHpT4R8M+9PXnpzmHdngnpTrDsTyDknNo7L53subqJe/6FPl92fHOMYjI+Yfzz5Ubx7FZZZZe2XkrLLLLLLoui6LosxmNeOOdj6E3CrseBy5SZqj4f/DKONw6c/FUc1Ltc8aupTf3sfKO5lJyUvOS0Sk2j2StrZ3H3lSt6o+PfkWEsJblU26rFPU1ePUfr1eJUbcbaWOz8/YF9sjqei8gDCTIJMQVBPQDEE5kfCEmjh6bbVONXpb+35Hx0DdYgxE8F6IegEmz4/t/cMDqNsXVedP7eG1tU2nkToA9D2HOPKqefVV7+9t+eyiW+iwaWfxZL4H7370s17L0lP0HguOOCKBKBK4iuIyyb8DeAYl7KeDJ+Y+NNaF4erB/aZtbkHquJ8az1aKY+tBpekB77vtPjM3M9Jv+Ej4Q6/ske55B2auED2aEhIemMFpWZF5p3R/iNVLmYirl6+9imaLTKvu5kOPhLx8ULfpxprTamiaJrz4k02KZU74A+IPk+oAOv5/MzFwww6lf719Au+cQGhSgQoBaBoFfmkU1XBwPPgPH75z2sIn45KAFVIgUO5aMlhO9S+sJSmerxvkmztanOxqRs3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", 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", 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", 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+ "comp_options": " -DCK_PARAM_PROBLEM_N=32 -DCK_PARAM_PROBLEM_K=128 -DCK_PARAM_PROBLEM_C=128 -DCK_PARAM_PROBLEM_HI=28 -DCK_PARAM_PROBLEM_WI=28 -DCK_PARAM_PROBLEM_HO=28 -DCK_PARAM_PROBLEM_WO=28 -DCK_PARAM_PROBLEM_Y=3 -DCK_PARAM_PROBLEM_X=3 -DCK_PARAM_PROBLEM_CONV_STRIDE_H=1 -DCK_PARAM_PROBLEM_CONV_STRIDE_W=1 -DCK_PARAM_PROBLEM_CONV_DILATION_H=1 -DCK_PARAM_PROBLEM_CONV_DILATION_W=1 -DCK_PARAM_PROBLEM_IN_LEFT_PAD_H=1 -DCK_PARAM_PROBLEM_IN_LEFT_PAD_W=1 -DCK_PARAM_PROBLEM_IN_RIGHT_PAD_H=1 -DCK_PARAM_PROBLEM_IN_RIGHT_PAD_W=1 -DCK_PARAM_PROBLEM_CONV_DIRECTION_FORWARD=1 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_DATA=0 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_WEIGHT=0 -DCK_PARAM_TUNABLE_BLOCK_SIZE=256 -DCK_PARAM_TUNABLE_GEMM_M_PER_BLOCK=128 -DCK_PARAM_TUNABLE_GEMM_N_PER_BLOCK=128 -DCK_PARAM_TUNABLE_GEMM_K_PER_BLOCK=16 -DCK_PARAM_TUNABLE_GEMM_M_PER_THREAD=4 -DCK_PARAM_TUNABLE_GEMM_N_PER_THREAD=4 -DCK_PARAM_TUNABLE_GEMM_M_LEVEL0_CLUSTER=4 -DCK_PARAM_TUNABLE_GEMM_N_LEVEL0_CLUSTER=4 -DCK_PARAM_TUNABLE_GEMM_M_LEVEL1_CLUSTER=4 -DCK_PARAM_TUNABLE_GEMM_N_LEVEL1_CLUSTER=4 -DCK_PARAM_TUNABLE_GEMM_A_BLOCK_COPY_CLUSTER_LENGTHS_GEMM_K=4 -DCK_PARAM_TUNABLE_GEMM_A_BLOCK_COPY_CLUSTER_LENGTHS_GEMM_M=64 -DCK_PARAM_TUNABLE_GEMM_A_BLOCK_COPY_SRC_DATA_PER_READ_GEMM_K=4 -DCK_PARAM_TUNABLE_GEMM_A_BLOCK_COPY_DST_DATA_PER_WRITE_GEMM_M=2 -DCK_PARAM_TUNABLE_GEMM_B_BLOCK_COPY_CLUSTER_LENGTHS_GEMM_K=2 -DCK_PARAM_TUNABLE_GEMM_B_BLOCK_COPY_CLUSTER_LENGTHS_GEMM_N=128 -DCK_PARAM_TUNABLE_GEMM_B_BLOCK_COPY_SRC_DATA_PER_READ_GEMM_N=1 -DCK_PARAM_TUNABLE_GEMM_B_BLOCK_COPY_DST_DATA_PER_WRITE_GEMM_N=1 -DCK_PARAM_TUNABLE_GEMM_C_THREAD_COPY_DST_DATA_PER_WRITE_GEMM_N1=4 -DCK_PARAM_DEPENDENT_GRID_SIZE=196 -DCK_THREADWISE_GEMM_USE_AMD_INLINE_ASM=1 -DCK_USE_AMD_INLINE_ASM=1 --std=c++14 -DCK_USE_AMD_BUFFER_ATOMIC_FADD=0 -DCK_BLOCK_SYNC_LDS_WITHOUT_SYNC_VMEM=1 -DCK_WORKAROUND_SWDEV_229564=1 -DCK_WORKAROUND_SWDEV_231101=1 -DCK_USE_AMD_BUFFER_ADDRESSING=1 -DCK_USE_AMD_V_FMAC_F32=0 -DMIOPEN_USE_FP16=0 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", 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", + "comp_options": " -Wa,-defsym,ROCM_METADATA_VERSION=5", + "kernel_file": "naive_conv_gcn.s", + "md5_sum": "1aa674543ec83d8948e9344d4ea55ec0", + "uncompressed_size": 101544 + } + ], + "solver_id": "ConvDirectNaiveConvFwd", + "workspace": 0 + }, + { + "algorithm": "miopenConvolutionFwdAlgoImplicitGEMM", + "find_compiled": true, + "kernel_objects": [ + { + "blob": 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+ "comp_options": " -DCK_PARAM_PROBLEM_N=32 -DCK_PARAM_PROBLEM_K=128 -DCK_PARAM_PROBLEM_C=128 -DCK_PARAM_PROBLEM_HI=28 -DCK_PARAM_PROBLEM_WI=28 -DCK_PARAM_PROBLEM_HO=28 -DCK_PARAM_PROBLEM_WO=28 -DCK_PARAM_PROBLEM_Y=3 -DCK_PARAM_PROBLEM_X=3 -DCK_PARAM_PROBLEM_CONV_STRIDE_H=1 -DCK_PARAM_PROBLEM_CONV_STRIDE_W=1 -DCK_PARAM_PROBLEM_CONV_DILATION_H=1 -DCK_PARAM_PROBLEM_CONV_DILATION_W=1 -DCK_PARAM_PROBLEM_LEFT_PAD_H=1 -DCK_PARAM_PROBLEM_LEFT_PAD_W=1 -DCK_PARAM_PROBLEM_RIGHT_PAD_H=1 -DCK_PARAM_PROBLEM_RIGHT_PAD_W=1 -DCK_PARAM_PROBLEM_CONV_GROUP_COUNTS=1 -DCK_PARAM_PROBLEM_CONV_DIRECTION_FORWARD=1 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_DATA=0 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_WEIGHT=0 -DCK_PARAM_TUNABLE_BLOCK_SIZE=256 -DCK_PARAM_TUNABLE_B_PER_BLOCK=16 -DCK_PARAM_TUNABLE_K_PER_BLOCK=128 -DCK_PARAM_TUNABLE_E_PER_BLOCK=8 -DCK_PARAM_DEPENDENT_GRID_SIZE=196 -DCK_PARAM_GEMM_N_REPEAT=2 -DCK_PARAM_GEMM_M_PER_THREAD_SUB_C=4 -DCK_PARAM_GEMM_N_PER_THREAD_SUB_C=4 -DCK_PARAM_GEMM_M_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_M_LEVEL1_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL1_CLUSTER=4 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_E=8 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N1=2 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_B=16 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N2=1 -DCK_PARAM_IN_BLOCK_COPY_SRC_DATA_PER_READ_B=1 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_E=2 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_K=128 -DCK_PARAM_WEI_BLOCK_COPY_SRC_DATA_PER_READ_E=4 -DCK_PARAM_EPACK_LENGTH=1 -DCK_THREADWISE_GEMM_USE_AMD_INLINE_ASM=1 -DCK_USE_AMD_INLINE_ASM=1 --std=c++14 -DCK_USE_AMD_BUFFER_ATOMIC_FADD=0 -DCK_BLOCK_SYNC_LDS_WITHOUT_SYNC_VMEM=1 -DCK_WORKAROUND_SWDEV_229564=1 -DCK_WORKAROUND_SWDEV_231101=1 -DCK_USE_AMD_BUFFER_ADDRESSING=1 -DCK_USE_AMD_V_FMAC_F32=0 -DMIOPEN_USE_FP16=0 -DMIOPEN_USE_FP32=1 -DMIOPEN_USE_INT8=0 -DMIOPEN_USE_INT8x4=0 -DMIOPEN_USE_BFP16=0 -DMIOPEN_USE_INT32=0 -DMIOPEN_USE_RNE_BFLOAT16=1 -DCK_PARAM_IN_BLOCK_COPY_DST_DATA_PER_WRITE_N2=4 -DCK_PARAM_WEI_BLOCK_COPY_DST_DATA_PER_WRITE_K=1", + "kernel_file": "gridwise_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw_lds_double_buffer.cpp", + "md5_sum": "712359db350d91dd3339320e2993b8d7", + "uncompressed_size": 24181 + } + ], + "solver_id": "ConvHipImplicitGemmV4R1Fwd", + "workspace": 0 + }, + { + "algorithm": "miopenConvolutionFwdAlgoWinograd", + "find_compiled": true, + "kernel_objects": [ + { + "blob": 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", 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", 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", 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", 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", 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", 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-DCK_PARAM_GEMM_M_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_M_LEVEL1_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL1_CLUSTER=4 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_E=16 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N1=1 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_B=16 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N2=1 -DCK_PARAM_IN_BLOCK_COPY_SRC_DATA_PER_READ_B=1 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_E=4 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_K=64 -DCK_PARAM_WEI_BLOCK_COPY_SRC_DATA_PER_READ_E=4 -DCK_PARAM_EPACK_LENGTH=2 -DCK_THREADWISE_GEMM_USE_AMD_INLINE_ASM=1 -DCK_USE_AMD_INLINE_ASM=1 --std=c++14 -DCK_USE_AMD_BUFFER_ATOMIC_FADD=0 -DCK_BLOCK_SYNC_LDS_WITHOUT_SYNC_VMEM=1 -DCK_WORKAROUND_SWDEV_229564=1 -DCK_WORKAROUND_SWDEV_231101=1 -DCK_USE_AMD_BUFFER_ADDRESSING=1 -DCK_USE_AMD_V_FMAC_F32=0 -DMIOPEN_USE_FP16=1 -DMIOPEN_USE_FP32=0 -DMIOPEN_USE_INT8=0 -DMIOPEN_USE_INT8x4=0 -DMIOPEN_USE_BFP16=0 -DMIOPEN_USE_INT32=0 -DMIOPEN_USE_RNE_BFLOAT16=1 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", 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", 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", 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", 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", 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-DCK_PARAM_GEMM_M_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL0_CLUSTER=4 -DCK_PARAM_GEMM_M_LEVEL1_CLUSTER=4 -DCK_PARAM_GEMM_N_LEVEL1_CLUSTER=4 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_E=16 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N1=1 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_B=16 -DCK_PARAM_IN_BLOCK_COPY_CLUSTER_LENGTHS_N2=1 -DCK_PARAM_IN_BLOCK_COPY_SRC_DATA_PER_READ_B=1 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_E=4 -DCK_PARAM_WEI_BLOCK_COPY_CLUSTER_LENGTHS_K=64 -DCK_PARAM_WEI_BLOCK_COPY_SRC_DATA_PER_READ_E=4 -DCK_PARAM_EPACK_LENGTH=2 -DCK_THREADWISE_GEMM_USE_AMD_INLINE_ASM=1 -DCK_USE_AMD_INLINE_ASM=1 --std=c++14 -DCK_USE_AMD_BUFFER_ATOMIC_FADD=0 -DCK_BLOCK_SYNC_LDS_WITHOUT_SYNC_VMEM=1 -DCK_WORKAROUND_SWDEV_229564=1 -DCK_WORKAROUND_SWDEV_231101=1 -DCK_USE_AMD_BUFFER_ADDRESSING=1 -DCK_USE_AMD_V_FMAC_F32=0 -DMIOPEN_USE_FP16=1 -DMIOPEN_USE_FP32=0 -DMIOPEN_USE_INT8=0 -DMIOPEN_USE_INT8x4=0 -DMIOPEN_USE_BFP16=0 -DMIOPEN_USE_INT32=0 -DMIOPEN_USE_RNE_BFLOAT16=1 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", + "comp_options": " -Wa,-defsym,ROCM_METADATA_VERSION=5", + "kernel_file": "naive_conv_gcn.s", + "md5_sum": "1aa674543ec83d8948e9344d4ea55ec0", + "uncompressed_size": 101544 + } + ], + "solver_id": "ConvDirectNaiveConvWrw", + "workspace": 0 + }, + { + "algorithm": "miopenConvolutionBwdWeightsAlgoWinograd", + "find_compiled": true, + "kernel_objects": [ + { + "blob": 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", 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+ "comp_options": " -DMLO_DIR_FORWARD=0 -DMLO_GRP_SZ=256 -DMLO_GRP_SZ0=256 -DMLO_GRP_SZ1=1 -DMLO_GRP_SZ2=1 -DMLO_FILTER_SIZE0=3 -DMLO_FILTER_SIZE1=3 -DMLO_FILTER_PAD0=1 -DMLO_FILTER_PAD1=1 -DMLO_FILTER_STRIDE0=1 -DMLO_FILTER_STRIDE1=1 -DSTRIDE_W=1 -DSTRIDE_H=1 -DMLO_N_OUTPUTS=128 -DMLO_N_INPUTS=128 -DMLO_GROUP_COUNTS=1 -DMLO_N_INPUTS_PER_GROUP=128 -DMLO_N_OUTPUTS_PER_GROUP=128 -DMLO_BATCH_SZ=32 -DMLO_N_BATCH_LOOPS=32 -DMLO_OUT_BATCH_STRIDE=100352 -DMLO_OUT_CHANNEL_STRIDE=784 -DMLO_OUT_STRIDE=28 -DMLO_IN_BATCH_STRIDE=100352 -DMLO_IN_CHANNEL_STRIDE=784 -DMLO_IN_STRIDE=28 -DMLO_WEI_BATCH_STRIDE=1152 -DMLO_WEI_CHANNEL_STRIDE=9 -DMLO_IN_WIDTH=28 -DMLO_IN_HEIGHT=28 -DMLO_OUT_WIDTH=28 -DMLO_OUT_HEIGHT=28 -DMLO_IN_TILE1=1 -DMLO_IN_TILE0=4 -DMLO_N_LCL_BATCHS=1 -DMLO_N_LCL_OUT_MAPS=1 -DMLO_N_LCL_IN_MAPS=4 -DMLO_OUT_TILE0=3 -DMLO_OUT_TILE1=3 -DMLO_OUT_STACKS=36 -DMLO_N_WAVES=4 -DMLO_READ_TYPE=_FLOAT4 -DMLO_READ_UNIT=4 -DMLO_HW_WAVE_SZ=64 -DMLO_LG2_PHYS_WAVE_SZ=6 -DMLO_IN_EXTENT1=28 -DMLO_IN_N_VERT_LOOPS=1 -DMLO_IN_WIDTH_CHUNK=28 -DMLO_IN_WIDTH_N_LOOPS=1 -DMLO_IN_WIDTH_LAST_CHUNK_VALID_READ_UNITS=0 -DMLO_IN_WIDTH_LAST_CHUNK_VALID_PIXELS_IN_LAST_READ_UNIT=4 -DMLO_OUT_WIDTH_CHUNK=28 -DMLO_OUT_WIDTH_N_LOOPS=1 -DMLO_OUT_WIDTH_LAST_CHUNK_VALID_SPANS=0 -DMLO_OUT_WIDTH_LAST_CHUNK_VALID_PIXELS_IN_LAST_SPAN=4 -DMLO_CONV_BIAS=0 -DMLO_UT_READ_TYPE=_FLOAT -DMLO_UT_READ_UNIT=1 -DMLO_UT_GRP_SZ0=256 -DMIOPEN_USE_FP16=0 -DMIOPEN_USE_FP32=0 -DMIOPEN_USE_INT8=0 -DMIOPEN_USE_INT8x4=0 -DMIOPEN_USE_BFP16=1 -DMIOPEN_USE_INT32=0 -DMIOPEN_USE_RNE_BFLOAT16=1", + "kernel_file": "MIOpenConvBwdWrW_LxG_P53.cl", + "md5_sum": "6a393ee4663576b37b85985576d42f16", + "uncompressed_size": 26664 + } + ], + "solver_id": "ConvOclBwdWrW53", + "workspace": 0 + }, + { + "algorithm": "miopenConvolutionBwdWeightsAlgoImplicitGEMM", + "find_compiled": true, + "kernel_objects": [ + { + "blob": 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wCGk389lsPmX56NB33Agj2GoE2RFJcuSeVevureE2XqPyf1QTQAvZCSQEu5PSkEnEogYiXsV6AZERkyMuppH2eTAtlDaJZu2CKDFCVxp2hSJo8oKIvNOXW0PldqvRXL6AU8hoWcW65GRspxHsEEO1OoN53EBeiQWBEmQAxQWGWK0GJ28CNwkkIQQQZwG1T7SVBDxI8WMihgsIM8QBN4mJH66xG4YmTd3KMYlj5OJMZUqn68i5di/MRKA11auQI6jmWaDsrmXTtowP1vYXIUk3DQy5/tyO3FIiIgKMcS4F7MNk+Hbt7rOmxXSu2fsOwpJi6WVgIW/Ur1bsJQPfx2oBs5w5+OM+KjDC0/Pff+VDL95VyclU8C4h0Nuxi63iXVRtNm95veNdUpnF4XYu0y/cOL0sTV9FwhG/yFUxb99ozrTDNgjGhjTi12o8s0VZauNlupCKVjvXKW+B9Dv4YH25E0FiSreq0XkKjJ+endjl8uBnKLXXdLOoWT5/NjO7hFIWO/wWcv2KcGN5syMy7kQw7eBRo9U7GhPl392x3oGUKjuYt6fEZ2zumvpdkpoU09e7nqU0U/gJNqTZBvazj9c5MVqT0+x3J61KpUWYEGc/BVpn7ug5PcbPXPPTXBmnky8wqOMpMcpXVL496ruHS9PTC94noI8TobuBGMoqtWfpcM/DPIPUk2rN4xS1EssuNUFoF19iU0qGlDPTC2AMiVr9LFZyssGwCAjaQ4OgRArCNF5e3s32V03nzXVlYEZhb1R0CMwrELwI2REhM2aKJCZLKYaZI6I7wbFjONtiLw/K5cRD2uU8jYYmNuycM5FRibuLjyznPbr/4d9emSlq7GtuaLdcxm4gQWPFOLRWgyN0hUtKCc6dgNHtKmpkbecFCl6iViZ0Yuur036qAJmZv41WlVfmIsqTgitBVg5p2nUREQlxRF1EDlqoErMKRnRcl1/P0QM8hZz2ujALpWveLx8twUa67EFWuGXEZNRqkuyIJaThNNBkuJRf6StXo9PdDxsQhh+kgfHHAgEicK4ZiSuC4OPSXfELVca0wIkL4wMUd++pAlCJDxICiyNrSSkiIPkRwdRwLYscrqcCWiNcWBmdVRtRRlZ0XxPj1r/7NukayicSCYhHC5FwkrKXG7Xxe38TleD4exwN58R+uKtY9C2fDfwsRUaB2pWtzLH2G+lbpLRjtRBbLu77eyqgq7Xrni4U3FA6Mky4ruxIZFBMmG/jiylv3mCOL388CcqTVdYlOAMK1+Mth4I4hjIiGjbdJGVtBdKYrQqoHchBkyoXHbPhay0GmsgbZYxJAGv5IppJJZQVOGwWfk60eZp6rabXUHjhDL3hDUcRBNlu4jSJjXebu7vVLsypmkyRdgUecRFjlyammsuYXsdNYEolWM40cJmNVeYKhpyYW6QcgQ25HISlutF556g8NXgy9RVpNBB96oka448u0xJDim4tIWuUnTgYVVSUQgkl0hA6DTpQ11Nig70ir4Jl/YAqtSzfj321/RSnUnevXpYvz70ARHnmoIQD6CSLRJhEqSRWUCKQCFjXVEBOaw+eJfETb2nJFKwxAjOadkaPPzuTkeA3HSesp9EIIIuii9hyJ6MtBSLtE5aybJlBs4OZcycQbTxN/+GskucB0wiRamGduSD1RSCxoCawOh4imFkAREE7K/zaxjwnfiY80PA5Wmyy5TPKu38OdiKVIQmX1t72scndrNV1hEIyakbeTTt2l/0q1nMjOQeqeCI8JEcUIdHZKwAYh2i8YmlVePTF9ihgIgM7oF6/zT141bh9ooK4MnquKqlDJVFxaEQQoFDIOq4dpBAIJBBa3r1HHnOZidLhZMJoshwdbz3vJTSkF9U5R0MDdTIzqi6FaqlutxKZMtive+wIbw1cwbgAOR1m1a8g8bzsR8MwQDabNDxy7wLaxGMWEWLGp1bGQXSpvAb7i0eGSw6bY1hnnOjElguw4bqXtLCqKSTxCYRG1gSLAIGhIxkzhrK71R2mw4GDrd/E6+K4O0E6pbkJ7uygUShCORGgLA5v5XbCYuXXsIqHBEV8hBghaEBBFsOFKG8oFdjY0Hwa1stCZ22BWJTHg+/cVVQmHoIoOIxkYJHNPctgAhrc3koU2YRkzc62hN3Jb0sCdISOiRpFTIn44RkhyzA3SMcAWU1CoNiYlOivSH0UV4AC5W02EbpT1V8osooyDOTZDeW6OalzxaAlOlssjmdP8PHig8eTnAQamitFlZ/PFY0a+SoIMrQyrxpO5uLpPzOOpl2q6CKTf9L1VWIoDhPgvT9ItrxV0LG22nx8HHwYOrYvhNycIGAz2WjaNE5GFtDTfOs6pNw8fNK1yahERRWjaat9RVdTVuAJ4GJCE3mdvKebqZkOTUz+r37I44ykQJxt6DaAYtAjLwjkh8NZxBdfdODOFnACEwAgZua7AXL59PjmM73RQyYj9iEWeSs8mnUdoDXkq1NYfQlMIaFiUxpqHQM3r8DBeBE3Bs6561BfjIqxsCXgW0p1ZhYWNnXgYC/yDGdOTU5LutiuXjiCTYtFQJBreJ4ZULj3pSo63UTWr1fMm5dpJuFXmbjeQwlcxaa9lMk6b3I71TuCSy8nv54P6DwYfd/1lDGhRZl5/gP3tLM06O+qb6331WnJZ1KZKZ0et8FOl4EHB7c8SItEYysF1X60WFLwqwz36iWJK8AR29KzXbPpF0GJ7+Hm65W+K2gOF2O85N+sMqTi0LTj1DD6oDUmZmH1mNhqtdX7vVnxSpqoET+ItuzbghJ3ETYZBTNHCTT37ZkieGPmOMkulnQ5grRsfNvCRtUgzC6gd/2Rh3UqILFTMEcbZnGcu+btJ9MFVMl2aOsrNen4p6oKLNsNQY3E6oAKv9Bs1RzXW1E5fPynM10jWHZtgWHWhGgWIJadnnJAAkcssHAFDYkYPgYM2RNFB/ZxKwtFYnpqoShYcQoAZHXpfO5lePneF5NgPu23MbkT7PKsAAloZqZL5Xt2thaRjQaEnWdkl9uljZbnQwBQeZpdPqcC8AFKfPn3+i4kgO2sh3BYyryaIUsuoDnLNEQxWCoq0uPTwVJsUTT5uaEL1EUksWpZWYviUcxx04HfFtUWwlKj6+1nT7aeguHL2tORA0CE066OdOk5kss/RlnAlDB4yOGLeVUNRa+13CHPDG/mVHGHE4cGz2SS81ZySXzWXrq6ZoxDsQqyLvmN3Jww6xcbZxDf67EjQ/D/Zg964MPiZdBQ6YMCSITujp2cIkQsDCAS93x8M1ASQGhC4SJrl1qdKurVjFPY1K93JgYnaBB3aNohWmxNm/XPNye4p0l/VY/l4OqaUDndm3Bp044yCaHTKJcCB1MPgAHRC53RBGZub1MmzuExOPAuOLrLmUuNHkevz+zueg/qx8zn+PuFnI6VW39PhgfZ0RwJx4Q3Xvg4HkAHLAxzzg92EAIRUw/IDiJFSCIG02WDzaFC7K3sPkbHXN/ybspU58vYhLDUda11+lmZMGtXJ1cRbDSHfDGHhCDAMAwI34FcHBcBgAlaoNdBLgFw8gINXizMsIGtXNmusHv0dowKuo9SaOpiFTn31HQXZoyaWjvLgXgYN4wIuhgYHDslFxHaD7uBVoYq+T5lwngbYPBwAwMCfPOqd54aRBW8TrWF+dQuU3LgTsyx5deIW1XwrcG8NPgXpalqcx4rFLk2N+yPFtbrTCQPoZLeThWRXiMUi30Fup9/+Nng0cBVdhR44Espg+ALYFeygAN4ITmS5sVk1/oDrzLoiOhZ32z6LZ7SEMooidlCqGHd4NoIYgsjDijN4VGpqVYjWHYdjmTBJRsDMkjiHrWcrXzIbZDTnO2aJU9WL4YZQfi1gFihe4od9xjLNoul0n5hja28ZEfK1ns2RK5N6UuS6jwyMwgaFPSUlOiYcLjIsgZwp9CXJ7Q8IzOrpce3DfLSjuiO4bIEvIl5MLFKZcuHliNtDy1R3fcws8zIWZyTx78YdM3BFTnZO3yUYBGEppR4Zm+x0oIl73bHZUxZzEJbDj059LGfi5aOtThCVq7QbsgoxIfMTgPMQDAePVFk+piaoKFSKBhKRYkFmC21D3L+qvf4EVnVe1qUuMZQw65vGSF1SkpK9knJ53sD8oAOOW4Ru8uTcSsr0YMAwDAZ5n9sN7Zj9j2fdcNliAVa449RoyDvp1PTRJRksOk3F6uTwQMADghwKkx/5M3gZ35sSyP0ex3sqbHlz9XvgpBUDPuejrgg5ITsmjpYNu/i4kp/UpzQLMxiYSbwJ4UwjDfXXAkdAGBIYbUPDAQAwgICAOWDfBIJhuAgKQFvrASCkGCpCQUhMICQMDSBgMBh4cJhABIJhMGFIEwpCAgIBhAQDA8AYGCAIgJQCiCEJoUsfGlBxn7PexFy5r7XodQANG9itQw8W86Hh3/X6kHEpnc4e10Xe1YphpMBlhdxwZ6TcakCHNON26rdAEg/2rh5jbJjdYRvokAkFYMmjO4tpyeJufE0aSxKBKnu/DDf2ADYBgRvwYNAGAHAwHKA7Z45CHZ53xZ5SOQCRYxGaliVMKy3Ih2dG4cafLdr7oLlSwHdCbnhl773Aa+xmEePoenUgstD2rw2zrbVvADYn/aAoQWMCYEoBMEwYWgYAwYBIBgJMBgwYMGASBgDBgHJZhdutX4v35UTuRf5TGIp9jD74pwUIx3AsfxB+F7uW8OkFYK4MCLIEgDgGAeFsIQrB3Q9cFd9o7jO69fnWtTt259PLCT42jOD2Gw5Vgu8X6jm4kxRjR/pc3CDp5gFMOtKlm3IkgrMhmEzMhmYYBmZMwkfOMS9jYITL7fbk1ah9Zh+EGRTpyg811Ixr9PHyKtAi2gAlgwAWAJAXKB4BkBzwo6t8eBQsrgPDpoJTaNqiyhNABfGgbl3E8VHy5VgL65kZumUbK6PhW7Hc4kaf7KZMXFdCqhr8O/kxRK6GwDBMgmBfiDXyvHyCAJXN9SSQIQ5uB19SAPGjjCTSpRQsuZrBoAwwDActnAysbolMGO4DkABdC+CVoNMPEC8DpoMBIbcxLHv9A6IcUyPY1Q8I9ga4j2iYBumzdMOokSy/YByVYjkj4iRZENIlQK2DsJElaXV2KorI5ctJYBHrzGCiQTAtPUq5Db/vwNeIrb6Ld7GxbwwCbgHIZWU6aGPSCkI4WVgwUnnkpe3L909QWlhCHJba9AhMYPuQHEkrbIZ8kQcoDKx8BWF75C1SaFRJMETCVu4G+zpa0uTmk4plK7dIDx5QlCRZSJhQLgWeKvYSRfDMFsEjbvXN40xYCxitBXa5BYxzclckK3YK2oPShStJSwthVST0pyREkdAK6ohSq2xFSUFWFukI7vY4JmFghuBkBAD3BIkQJXxE27GVj3QwYmlQ6uju9coTwzCvwAoJaWGlUC8HnAyPXBnCw2DBHKeng8OIFdKihPziirKVG2p11RWsIlhqE8SqCWUhRbhKEMyJCnY6zZylbNM16pazZ6Tav9Cev2kqIbrOt4TM+gjic6K9QpDRcTB76abzO3Pi452hhvTsENC+jzLWNFWHQCtNtKTAw1k3Q4RvL+yaZfktQh6aOnzGEmZESp4FGl2JlKCxVi8/AwpIbqA4f0FwndEBIDLO84SRk9+kyQ7vOCLaNkNJBhhcETZWHLAYGSGJkwJYbaRmpEqQOKLCS4jQxMUz83MpMZ6foVDSHzdQvIWtqd86Dh8P0dfp5ynFScOLAi8kZa12VtyQ8Q1KPalY+syMHeRQ4saMYZTyeXoJ6RwklkpEfA1zirhoWd4xKDdcWWIxUlOLZYgSg/Vr8HBjwR5ZSK8ctFQIKYPNQVFIncoI0qr3rLvgbV2vx2JvdZ3a7SBeBgXSShJhoGNhQUBEwwkiQidKxQlNIqaq2XQ1gWR0pqtxhVzSWqTOb2H08Pse/ZP2ZSlSkp0nJROk6Uo8TnSglOcSpSlKUpSdJ0nScccccccccUce6LN64a2KCLGCIsJxipLGuVgFuVD7ICBKAcGuG9CwF7Ol79JSwkH07jJtowKsDns8foOfhQ9qF2s6OKzPiJarQsz2abV0gO10zHOcWEtZjRSMkLuoWgvGLhgK802ITG222NsG0mIx8QjEKPS4o6jmhr4jimt2ymE3gTXs+S1u5YclIbHAYN6EweF0rBjpZoWtoGS3AS5UiLjzFiIFWLgODq4deqzNXK1eMKaRVSqp4VUjNCihUysNlZAMOEQoeDINfveZd4/F4BPSuSTKLnE3SudKGvZkfZTnjA+vdHruBYB3CCIHpMWIE1jNb4xkVYaIwYG7DAzwogyRCBkBTWOqOhlVyuzQWCikpwj4gaolW94GVEKJJSsWTRBHDcAZaNeBzkPaxlUnh99y+dFBl/g+X4j09jdZ3vX61REI2fJQYhrABwIkiRojjgD2+A58eDE8tyPr9KW/vRpZR03f48EAcvZqO8Hp4VlwUsT2+o5EE+YzTH4xQWLXgxrLDoOvDeXUPMf2bHtg6x5W3b0DsO4SR3RZvxc/CY9/udCs6DRvCOGg2Z757GXqGoklhXrS7Y2JVAVvKnc1u0nOkiVloJ+lz9s9zuIZhh4o5pmG5WnxmatrVaG6hAeAnq+JMYVxuTJEW2hx444tqaAiGoYwY4pxYfZmtTyqNOg8lzgaMcysNfKe9b4m8CoC3eIYU9NBdFgN5QGMgkDJHImA9Kz76Zt2vTzFRupgVrZQAC5XcVt2mXRZD3fBT/GzWyFTMSE2RjBoYAe/80pFfLWWv6fr/7s5FWi0cr7H2vOh+v7j29zlzdMvWqfBfaTOS3dm4frPGbTg9Pu9mdSmpvS3XxNMJPTaqf5HdSD/TwJ7MO9PAdzmZYDT+CR1FLZ8eZ7PA/RNUU173m4egpeNrnrzLiTEeHIWKMM3M2M2DJ+duZqMEmwqibijK6xiiDUbAs7sMKz19nr9BUVL971tg58Oidfxu8s12ewjrqdd1kjYSM7IsNpIyFnDkZeqvUJfw8WFajlD9gS+WjOfjAisCL/JFqyK/ZnPgMznf7s56H5yz2m5Z6uJo7uJZ393bsNNar76Wwba60Nz87+/LQ35PhSikpcIiIjq0Hh1vc2GX0WR0KqAwOlC+iF3c0n9Odb7HvQt9TwqaDGQ7rx9ktbz15T6qo8Q2tmG+lttKzSjH1qKN56lkHEDhdFRG6jHzOar34loly4+Bh1aUu1bg1VVBJpv8/TJ3DJeTv/OnHDjcPtvhHzOzx/d23Zq6KMtnDAHyaYmDBthrGthixToU+X2LybCxpg6lQnJJiTMtrnlXYPIQMSjx6cMMs1Wq3DcFl4WG5DdE3JPCYUNLtaiS0Y+RV1nZ38jLv63Q0Ndo6OVd0WYLFgtGraRDe087JQxNiUjr4QapgEhJpLRM+3OUpPe973ve+BJGynADkenMp37F8iSjAGQG2yHAGkNNAQhFtrxWnLA2/c6EWHfYcHiJyRhAW7jKo+Ae8puRLyshjTWHbGwmzFOdrOZaBR7gwA+tbSb2GXyui9Ni0hZzmIqwut0lp+fNPG9yp8VLYmzgDuTa/a8uGWEdv5pTYQoUxU3D1JQKhrPaU55sFlUpLKCSvMUrvV+pmpdP21amGNxOxulVJqAWDdkJDaQ2m0hsW/gIZ+P7xKJxA+vhwkU0gXdwYEJBn2vlKxf1nYjV28j9KAA5jBvqtwHFQFhQJLZhcigIBiHFRlF96UhncsikzuSz0hhET5B3lJoL1EPRQEhCiEJPMWUlOoyVJRCpWc+czKYuImj05ilDEycI6REokMOfqD5UH2tvA9pqb3VZL5OLDX+4Mvi62BmKuHNwxH07uG+Kachq5BQmxzG7ySSBdGnuZUQNsujh9R1hGfHPM+zLiTHl3lpgeemPPPBym5JLiVyOJS9YHDzxl05B7l6kPP7beK9/ouTRM3ZHI4OQUoHGVScno42+yudDZTjb2hP0mLil8lX5AB4wX7w5uDzxGDQ1GliKvkfdkQa29to5XJuzeZ7bVMZtuxUD+ib6RmCf4GtYP2f9WROnfdfp4Rlyx1DhRhu4NOp7m0I8cM+nqyKrQxI1vEt7fsLLfb8vZ2mAZH3V8NqqVLE2m0XpFmZHM4U9dstS3VZB1hlzICuu9rbGOqUbWquiyi7SFdntbP2VuGqVvtzaFgBEGVz6AAHX4sf2NbKc9dcxP68G3T7fofJg/09LvrL2I/8z+81TQEMnJAAmgIRg110X+U9WkKm9Ck0c+0hjGOz/mEKiXWA+ETAIYYb2MhJOeXh730XI0UB8mM32LDuu3D0+lsT3dQ8kCcKBSIcgh6PynpQypPiSggOFnM8Pqq3EqTCKYVpQSICT+dHptAt7CAAb1hIAPKpQr3sHIPOa1OiXX3O3yMPI06qg53rjo4OcAA4Gv6j0zyULn2lj2Esu3YrpbEmgsP4PZZAAcIgoIgIhhWQ7oOHDuwd3dkkAHTkuwDpMgQ7oM7u4ZJBndygi4CHDgBIhhWgSYKonsGx81ENMbbGRBI8HvPMmrtAHHvF0ihWRnOmG+cR4XhY/mEwZLzQGmuAScKUr0+dOL/hxGR7Odn9koDfJ9ZkODdoZAwU2A7S10Hz8G9gLDdIuFzA2mWoUMGxpobG2mmxjbYxtjBg2mMG2NjGNCbbTG2MbbY2mxttjaY22222NJtsTaiUcGQREREkgDgeYcN387i8prcnk04U9wAHzchdLL4Ag0uu77yFzcvKgSe9/M9UVAkwJMYkQGB1tJkIgdTtFvYkikQ1leNjJqfnBuOuPnPGkpAyhFvT+T8LB3+oqrO+bBSLyLbxoClMhSihykNIxjfE3X9/WdhXMM1s+0LhaFm5kLvmSih4lcsLwQZvFzTADtHCsgbrmUauhnRthlNLEzCqjWW5zNh00TnTp38DsH2V2Ka2pMWow0nueTsGAAP/tYCpRJexfW9jc213/4u5IpwoSAAxNvS", + "comp_options": " -DCK_PARAM_PROBLEM_N=32 -DCK_PARAM_PROBLEM_K=128 -DCK_PARAM_PROBLEM_C=128 -DCK_PARAM_PROBLEM_HI=28 -DCK_PARAM_PROBLEM_WI=28 -DCK_PARAM_PROBLEM_HO=28 -DCK_PARAM_PROBLEM_WO=28 -DCK_PARAM_PROBLEM_Y=3 -DCK_PARAM_PROBLEM_X=3 -DCK_PARAM_PROBLEM_CONV_STRIDE_H=1 -DCK_PARAM_PROBLEM_CONV_STRIDE_W=1 -DCK_PARAM_PROBLEM_CONV_DILATION_H=1 -DCK_PARAM_PROBLEM_CONV_DILATION_W=1 -DCK_PARAM_PROBLEM_LEFT_PAD_H=1 -DCK_PARAM_PROBLEM_LEFT_PAD_W=1 -DCK_PARAM_PROBLEM_RIGHT_PAD_H=1 -DCK_PARAM_PROBLEM_RIGHT_PAD_W=1 -DCK_PARAM_PROBLEM_CONV_GROUP_COUNTS=1 -DCK_PARAM_PROBLEM_CONV_DIRECTION_FORWARD=0 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_DATA=0 -DCK_PARAM_PROBLEM_CONV_DIRECTION_BACKWARD_WEIGHT=1 -DCK_PARAM_TUNABLE_BLOCK_SIZE=256 -DCK_PARAM_TUNABLE_B_PER_BLOCK=16 -DCK_PARAM_TUNABLE_K_PER_BLOCK=64 -DCK_PARAM_TUNABLE_E_PER_BLOCK=4 -DCK_PARAM_DEPENDENT_GRID_SIZE=36 -DCK_PARAM_GEMM_N_REPEAT=2 -DCK_PARAM_GEMM_M_PER_THREAD_SUB_C=2 -DCK_PARAM_GEMM_N_PER_THREAD_SUB_C=2 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", 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21DmNddSHwaSe9nW2nBw/T4fUUmC0dP3/Pqq6kMtH0Qv6kaBGS5A1ZlDKnC3O3eUNh2+pup2SBrTjDOIDCAqdYD0wBswdWdUZ46EAyr7z5B0UM51HSfgfiYYedk+8NRS5I/SHdfrtQyHUYc1pGbluIfQMNtsHOb7NtDDQNsbzQOF2R20LOw5Dm6GNxj4TAdLGEbjZjrOGhsGhttYNIOgBssh0i8wJjA226hdGTXWNxmhaqbjQ333WQ2A0g3m8BOltA/bcpuPKVoe+5DebY4gd5rbTW2H5D+I8Tnug4X9Jofym0/kjtND+Q0v6r2Gx5W81OY4H8NtP7Dvuq6jSN5wOM/juo5pfdF4Gkk1Ow5TJymHafbPbzHGf4pcvF13XDqFbdUN4r3FaeeIo07RHKRMrC2qfz8YRm4HRj46+QQQPXzlHZGRove9/OfMdBzfNN+SYHDZs7Ldu753kOs855Tpmnuuu7rruy6I2m6hwIa7rvChhMoGl0R0Hceq8o/XfjeZmPxv8t67MftO6yV8gwMMN/nHothcZB1hDrtPfA6GIcCg/XwG4P5XPbDHZPxqHuhjyWm5fiPHbFoSn3iGodLGDuMQ3B5Qw7LQ/IhrQBeB2npvRZvbYBvq57kIehxDmjEN87LGncafLHxGrN1eS2QyddwDQ9cG6vIGGbho0AUMrD4wMQ0jZ98M2k1hC0z8bebY5LU5LmNdq+32bbcLQyZN9ujQ5A+JrwDgbg0t0f4j0mxyhyB3HadEbyGa0tDMsbRBqKqtLh/AfLV3hCAJxWAGyw1di0PvXYbsyCHQL3ZJdBxkPw3Naxkw1l3bJMvGc92tgrf7Qx/UPX/JPybHLEPYPL1zr45fvt4+xePMeby155jlvA7LA95hhm3mq9ZNzj1cswbzUbrbayvlPVzjFdeI0Lo22hkhA2i1UVYTXwmGsrvHSyzMutZO8hjohgaCiozK2rHNabUVYjIroKLDzcjS3CqV4QiEIQ8Q+Mc90XPQmwPZdtrk6aEkPynwMMIQwMIekQmlAhxMnAY+m3Gttv8JrGxCBJMN1rZPWe20MC7HvN7x2y3P8P2SnEgplfVSuitpl5tW1KqVGQshHEAmAM6UJCADea2sqMTBamvjLPY/vaVNhN9ry5zAdHtOt3Pg+ha67i6b7uHT0VvzON97aIh7Y5/a5fteP9vTrH54wNp4WB95hoYeJD4WB+sh3bdR9kMUzIeaSpXe0h4w6mhpgaP839v21/mvy2T8PdbjA4GBhhhge2OQ+gcD8TCHwjJpbHzNytyGTS+JClmUtbabjQUD9RgYbTpAhNCj7YIQ0MBifwGGWQPuITYb44HC3XSGwa3QHHJxhZVDU9wZpdYL7+ESSbH4DBjvWfls/dZP1n7TN+nT7z+I5zU+y238RpflN9oaX5GpofVcLS/Tb7Y3/qN56LY0HruU4z5Gpx3GbjNvNLQybbdZOQfGxNtD9cZOJyWTlDQ1txvs3FlM2hpcJ98xqsPyOY0DS4w/I/YcZpcdy2poaW223E8bdfwXE9Fx7boP4LmNBU5TebrganSchh1G8hbwtwa2twug3GbkMOgOxdDdp7Iokg7A0xs+WMOzZZ1nXdTk7Todl3CxJC5Jtj2Y7zk5NiiSO2bI7Tk2MmahgIjUcLQDvA7wO8DyNAmFhvvsn3/Z/5LX0h526ZkqDfTFl4JYxxQoC4WAgeogMunJ0maqMnNeQ9irXSdx9dxW82pzlvn/b+rx8Rs5XRWNPidDs+vpdzUUeV3G4l6pEfy0JJ16AiqBrjiAZAqA0+uHd9W3f0TT71TSSeOx57G7H2jGMe/cm7YakIVmP0GTax/t3f7fr/7PvPkfI24bTQ573WTDQ0MnCFhwx6z+C+G+wY+K8Rydd+o/XfGHiOu9oP7IfbDjtTDpjSDjs3Zc5qax++Gpy3yvsttofqn1PpP03RewOFkeRihk/CMxhChk7bfG0OU9Fk/Ae7XN908Xt3kAxj6Xzs0PjPfcCTEq+bm7T033DHbeO4ckO7Bm/MG1W5T+EyGGBkwzDRfnAwOizNV1WbMxh9gEgghQL8I2LiGBEYqtjwazL5Tmw2Sn4u3yFz+dLe11dG6fOaV/kKmL9/F8h9P5vRa9/ce7ncdmJybkvd7i/IniMTHj06CAM8QIE05YDLmcGPtRs+1Y9V+C0PQYryGKwgEO8ItBKhhpZtTd+U4UO8MDeGHje0NbY+VsVx2H4eQcDgcLS1jdfS+Jwq4W895sQ8owOS9Ibzfch7bwDQ5zacdldO6OAaxqcsGTIYGGxvOYQ+WguGlNIQKA1wqzElT0hQCsMUXDr/x7/h+nJOqbTZbJ3MLdRm8hp/w7DkH8rycSW3Z5sO4Aj47zh2njDZwIeU816wxgh1mnwnUxg9FghGOYnNHuRoes9RshTmfNzLESQycDtuRlYaKoyLlVVDGmmmPZP8NsfptDyDdaG83B+J2WTbfjGx52xgYHJhwPYYddxgZNDfeMHJLw3HhSpoG+/UbTTSzH4Gh2ZvWeo6LzN1zBhhhoHqDpsmGTdcL+a5WLS+XOdj2PWjA47nOyNx/lUxnknpn2J1jpg47beyhojdZoSdJ8LYzZj4h6rqMPRHXeBoes7DsCHbd1ofyX+M1Om/aHUfC5zN2W857mvxOJ+czbrOogpZTc1sQzhQzRYYogICpmS4UBYUOw4GHw8h603ZWeZu8jlkS+vYifhQCha0tYtRKKRRxSihERtAuSxZFFFHpCA0KKKKJLjBZESQUUUFBSAjCKCgqxGCiw3kSb4Y85j4h+LRu2LWQ6owB0EOCMDSIS0kBQFgooSKCMgKCxZBYaZCEhC0wOAeQZNAhdcNdIMuuOmNQNA05oxbDrulsP5SB0xmaGQ5ODjC1rsHA31xDYGuahHziB3+6MEOADrjccXGwmAaBoQ34+zG9DQOVx7BjcGNgjAgyMk3wbYyHcMkiNl3HjeZrB5QZs2GQy4P3+t8OXc5f12+Zzz2DUUjYW2gJ5hdt6DvOVrQ42QspYVlq+LLFliy1W7lhJhCESHzFoB/f1R3HJYEMDJ+i/jPXdt67JqbAvehvoVt4m+BtNtuPnQsG23Dlbg3QpB7ijcKJOk89yG47rxOHKkp2nDwvUIUHgw6Hojw2yFh6buMfb3Y07wNmmN2IR2wY8A+9/a6o3H+C1DWyHOAyxhYB9gfEDDUhfIHna3AJi2CuqgQQrcAhI1og7a1njJBY4zku6xdv7H9XOcXqAjHxGPkvRGgeuxszwmMIQ5sJRz2KO48yEh+htgdV6ivVzBCrpjsDMa0KO0zQ77ujQGF6TkvRHgbjlIVsDAXHxsuo0Mnib4yvgzqjwa4VQkramlg8JnAUlAwu9mh0zAGAOO1kQHvXJwhfpuGk0PBMrSGHSbLm3uMfIbNRhBiEYESO8hpaskJEIMYjJmQF5ANYGSUigThCMXHs1N7h/hUeFzXL7fuut8jfWYYWGFMxy3XHLHX9x7SlYOYDCubrRJRJsK9xgdtwMn5yQhuugkjdHVXE0CFbvIfyn32nQx8AfC6Rd0NFoSEhIQhhD2TrsdTnYeuhnvReZpmNgy8jlsqX0PMO85LSe+IRW/VBk4/4CFtwj983WY5B9NstlAyMti8D6zwobh5xwOO9oCwCkecZYW2DzgT2QfO1Adxm7jaWrrjB0nQY+/bAepcg1QDF9d8BrIHFYYZN0KYweA75p4LA4DDXGcR3PxJuN+MzoP0PjzQ37NjsiEXfMYEIMSMIMIw78e6B2h5j4jpQpsMY5AdNp9i9bJwcs3Sk54xfJHzXksbB3yECBICAENKEiCklDQbb+Jfa2Nt7dV71/woNADEGDAJlmX5ScDAoZznvemZXeD5k/zvp1fYoNBsfou+0TQjyMd1/VYY3Se6OS8r12gJGc99uNjzlTetgdVtNDSzlnMgHRJj1QJlLgaAO1CBS3jgH4nPfAd112+PG+tmeznfx/V/euZL23LG8P3+SYHNd6TsPVKSIR2GB0HoO5OCntjnuSNLJ0RmPmYcp8zsttsbr7DDD/kP1H8Zm+s+dxnf1qHGfRWYmTieJxnC/bYcdhhyRkqGgzdkyTz2vXPNrgWlNh43jayw5LD8X+JktdyC5eZeJ3XLPPgHlLp7/3j7116LhP4OBndcDeMhyJrlOaNo+zYwX6zWmTcGw6Dmvecek/Zoe+IUZr6H23jbbW+8w9tqG0DU0sxyHvIdVhkhqVDPC2Fp0B+ow4S1jj6jsDsFKt9rJI8yvCyeL9jge0PfHDNzGHCMDbbjgew4i8xU2A2ncNubechwg4zDQ23HELTQhzFwampmMF43HCakkOQHDdaXdeYrdOtoaXibj22ClynRb7wNwHQcxCG4XzwGW5bDmtL8ro409pU5e2NneHkg8wa3aBjujA4IxC7HkPgNdl+xjk6DNOzRqo1FFBERFNToJq52mXDBjzNmg9R13ZOc6msIbjmO823UZjnoe4Phd/ZFYGkDJcgcv+GPRanw7zTDUDruBsB1XgQ0GwyLj/L5R6yOEb4OmMDcHEPRGjZHlbCdkDIICIdzqsx5waRkDganrN9k67B1n5wN1CQzEIQmM1ZM0P+jNasWNc67yM3TGHHOvJz3i/kdZxD2ELo9hwA9caBC08jhYGwVsbGB0XhO3qcDxXhzxrB4h77hbrUDkqZwhbeszchvAwhquqMjQHfYayh2mWowYnWaGdTmu81MOw32luMn6LB0HQ6HlvVcnXDlMOS6ful/5hCEISBAhJI6nGGjR1iIPQIbDQ4XfH7o1tAhdHqsh3G63/Te6CHtyct3nWttsbY4nsMhttbD331XFlPWaGokyblTJpbAaHYHOd15S4REnVOQbRp3iTslpk9IvSk2HoCsQyi6mjN5j1RtzGzk5NOGN3eeGjVY0MD7xD0G8/6s3eHoNbZQ44NIu5AGUPEMnjaZDnuDxjpg7Hr6DquqPScTDpD8ghM3PzJbb0XS5Td4bAeI+Gd/vFd76s9b7zRqN7nFFSVXRuCHau0wcTxMhsa3jYfA5rN6AoazeriIigWYF0JMEaA74HIeLQNIYIwTDgaeY8Iaejs6e4cMcnnjm9w4bNNnD0DDZoMge4dLTdh2LPMg7rfG8NQagHXU8akmOghWNP7xdZOAYBvOud7K83IyfSeCxULaGswOP3QdZymb2nIYGwd89TfPT4TaaJ000ylLGz/IB9YwAZBkaTptZgaSmgcp7L5oynMNuokxaGh0x2WG0NDMdseF3HqumPZYAm7w3G4wAQwW4chCTkAVuYPAw+FqhC61O+1gbzRScLEn1wbbKdCESiaHqgzC74RyxpEJ7vIRDJwy4xvNA47xP2dl5XxsDxOOBCB6xrNthWfqMA8StGi0uFGlSt1WSFUDA5J8y4pRZs0yIxh2GGxk67S67Qw0vtHO/t0gUOIc1mukOBvDNOww7Ia4Ee6yeqDJWp1BtuXY4zA6j7p7uqZlLrvQGxmw4mAdDGes9A40O20j1NMNTOsd9CQkJZ6wbxHJ6jxwcWaV8Zvt8rRRA5MEQdMeUDkbB6g3nOdl3nbeo0tLNlDvOBmGu0MsAEF8Y0G++06QG5usgPYH1gMgd16g2oGIAOqhBIhLp/NTSHtmke30Tt9HD1I4vXbvjq6zEaY8rkNWowDdO7rF3WencHCBy9VwQ3R3GEN56XkM7LJUDaA7TzO85L2nOZPUcYHEOOLgC2BjjyVA0gzbBxqY42nIHMeIa3jbVas2GvIaLTqMr9eoO0Bquq5nWttbmsITGznG+XCsaWEMhpHA4XM40MWlrX20w67xM++2HA1O8BmOGuNqkJvJ0zlBzR1GHVHy2PpPTpNZD/Wzh8bcHKvAZAbaGUzZQ5PK+NDqMiTDyA0SYgQzgep3Nsd5y+AfZd4YZu77Fca7QMEefojhtgxAxQDHeJNQh81nNtNx5nYJtbUbVtbG3MuNVsGmgwKUNIBWwBSB2C0UhN1iA7ZqaD3TUO77vTsdtyW4wzb2M/XOwTDqGW6o6bKl9xtQr3GQ5UJoIe0rJtuhn9ZrZwhrsNbiarGx7TJ2qx8jtTeu0PPVbZjJyR7bJm6DtOuDQ6UOq6oNCHCM2S7GwSA53jcTNm4ycMWtU7kQSMcH1T2fhdkQxjuxtaY23LGB4nWb7s9CNEbZsWnYZAzfBaGTztpsQm2PRe2zdxusnpOAeAu2B0oYB3zsuhDMobunJDft2nmOGkIw0jUbRSeQccyG1LwW0cvU772X33Lczr4zact9KEho/7fU9vMHbcLbQuMIZFujOZPlaR1B7NoaXHd52Gxocd3ZJ02rnfgfVOFqQ7T4gkwdUGpugYnqFnVeo8w5LMGp8L4nLzmbLptDhB3n13fc1ShNFX/4tXrprPTHca2x9j9r/GuYhy2p5HXHhZ21brqPO87uPVfA8wNp6KNLHcflM26Ou8APA2PQZg9jgHqOTU8WCswPdPZ0z2dlxA1a5cZuU5nbaGRDdLpdul3la2oqKqirVOHde26zgflPpPThdFja6L1HoPM9x1Xke80PUAsBpfIM+oUOU8qEPVcA5b0F3x8AhJoRzH8aB2rdG+mWx02bvuk2IXWB7bJpbYhNxhmwPYdFrGh1h7QNjiGjmHSe23C0FLDzPGyOJg24V9VgbTwuOw5bJ3zf0izC0vO7b2X3XGcI6Tieq7Dnu477NhsNt7j7h7knrj+jrj9Bm47J3QeRmMAYZPsdEdh4mSGM9l9JmZhTCcPOhtMq3PcktvtOcbiEXNt3cTBsDxFbWsF0fHYDuNTotRkkBbgQ33YdluNMmT3X5hlb5wXRz/Cnnch8DA3l5e/EogIWUEAVsnQytp7bYNo8RQzDiannbe87WW7psB1HA2nrjd+VHgfefnPVfqPtvbf2rHQ8H2cr4oIjGaXeB7w6ngt6J3ZSeytr52wZHqvAP6vGaT034XWH2G8dIy3/BflvhdV7znvePpQT8H2m6P0+c8oQ/F8/fnhPFHad8xv1Abm0ScZuPPdwmMOAYtODxoeF9sqJvkGhJERMMcd5R+gZH3551z9PyZ1+vL9kPPQ4Q7x2XQbpkRjHpiFUMJGCGIhdeDh9Z42R4ngfYpKz2z/R/L7n5lLoDsP0HA5b6Co91z3IZoUjJk1Pp+KKHuHZb3UP14bHzNmae1R56jyzLoTtug66ENT6Gr3nzuYPfGHVYbsOuhMmeU98ek1PqjdfS+E+X8A+2OUmFxGScZsUycQVB5XMJvrKZLrPC3KTkMx2+me+7eU5WOlruum9d673Wh7z7L0B4V9ptj2fR1Nt0mkHV9MaDj3IIPdZsMleZm1vC223Jk1JS5QrDDga3SfbekyaXTZDjuo32hmydFqcbl6V3Aeu6j5B9n2GhxnFuvwfKjyN8vnScBhbr7byO2h52b7jut1+B8DjDeBtD5kPRXzM30MITNpttpz3XdV7GSaeS2/MeNuvmc7wPQVOjPfew7dLQMp9hzHld1xDyPOW0DxPG9p4W8hmvbfVeZvjjQOGs5WQ6z72np2PSSpyMej5zxD2matrrxoOk6Taai3IPVYQ1GhkG0+TRS5XuG7Vl9e4at02W2Xm0911m5svgZGe8/P9H6MXm/1XA6rtDzvWPBBEmvaem9Ntuy5b9A4Ya3Jdxqbg2PJ35ISEhISGR2fZ9Xi9F3x1hp7y3Qe8cDhjgwO/mcUJyrhz4DvbpqJgmxNjspoG3nPECqgKQfZ8j7VHO6z9F8T03J7VYOi5d7p3HzuW6L6BoGqQ+hnrQ+Ie/yhN5GxwPMyHpOHtx23ttLKsGfEM+w5LQ0pi4GxpZ9oOozmdYoa+k9Jvts8TjHO6Dlv4j1WT77gqm47zuOX4IkhyDJ675HRey3mlxnrPNsvWl1HrtI0g00zYeu4Xfc/EwnWOuhFbs0uW5baMXO7DrCRD6knb/p/x5+s9J6ZY8ww+N4BreF4HP9V6zQ6dL4XyDrjheZkQxiQoQ4nyjaaB2nA5jovcaX7OhxHK9y16jwPEzf4H/j/M/U4e1FTxsdB2GB348L3xpHWzzWGYNj3Jc7pNhe9ge4f2D676H7Lruo3fSeN0nzFkhkS7D2BtsNb13Xam815j3Jcr3WGGhkwNFE2HujlHdL0ju47yNHKzbXQe25g5RjSavMIdh9g22iG1l23836t7xuB6j8979wb73HgeBsHtsPC23toQ+cei/Od52Gp7jmvR2HPdFMqt+a6g9h9nEf6f62rdHE4h8LJ+UMmh0gpGkZPffA7jzPnZoW0fQMDpg5I2IUAWiHxMFBEdVm9p0aqBm9p6zN7T5mbQ7NAwe+yfjJMfNes98zXXH42lsbb4vvPfbHxZD2W8773Wsf2cpyXWd9zGocTm9/sK4nwTmMZLpga2q4+s4+ozeR99zHMew9M72ynD52DTPv/r/2OQ9F7xbLZjOM91wdFyx6r773jiMYpGl6r1HlHukDAdF7lJyOh/nWsw3vxctDUj5hmm3E8fxEBnuVQUv0uap2XMem/h8XTfffK5r0npeRkrytlBhcdfOec6bnOMOOaghlki9LwmEDlGLnW6LzXo3OjIQOMdPQb+odyw3C5yEDBsWeQePZqkSJF9obrMNAof2Cg4bpeNtzxK1tqlyy4OlJWDymnTeGs6RsDM0loyFOE0ai7Kvxrzi8yteQ8WffGOdZKhL/8QQ9AVX7Yhbu4H5YhujX0uxfFdU0ZkndwRBEEQRBEFFFiqKfrEHUiD6XTCD9Ig0ltRBZEGqtiEAHwBBZ/8CGkQrIRACYEIXBEANUEMCH9QQ23vIfEwMkIei658s2pOV3vIcz3x6Boycbed15TkJCcf0rvfe2MB36p23vPffw33Gqkuyghlk2dRJ4bTY+yPcfB25NfgQuG41FRSGV+6R9k9k8XeTUNRs03V+Rw5kzXibOqLIz5frnEDBVqCIoGIlpJ4+5zXE6RYT8nDxV0V1FYsigqi8XW42by840u7sCZnFN3iMRcJHJovIOuIeXPZZFqJgcT6HJyciUpSlKj55938bj6TyOo8L8owOHDvzzCDdCTts3ceN5X2nL5OGbX/NQtu4CSdulKVqhOdZWgD4Ha2bCRWAxD8w+SQgiIiIiKqqqoiIiIiIiKqiK2hD+hAosKqrcmquhKgDlKoirBVVG2+NKclrzKm9Lm5Tcl/IFVdtVLTTVVVUoqrVUu2CZpn6ybSZMybTf9qJv3yvppddhtPWbnM90AqanvOrJ7MjOm8rU5jDrmOXbtrjujT5bwDhXEK4T9aKd92xhs7DHjwe04hTNeVHI2qqqKqqvA773vuEz5emznJzghGMDQnBttc/gzWgQkLmfNjYjDYzM1rtqu2pRVbVa1Cq2q1qUVdT/nl+m1JqTZnCF1NvM3kq1JW41MF6Xph3jOoCGh5Q9UURIDYbruHKJJISSJIRRXq+vmxvXLRVXecmdu8dwOj+tf5nE86aPU8IbANLT0tZrUVFWRQVRePy04M1005gJoRIG2N0c+SE0ucIG33WvMvaOTpWsqKra1rIqtrWsqKu9wTbzlpUv8rsDYBil2dCTql3KxYMrYKqqqKqq3ThdWMgrlDm9ZkN5GqKaaWqKaaRqilAm4zJ1LIMzFHGCVEIGkSEvYbKqxZFgqjz9r5fO9B7T9h3nZYIYhCGB0cIbN/OYwCHaHJNkmDsn2uBvNlMREcOo3XZdph8DicWicjS7VyNGUREECqLFVUd1qs3J2Ro5muvbVUVVFVRzw4x351z2Bcve997T13vGMH16vYnCG7hu4B2bodc1nxD1W+4XC2ZqHPx7vU0fqtjjIbrDDAwOmO08Io3neUJCEnNrHddLTskSgiCJdSaTnId16T3jx5GP/pZinp23F/A7P1XpHLPK/n7Oy2312H42257pg94YXLGtYNhcrOiWIUGBYNXdo3XP+09lDeNQT3htaqVQmQMjJZMoGBycjbBMmy2NbkvJx/le9/O1nPey9l0T5GT2X3Wlv/c8Ln5+06DnjWwhAww5skNF75pBLPb7jvG5FiFNuShEIZ+NQfa0bk/pVZU6YxnnfG0nzWLreGGGB8SBYUZIhIZyL92/XqV5f6mhR4PAxxvMqC2KguEQ0GG4zwXv+akddm4SIIm5j4vNPQf0BD+92RDYOq6q9GH0/TOQNvB1x3GKwdwQunU5vON7tiQ+75HZ9NJaFqltUy5ne0667cW8VxBImTLBjQYMee8IIYRZlU3aB6DjCFAPIDoP4LDoPyx0nSeN2h5ngOhX/f3rNJwihKQFnCBxgAUREMxRQ8ZgOg+Nj+LnZ20rKcSWJSZXwfLLI9/A7eiDO3WjaXDW8kVCSviCMzcKwFPGFh1F3wPxsdQ6k3Ofrutw/T6R9l34h1+iG2NhzaQ2dO8hIQ/Z+DtecQ5qfjsxXo/FL4DoCEysGkwK4HONGwa76CNaQWQBcICA0nXNxZ3UP5XmSt5qNPUwkFCjEo9wqiVLo4AED1rcNtvTYdLndRfTZeZHt59nTvdj2P29F0QpVxRUFvzCC7K0QrwhImu3L+pO11i35CILvuaUX7KN+4XkIaCgiCH1sB93JrY/bBYGtpgZ+mdIjMlYtluG3XfMO+8YjTLvDRFxh5JIuZ3OkmamZFEmqMzSNVVUC5Jqpgy7u4cPTObkCSL3oyrpIkTExERERVRIqJMmFiIgkksXIJDszMgqBeLxERERVRRuzMzMrJVE1FRERERVUlVVVVRERERVVUREyL3S9RETMREREVWX6OHOEPtCH3hEzBR/4BE+oKrIEPsAhkCH1BDIETIRPbijmIgBBD3AXEUEVigiKCKxQRFBFYoIigisUERQRWKDERgslCjoFGwIfREMCHtRChCwIaQQsIfLFV1gQuIZCIAfYFESCGQhrCJBR29Tyw1eFTcLcakyEJ7c92c0oxg1OanEZ3yaeKxx/rAhgFVoBCQqv54IZgqvEEIe+BR6whvCIolCq/ty6hwhQYEFYQQiDVD4glKwgxCD3og9ebG0rmdc3wiL2+yIk0iFAA+MKIn2uPpOxDpdHpfuiQd7DoK2foFm1eMIgpEDwIHJJKnFrNPLBBCJJNSq/l7+tnCgMbBsCHF1v6AIZO6WvmG30MujaBExAheBDQEPi4M7i6tIqtYquiKruGcqshVctxkM4URMkQgEUwmzyRT/RFRAv29XKkZFHXqEOEVXSEQAtCECIAdQQs2AQ941QQude0IZ4CGPyiGWKrmIIZeAhEKwTZFG8KrfBC2AAhVslsBVaBVYEMIhdFHEKIl0QxgQ4NwRMv94QlgFGsUdUABDcEQMoQoAAQkIm5xaRw/dIg36MRmAhsAh/VFG2KP+8VXYAQ5ghzOODxyMCMFYIWEJiGmIfj3BC6CECHU9gfwYd8Q33673H2HAfmM2EPljJh5xrZvWhkzH7g1DAzQ7DS1s2phqepd0KmkLowQw+szGGSFVy4N8H2q2xSMcDpENI+7B+5A0IaGihi504A06zYybtNOTrMfPdLTdzQsBT2jkNP3rZjZ717DJtP8dk+N/IGh/kDJ9d8DQ1jDJ5W00Mn9R0G87Ix3D4j5LxXit3sGzxWzRCmBweCbso1j5go/uyB50kJs5fJlzQCcM0U5oRERVVEREQRWMERERVVEREQRWMEREYqqIiIiIrGZEwS7KmXMoGwcQhIdBz3Rc58AhkmxjDjDrOAcINxhtN1hm57eQvDrP1AZtLW2N6DGYm0N7bHtiqD9YBDv8Ih7IqvlEMsQ+D1AQ5hEAPf1QSwQ7QqvfBCYIKH86zu9MHoOS5roOk7rrPQ5QIdMVylcsB5mpgQ0NobAdUC1Mei2gbHaGltDMZANk5IYzMxh5gdtoug9AHJSphm5DJkPM5TNk5TJrHKaR5ndHJG6hkuFxO8/oD9pympy2p1xqFc5XNfga2ozjI+bYfwmgpWMTdaSq8xIw1mIsKGcp4mnyFas3Oa3gBwDaHRBttTwgXGMTmukOi5zpOiOi6wo2zEeodA+jWKPehEN8Q9QRADu7TlgRwCGo5w9BChk4Gpw6Lic98NbcKnMZCjughAo6DzmOCHEIU0iE3Ne695+67Y7g4AQ9L6REXoCHk8wheERRL5qAhlAZ2c7j1kKxVeiIY7jviff2dL1zOEKBC0drJAQkoXKNoQs3KhDG6AIcPkB9Hr0lVSVVJ8z0qSqpKqkvekqqSqpL3pKqkqqS96SqpKqkvekqqSUuiYRC/IEIEL4quoIgBO6KOEULUCFxRyyNjjgIQUcCEENqkBDZ/xcrm62TRrAquG8gKl8UYQUJHtCG7i6Ao5AhgQuKrdQ8gQxYBC4IeTsxiHMwA7Qy3wRIMoEPR/G8Qqv4whniIAOBBUAgpEG8Ov4XQEGvWyFPkLVhzhonNmsHx+976eRM6Ody/XgIcA+aCHiiq9uAhuiGBDeEK1Qy5miIUghQCXgToCJOYo/xb2bfFV8psbYCFwABC8CGAjZBKAQkIgBACjzl0QE26LXvCE5qFQhcBDfwiGY/SrtiEAhiyJghMGAQ04FGQCQEmYUQKSAiQFIDEgMYQjAimIQkAhBi5o/pFCGbSIXDFQIYBCFH/HxIn5v9YoEMgRADAISVXDsZ+/j5YIY4hfERROQUckQyAUdPWsFVyARADCKInIAIZYh69FAhAIXDH5c/TFZMshDGIGWbMVGIoioxFEVGIoioxFEVGIoioxG8EkuY25NO8Ifj4AQznOq5bBC2IfBk3xRE0wTbgQYhEIAIRBbBBCUEwIEgfEHz+U2n+KLzb6b4o/HFfsAh9YGKwH0nPapR7BgCeWQ/MBpoGmA5tqHMCMCMGMQwNgwMSDEKQ0K0h6x6a9WPi+tfMfBfWu6/dvwH7aeURH5blD9cQznC+6/NHGofbfO8j8L7jYFTCfRHbZvfbwXwvq1jQ0Oa5zfcGB95sbiF5sQmLUREDAUNlCfOpGkGb7AMNTcYcLmNoh95+g/C5TNhut4soaGTlN0HSJOm/ovRdFpcmHKdNk6zS6zeD6Xxtp+B+Jpdl0XEfLvsm022GTU0t8zZMmbtN1k5zfM5hwvxN9ympwF10DutTY1tT+U7LqZMGiEpt0bG04B0nMch/IcDluo4BvIfUZum57Y47vv7LrO+3XoN5wOs449hDbHZcl13ZbByHTckYaG2ybT1By3GbrtIaDjOtuOAsMLtu06o7bpOFOicBmOWUkjMNR1W6yZuq4GTfHC71oxmdWU9Bx3ZbTluK3M1mtwsOi6TSTMk1HMAzF03Lc3L03dYcA5vC39R1XC6jRjM5mM/pOMhjLlYzbcLoNttshwt43Wi9dQuxGc0Oayclsqct0HA5hfNFxjfvljdNUsssNdtb9wxi4uaeIJYjCYp5Y5iRSJUKWWS+S3BxXuEajAfgZ9+2QJlUM1StXNBY1gUyuq2oqAwFklJSBallKK2aA0Q57cqqDSQmkp4xVU+xN8VTU1O/dZg0cbedLm6DjtTxIWgd923CO84H5FdVXTGp1Gp2c+CIzcyJ5sRnxQZPI+vusnjclk6CGS2N5z24ydNvvA0OFtYZwgh0BDiUk71Tbg+J7g4gITxY+L/68u+HvxiJ81jYPU9SwniPcvSae8YWJ9YqHTMjItYtai3aFEj6okCD7tXJwBAjH1DB0uY7jqaMMtqcOTY0pm5EbAZOCsYwWL1VDTEI8VgYQhhys6DKezeclrbp+fQ5zQhhENMwfhH8mHYOn353P4R8PdQ1mPXY/FGPLoaW4x3ztg8UHbbN1MA8lpybNIxTNw0GHvGzi7z3smzYfLpp9Wxpwxp5DG7BjYaacmzrNMQpBjBDOKsg+lTDuWwOYiYYxjGMYx5DYaVg5d09N+C8lsNIfCbt2zkaPYUfLEIvWU94rFWlAEMMQgxSDgejGNhiQps0I87IQ6DYfEfssabjk948xpu+/Aw6mwMYMGO44YDFbA8/nWcDVOTmN0NdjmhH9y4cgdI3IhAjoLNnQLulzJ7pnE2DsDME0CGT8NpX+Ab2ZRoQhd+kFzgIVpC7qP7joOt6o0FadBNDau1ufPzMmGCFzAdPqFFiqOdXznQ1YfevWPWAd2WP1di12xR+zMF7BMZUOArZKoq2AMCioE86DjGhooFYVE+0LQMkjvDgTMncdPT0c8zczKxYjDnCHg7oyZaS77MQkqX3puBwM2zTtMY8Ru7Drt2wYrTtZbNh5AQfz/0aw/sUtiQRGIsgBp5mP3HDVVVVVVVVVVIEgbKBBCIQQghmo573cvA+5kkzNJpKKKNKGEgMBCBfJN2mQiilMKYgSEDU5ckn64GWyiBtGVIMAGTpDkcwWPaMujFZ4w/V48v/V9FlEDzh058vwPOEzs5VVVzgzgzgoKCgzAJkBAhPKc90ZNptZiORsKsUWK1kSYhgMYoCMGJGIsIaEMhERSbJiyQJCHOc8gfdO8bvR3zp77wtLdGav7rug+Qpf3H+5fZcgcPdNWWUAXW+9cZPqp1G8c743KSgP2mthsxPqPidQ/ovV6prvG8mmeombsBsPqZ5nukZbExDkHJcpz2nvnR4whm8p4jAJCBzXlMG7GIRgDGN2K0DlDwKLTxnPVLD0hCRkYhEAkHoGP4fvtBZ6ziyhaHqGeiA+gKRhEIDUuGR/z1dA5uY2e+d/vnfwb5v7xvdBxH2w/AhHHEUm6o+ybLyeg/SfUsd1+a23ujQG69c63VOagf57vtBzUNjS3TGqLPbPbrbGB7LA+42mgm23uFDfwEN62eDtHakSkd7EYpHnvplsYmoyOk5Q1D9Fkw/WYHKQ7Ihu/c9zfpc9wCJP8uTcGgy2bMbzA7KE2TJrsaBhpbBCaE2pk32YhJDtMDNmydluMxtvdZDS9D/ABogaWkbbrNjY6rrO41uyw2MOy0uFwUDFt9V+2hPTsffdIcdyWm+3Bm4mhvtJYTnaZthsuM+VyXE23dbrO77Uy+IXHiHE+g5H7AOUDQBQzozBxh6I9EfaG4hYP5/d1tjFl+mIV+eycthhyX8Bw03abugj/XboXH4jHJ7Rp1OyB9/wnJ5T27S0GoODKg1JizFF4DkTfCBuzwXuuabHEkBQBIP7VhBt8E47icdxnGc16jnJt5uPHWvuoe+D+iP03SdtsZMPI+F8L1nvNLxjeOsMF/qPtv8lodAg7BH+o6z+6hMew9F126zHsj33E5Y0NLU/Mfv226zeQqe+57fdZvPeZNDheVsa38V+Rh67Q9XAN9gHxFQhNCbDbckZDjmIulY0thhamh3pVM3hKpzbQ2PCzeGrdfAd8zLnqCGDHRte9zF9Q2w0P3B7pofN7APHd/3aHIuJBy/lfnAIZiaXer33il0SUwjxa2uWwBRr759EglRGs3bc24yGR44r9u0RKcv3xCQhuiHUELBCQQZogzRBsRB5oQZQg9KIJRB0Ag0xB8YQ+KIfHEPjIfkIfXQ+Sh0UPiofhoeChw0M6BzUDwkDfEzzroghRKKEEKJRQhAX0LSF5C2hdQuIXEP7VC1k0as5TnO07+yAIWO85Xb7bd5faGrWvry1reeCHBFH7aAqRCIRCIRCIRFMlDGVSsixsCHCFESWw3+NCYcDDx4+9LSQ+wh+gCE+F4Gw8TdzZnBIbD7yhD1goicQEU3BR+WIfKBChRE5KHzkIhEPoiFxDhAIeI6nlbCB1vQhu4eqbnFMXTcYdqSjXFGhvtB7YgQgQiqxViqoooooqBA120unXCYZV5dTTt2BNchN6jxuN7nw9PqciPA2rBrkcNNdgadeFdeINzzJezCak4bSOk8gYqjzqkMbNxqq45mZnraLXeuNvgdfapy53HssmE7jT57dP/TZt+4JNfla61wgghCwyuMIODEhQNJDlsUOkhDd7agxA1d76dcoQ1CGlD6uYE91rsXAvXcpnT4s7cbJWKKKLzMDsHXsffpcgJf1ygX7pcbYQ5/MoYIFDuYfJ/rzx3h+8WUfzzSjmiAeC6tY4wYebsQ0KYzt+jmOw1Za7k3+7N3ZKxu/u9yfz0y1fNbhRnH/XOcSMSZBU43jjBfL0pB7YvTyqdRkeEu4S3OT4h/FAXa5FlFUNNouDqWHqcgjffIIHyNUXVdK98v5Jk1CAiCgoKFRGTqdT1lgK+afHfWQTLQ1LlZMmwWMgdApylwK3chl6fnuP33I2Nc5AjIsBSAoCkgoSRSEgoCEioyIJICsiSIgSChIcAQ3GkD4DQ/Sbg84s0FmDTDeYRpsWSYbjQ02shYj5JcblhwwQiR+C0UMIMaGNDAg5NBTCMSzbIMOHDk2KcOGxLuGsNIWcm/mGThzLYbtiElioVAuQhJJlhhcUyHIYxooYQY0NNUwYDgGOYODMHMaQe+4r3mzG4haCHwRD4NmbKF0K+mCEupoPNafYq0hBCA8FofDGDHxUofw4IWfNKfK8o9j1396R9Lzyn2/aQfZYas8rzZep4USCAD0uXlafwSI50UGEwbAR8SiqZIoSbC4UEi99qeN2H5ZlMRHVISNogYQMgcCObydzylFiIQNX3+kET/yr/uBtELQHZG47MGlGMBsQaQgxiEYwGA3obEQsMYNJQwH3P5auHcgD71jpiHtmIWGhpWn/orZj9RjcGDAYhINHYlkaaaGgg1FCmPIGMYxjBitMYP4X3CJ3bAYMQjGAxCMQgxCMRIxCDBgxCMYhGMYMYxjEIxjBisBYwGAxiRjGMYkSMBIxjEJEIMGMYhHfR8BiFmDGIUxWgYIQYMGA0xGhppoGK0wGmMIhKjCFAJGMARQiAIkWLIiLGRiBEYyIiIoqIsiEGIIiIqgxjGIRiIrGAxjAYDGMgipEjGICKgIpBjEkRURURURURUjERet8cgJHR/HADTWWitKSMvpiLKJd8YUg2Mrmo+Y4EnZXyCgwHQevXIFoeeg9gR4q7Dh3K5Hk5A8rxFiiqLL5zAxYIrFWKsUcs6V6ZO0JfNXUw+Gt5i5cwhU3t2523h4+tzb3C1nZ+lwZJ2IPwsGLD/l/9NTZVTPNfbZyH9OhoZhkVUCJ/1+Pb+H5MWXlqmgkRDftPrkPlPovasPIJPlmGR7B8FycnMoZmVdO2c/Zd60U6jGtjpN/eFz+2/R8mKzH0d/J179TLyp8vLVApXKx65vk4K8On/M/eoa0Pc9ysm6/t2rtBemTSYz/Tij9Tp1Bk+b/D6fEDaqP6sTdHGv4ikf06lCcDPFo9eauPayeGgySIKGEQovw+R1X3cKaDoCYE0AjshCksEPijSlQ+NmFSzFHj6B+0WXi6XYmXLlyL1JU3qytqa7Cw1vd351u4c5EBeMGeXWgaUIHpIkCoICTK3sooNzn64DzxzLbg8Wr0jei4aIJa7cstsbiTqD4AvNiKzSlpcn2jt5z4ilcfzXn/M/Ix+8f4+vvnhwWjU3hwnEog/6xE0GwdOnTp1Ng+WYEoduUBYCgOUOAMoeiJpEsdQKmrF6HndMCdi/+LuSKcKEhhErA5g", 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", 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", 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", 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", 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", 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", 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QTHLjryZZKJAvVE4WXbs9HnyWG8x9/yylLCUhB0XBCVS15O7F6SLthDDCTDM0ZPCxnSV8aLXEvOxuN3c/VmWGK42YkXucALbgFxZOJ7pKqdVOB8PpcOK9irfFY6m0GASzYhV16AB6Asjve/+VO4PQm0OnFFn5AR2uYaVCBPaaFJ/KrG+0xvepPeHoNPXLyIthZQQI4txsdj3Vw8Aj8CieGJ9lDjM9NOnTgCnAFSIneGU+Io7AqXV1QUV/aBWSDyLspyFuYeaQdwiLHZprZ09ijrVZQxHTpCJAIn8ECWgRxtumsKXoXrc0Ulm+KVMnl53Z7p6HPSX3QkcfxSrWwA6/OPO/Eu4wS7BLuFWwM45We6DJOy2jmSQw5bjLZYeND5xkT6rABOMCbGJsq5SVar1bO8JeMYzsz+zgw4tDWVoOSOIxjetp31ixXEsJNjY21iWrtvG4AzE80XMeyfc4GJ2FOBKr7Dhvn35yd+zJjY5Hzu++45G+9X0/F5XN1/Lm3vBf1gxuDj3t4WQPuimWhjpkYxLgK4AuaFpUDCpjOgkFQoFQYKhAVuWTcOxSGXguMbp2vItcbqFvukS6h31ub+z1aT/LFYxcrSkAR2NAdstUYYwwmGC44XNjSs+VKiin5Zl4rfMBwAMLbHJ8IM8CR31qw2jVBKqHIWiBO1HgalvcuvReoN4Te1Lap8d7juY+Mqfc3CGnn8jB4tWWfufubcmOpG3DEF2byTpgSHizvM3U+Jc1CtJVwzpQTEI475GuHrrWG13BItMpWCOwje0ASKESU1wAUJJhsYJP6NdnM8BXf2olLOVDSAaCo8PiZTOWYVcHphGxDlFiCRt2Qy7Jbt4cK/t46oeppUi1DnyvO2iXCLs5ShT1OSFHkRyyBqR4jxpt3d3d3eKKtMtNX2rr6DHr6G0vtDhRdFs+Fz+yl5bxo7IpUIZUmDUr3EwFcqSc1J4D2MznckiiVqx5Dl3lvnKstIggyEyCDIMzfvwqrdqc1YprU/uN8nhqzlDutu9N1uu2zmvsDJNRUslSo7RMBaUEVLME4ktKWKOdew3G6kCjYrAez68MhFJCd3fUabqHoNbIzmfTc5yRW3oL74F7ILWf4AvilQFCcQtzm1HiqU4bqodC7vpRnSJoRMC7bTkx6rdNF3kd27WsglkEeBLAJBE2KQb4Vmrbgfp4N/eU/DKMr0NN2QQnP44/lc/4WN3u2rgq4KqCrguLKR5oAkNJOyNdm6GH6mswOjzXRce802/ZOTk08DTVqEq0j5q2Ok1V0d7WWTDABMAEiCwgWxBahhmNPkb9oAVHrR+XBowwzQU0FNBTQVqYCYseWqYCFQuKZrwjihHd5c2sGKAlOmCexqAlQE4IsIExbf3nWXkR2EOHkSiRxMpUXS+b4/eokjqg22rqOr3HZCka4XMLCQ3cnUkkTV6p4OB9jsri+za28Ra1apbvaxuMJE4WZi5+t2L2Dw4H4INBT0kigL+AEDlMnMzhljpWOlQ4wdK1MNXLdLWcbMDJq4qO+11/ZSsrNJKl5mVIac+bqwC3bviua4FrQWTrQX4u2ygVWldqtVRjsd6i580xaUGOBIgL8QAPIhPYIEhEIw98n6A/MhdrF9P5F1eRSL46FfULzkT/Hhaoto0vjOJGxizwDP1iCYPFwyteoNBAfDzYkvmj1lW/bU4C9uAVuAUsArYAqsiBHSBXQkwABcTHeDWEwM3NEUJiWVBzUT7UY6b2LqtO0J8TCu1YE5JYQOFeqjK1wILxkjWv9g+SCYAPrgvxgTkl0QVL83AqThQYGekkS58JJEuDlSVm0jUj4YtqM6Gmw8pKgsVFeYwGrRaRn0UEQJCpaPj3LQF4mwSGK4i9SUGCwFWroII6e1WqzKX0xYaMOou3vES0aoSFgnrsIgjCQroWeYALABYALABRFMwyULD/jQ5fVRNB/Et37DMmgQ9gJxIlWTJBZmbJLvQDasEs1XO+cvZVIkVtqY9E1tCeVwVcFXBVwWEJB89YPoY9MV8hFrMspJHKkUiEV8izOk0kK6LL2uHkAxiMw2PjdPEmG4EzJkZ0MfUbba4TfOVTU40FOy6pjWqFGx4BbNcNtD0MItOZKihViWtr1Kp7RGiGKqQaYTtSoVCoSR9ZCbxRcI7uV9QjgJUC4CXAWOCjPwaOGp7LDWQkkfAoVJKMKrQT5GqPXbeZdvPDUnQyRmas4ol+IxaAxgPacjSNchP5OzThABHmS3kND3WDKNR8otqF4w4vyjJUtgssEIK/BX4K/BaEK1wqk6iGLTByQieHq7p08tl7QUmi4O2C2Q1SF1Jr0hfoz5JcK4jbMt1iXohF042qSQzxRV6ScMmkfFUfFJMhAykgxHmODs8AN0yfmBgy1eXDrE7HPz2rCME659Ndyuu31AjALHBY4LHBbtGDkoWDbSC/TIYGSRdPZuHr0yHuIK0BvV28ECgSO6NxglMiGMHBZNIxqxcI6jDxCRNbLEdZou/FHHg8bYIujm44tWkkWLlCg2Qgs+xMt3aInnW2b4wEnLMQFiAsQFiAtbPJBJFICIsu4F8ba6bfXUjIJkZXGCxbKlNcPI3iM1TkIkW1LCQ9JsJD51o45DSHInl5dmuxRw+VCwCsArAKwCgKOSimjeE+oE9GWEhQZdqwjRkiEkhi50TRyNaOCkhFLckVs8XK1aZtVemCP1jZyZCabpMg6pgOQPqAxXF458HXU1tR246t1+dyCVdkBKr1ZyhERD/lJgPIKgUIhl8BlBQIAGyRLV0gKUwUqEV0JJDwIK7XiIX3hqMrqTp0a5BHR9Tzp1sUuaQXYTK9l/PvTJFTBBerHUdJIj14JwXySCvJKlUPf2q9JgpjDAw5PiBQsR30HWFBDyE+hApvJWcMFihLCyJJbEzNi/4zbQ6y0biNdn0zTyunG9PLQrHH+Tc7fqj1zAvBLgvUD5w32ctkvcmzmsib6GPuMe1tvJ8S18zeQfLt9zssHVw+ZquhvvBlZegE8+1AQ/oPK21XEU7bvy3/ivuYFuDSJ4e0UnCS09FeCgGV9IcQuk1zdJy1shZaQ2232cLK7yEl+LvZdMDlINvDKrfUEICCSIFAVsa6ApIE+Y7JL8flCiGvVAnVSxacfZ4NQMqpGZVCNA8d1UNdR4QimCL7g34oYYM4Dc/naYfosC0zxzygUlIfLOFolCiep+TGMaRfw3GGzB0kZskFplpH6yAdJXCOFMDFSGoajpUv4maz/E54xZXamDGXLwRl/IUBiRSgGcgWoMSQm/i7fxsCIJcr9FiLm8wsxdnRQ/D0eq1IAgEabM9F7XrVyD4LdZiwKt1+Jk0ZhXW/28nyW+V5pt8qNGQZi3zpmhwtaVTSgIOU4zK+0P/f/J0ASToFtA8GcbsFUjP9eNoYOj3ikCzsrFITdTDDsICyy1amfkQslx+BJ/ujdMgw0jRu5bKAhz++VhaSglPAn0f9xvnR8/dUAmTApjQYwHLVrjaVUWkG8RONaBRl6AjdRiNOxv9NgWo7hPRj7NXbe3/MJjmXh9vi6mSuOYdZJpojCYTPGubgkcyW67DibLYZGBsumxZoL2PVqMdfP+fbMNtuojVbTSagiN5C3/9ONkeXpQYwDzMzMJmSO2r5jCO4c4QRMG54XD9CSqjGj4O7LdY8IbFfOwPQ/PaBqptLsVBCv3+zK2+9N6b0jPwd9ahR9Jvg+CMpa1+qcc06FIOzZ4nITVDLqui8xdjew2M0nfvFa9qIGayM4jhEpOcU72u3ZzpwHYCZ2gM1X5AScEznXzseWpT2sHXT6Qp2MJOXcPA05GzNHt4vevKUzAJpoDMFicbAZMTpzTdp95spoAs1l/RcX8+xfB9pzRX5HkYjsyq+FgDCzqP0DL/NEiNaV/Lmj5YUHC2ewE0ZFNv4th20gz17rD5HZp9ezcvytbV+W7Zc7wgjRvMMY9Ly2ZAmCQI7QPLCYh5bsZTmTDwLOQy3nFHCHxjVX48wcsc8JaTZWv2qTcbfNBjf0VytXEvM2J18ghhfx/Hiy46eSdxTlDu0UpSChQF7AQQdp4NhvhvEz8vCY5Cy8oKGonfddoKFEHT9JFG0aab1rBhZMIDDAuFyRmjxLhUGWv9n8OaEjxbR/LlMLE5zrgPK+lCHECbIAJ6L0kVf33rLpwNJM2/jZs5rLm771hRftzs2am83GmO/yomdnT1JT/++aysbO+x6PrtlpUcP30I0+RosnK3NkVaqqdKUnVSlKTpVVOPC0200Wz5LYGPsI9n399Ce9szTtN+sBIgFsTL3gWuQKCfstdrwFA2AIAyErbeG8mJfbpkDAyUm17kg36PWlnJ9xwBLkkvDADuElGV8zAYiIqXv5J4EABIhHKVUI/uX0Hw++GQ278ZChD5EMEgjfGPm1jgGNHL+V2Lv1N12NTOOMPu8nkd2TDtuPP38gSQO4+BFCQwliEl4NG+T5wL+cXrnw9l6Ho5LQJewolOlSxm5Myay2rp3zETq4OlwmpaatbAEA4kG/BTAZCv9kBiEytuAv6WOvEUNV4j46M7rNR3/3mb5bozid15/hf8VsZ/1zoUwQmmiXPLsb9wp6fAuYMb5X8mAmonfr3XcjvlLB/o/8aV12Wtu1BQMUmgSIYCGxJNiOnaF44JgMF9EIgFBCCfsoN6MPoKufKSbuzgl5yVhMilc6+VpKiJy5d1ApMEXoJgrdpvcVEYZEVuoCqCZf24k6XirkUpHNRUKTE5wCcVzmJ2MvqFqsLQgkswOwLCZKxwDv3wc4pEWrdgCtp39Vema1TOM03Abw9WXeFgJuIPtD4uHuB82go0RpmNPGQlFymsikh4Ka+u9GZAowwrlLWFXQgKc8bOFJVwxHWZGlOL5DE92vn4nsDw1eCS1HR93RdsRkCpHRPPJwbEdL+WWucqxUPhmpkE4wBjVAni66t8Y2e03Q1Ftm2OuAtt1Qt8wFhSIFUCLpdIUkgY0vBYrMvobKkg+KxL4FYiBheMssxkgsaOi7h2hvE2e3yPd93a9Yw8myF8K8Qj1wOhWObwT/Hu2QPsDFRr7LQK8xEwbetguyXfdJLPd7dlK+8Pu+SyKqusiMmuUr+IbdZFooVlZBgLUlXUXkiUoIiCIgiIIi+SvR31TIcYBcMomWAoprKolUxF2QROkgpaqciCwpMVRWqxrBm8G43gmCVCkUKEEqFCRu7GDGgvPIHhL4VrASbJdprkZ/UMfhKQxDGobZB5Xr9nye/hsfEyc6tqBGE8J4HaqCsPmeMxF6Hw1MskluF07489VQn0KJNDh96PRlgXrNJF94ldiOV7AaL4MzmMakiK+qh1DNr3jLVxqbq/zPz+AOvau/dIphCGmf7uw01V7mJkT+0ye5wsPm3cZ+8Oj+iNDuxBIgCVD2YOlrrz4gUMzm4Ur5ACDjnK1+Hmo/7LOdeUiON9k+X9Yp4x80qGWHca05Ph/Um/2H5h+UOL0rPGxantoSj8OWXZ9Euyrvuve9TsuDcMDuvDd26pQtUKNF2Y8SGmaWFZGviN4xunO+tLHdz3n9JoCEbgBvKJ5lp0WjGeB4vCDbPBiQwDBgKhjHGdttymHQnxd83ja7+9vLyMPQFYRDvL8xtCllBjZjDeHzu5LJ7JBSGvPsQTxpnjbk8u4Vupm6lXL30RERERERERERERHfkMbGxsbG2htDaG0NobSIJNQ02m02m02m/9ybbbbbbbohGmNJIXa6GNhUkg/7l4S7bS8B0wu6PKM+ZJ6k8EWfhFmGeKOmEa0pFc7c/Kb0WMM4cHTanVnuTUGiZByRiHZHfnhGSeX5RhiGqAv6YjFji0Zo9svZYbuHmZLWKYxwYKFicnCz3HZyLWtoPNtWmeHGXgw/UOHHOCcc2o0SriyimL5siYJ4wqkqlMLN9WuqKKBa3ijeKSAe8US/pIHQnDdTfkSOEJGZGMaLQDEIaV4kYCkw4HTwlJH/i7kinChIBLNt1I=", 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