[MLIR] compartmentalize build script (#369)
* compartmentalize build script, temporarily remove dependency of onnf_opt on helper.cpp * fix test includes * fix op directory include * compiler -> op * compiler test depends on boost system * fix function name * specify libcompiler dependencies * let cmake take care of transitive dependencies * remove unnecessary includes * use ONNF_SRC_ROOT and ONNF_BIN_ROOT * allow whole-archive linked libraries to be appended * [MLIR] Support filecheck (#371) * support lit+FileCheck * add lit into build script * format MLIR.cmake * format cmake * [MLIR] Remove input/output ops (#372) * remove input/output ops * get output tensor type from symbol table
This commit is contained in:
Tian Jin
Tian Jin
parent
dc36fd416b
commit
d01ac7732f
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@ -42,3 +42,6 @@ cmake3 -DONNF_ENABLE_MODEL_TEST_CPP=ON \
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# Build and test:
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make -j "$(nproc)" install
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OMP_NUM_THREADS=20 OMP_THREAD_LIMIT=20 ctest3 -j "$(nproc)"
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# Run lit+FileCheck tests:
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make check-mlir-lit
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@ -10,7 +10,13 @@ project(onnf)
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set(CMAKE_CXX_FLAGS_DEBUG "-g")
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set(CMAKE_CXX_FLAGS_RELEASE "-O2 -DNDEBUG")
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set(ONNF_ROOT "${CMAKE_CURRENT_SOURCE_DIR}")
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set(ONNF_SRC_ROOT "${CMAKE_CURRENT_SOURCE_DIR}")
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set(ONNF_BIN_ROOT "${CMAKE_CURRENT_BINARY_DIR}")
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set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
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set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
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#TODO(eventually enable the following)
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#set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
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add_subdirectory(third_party/onnx)
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add_subdirectory(third_party/benchmark)
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@ -36,7 +42,6 @@ if(Boost_FOUND)
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endif()
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include(MLIR.cmake)
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add_subdirectory(src/builder)
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add_subdirectory(src/compiler)
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add_subdirectory(src)
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63
MLIR.cmake
63
MLIR.cmake
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@ -1,13 +1,10 @@
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# Flags to link with LLVM/MLIR libraries
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# Path to LLVM source folder.
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if(DEFINED ENV{LLVM_SRC})
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set(LLVM_SRC $ENV{LLVM_SRC})
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if(EXISTS ${LLVM_SRC})
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message(STATUS "LLVM_SRC " ${LLVM_SRC})
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else()
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message(
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FATAL_ERROR "The path specified by LLVM_SRC does not exist: "
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message(FATAL_ERROR "The path specified by LLVM_SRC does not exist: "
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${LLVM_SRC})
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endif()
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else()
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@ -20,8 +17,7 @@ if(DEFINED ENV{LLVM_BUILD})
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if(EXISTS ${LLVM_BUILD})
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message(STATUS "LLVM_BUILD " ${LLVM_BUILD})
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else()
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message(
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FATAL_ERROR "The path specified by LLVM_BUILD does not exist: "
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message(FATAL_ERROR "The path specified by LLVM_BUILD does not exist: "
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${LLVM_BUILD})
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endif()
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else()
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@ -36,9 +32,16 @@ set(LLVM_SRC_INCLUDE_PATH ${LLVM_SRC}/include)
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set(LLVM_BIN_INCLUDE_PATH ${LLVM_BUILD}/include)
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set(MLIR_SRC_INCLUDE_PATH ${LLVM_SRC}/projects/mlir/include)
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set(MLIR_BIN_INCLUDE_PATH ${LLVM_BUILD}/projects/mlir/include)
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set(MLIR_TOOLS_DIR ${LLVM_BUILD}/bin)
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set(MLIR_INCLUDE_PATHS
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${LLVM_SRC_INCLUDE_PATH};${LLVM_BIN_INCLUDE_PATH};${MLIR_SRC_INCLUDE_PATH};${MLIR_BIN_INCLUDE_PATH})
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set(ONNF_TOOLS_DIR ${ONNF_BIN_ROOT}/src/compiler/tool/onnf_opt)
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set(ONNF_LIT_TEST_SRC_DIR ${CMAKE_SOURCE_DIR}/test/mlir)
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set(ONNF_LIT_TEST_BUILD_DIR ${CMAKE_BINARY_DIR}/test/mlir)
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set(
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MLIR_INCLUDE_PATHS
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${LLVM_SRC_INCLUDE_PATH};${LLVM_BIN_INCLUDE_PATH};${MLIR_SRC_INCLUDE_PATH};${MLIR_BIN_INCLUDE_PATH}
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)
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include_directories(${MLIR_INCLUDE_PATHS})
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find_library(MLIR_LIB_ANALYSIS
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@ -112,7 +115,6 @@ set(MLIRLIBS
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${MLIR_LIB_OPT_MAIN}
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${MLIR_LIB_SUPPORT}
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${MLIR_LIB_TRANSFORM_UTILS}
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${MLIR_LIB_ANALYSIS}
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${MLIR_LIB_IR}
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${MLIR_LIB_PARSER}
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@ -123,32 +125,45 @@ set(MLIRLIBS
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${MLIR_LIB_OPT_MAIN}
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${MLIR_LIB_SUPPORT}
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${MLIR_LIB_TRANSFORM_UTILS}
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${LLVM_LIB_SUPPORT}
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Threads::Threads)
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function(whole_archive_link target)
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function(whole_archive_link target lib_dir)
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get_property(link_flags TARGET ${target} PROPERTY LINK_FLAGS)
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if("${CMAKE_SYSTEM_NAME}" STREQUAL "Darwin")
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set(link_flags "-L${LLVM_BUILD}/lib ")
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FOREACH(LIB ${ARGN})
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string(CONCAT link_flags ${link_flags} "-Wl,-force_load ${LLVM_BUILD}/lib/lib${LIB}.a ")
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ENDFOREACH(LIB)
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set(link_flags "${link_flags} -L${lib_dir} ")
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foreach(LIB ${ARGN})
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string(CONCAT link_flags ${link_flags}
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"-Wl,-force_load ${lib_dir}/lib${LIB}.a ")
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endforeach(LIB)
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elseif(MSVC)
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FOREACH(LIB ${ARGN})
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foreach(LIB ${ARGN})
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string(CONCAT link_flags ${link_flags} "/WHOLEARCHIVE:${LIB} ")
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ENDFOREACH(LIB)
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endforeach(LIB)
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else()
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set(link_flags "-L${LLVM_BUILD}/lib -Wl,--whole-archive,")
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FOREACH(LIB ${ARGN})
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set(link_flags "${link_flags} -L${lib_dir} -Wl,--whole-archive,")
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foreach(LIB ${ARGN})
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string(CONCAT link_flags ${link_flags} "-l${LIB},")
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ENDFOREACH(LIB)
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endforeach(LIB)
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string(CONCAT link_flags ${link_flags} "--no-whole-archive")
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endif()
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set_target_properties(${target} PROPERTIES LINK_FLAGS ${link_flags})
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endfunction(whole_archive_link)
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# Set up TableGen environment.
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include(${LLVM_BUILD}/lib/cmake/llvm/TableGen.cmake)
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function(whole_archive_link_mlir target)
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whole_archive_link(${target} ${LLVM_BUILD}/lib ${ARGN})
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endfunction(whole_archive_link_mlir)
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function(whole_archive_link_onnf target)
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whole_archive_link(${target} ${CMAKE_BINARY_DIR}/lib ${ARGN})
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endfunction(whole_archive_link_onnf)
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set(LLVM_CMAKE_DIR
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"${LLVM_BUILD}/lib/cmake/llvm"
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CACHE PATH "Path to LLVM cmake modules")
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list(APPEND CMAKE_MODULE_PATH "${LLVM_CMAKE_DIR}")
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include(AddLLVM)
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include(TableGen)
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function(onnf_tablegen ofn)
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tablegen(MLIR
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@ -165,7 +180,5 @@ endfunction()
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# table gen utility itself can be detected and cause re-compilation of .td file.
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add_executable(mlir-tblgen IMPORTED)
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set_property(TARGET mlir-tblgen
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PROPERTY IMPORTED_LOCATION
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${LLVM_BUILD}/bin/mlir-tblgen)
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PROPERTY IMPORTED_LOCATION ${LLVM_BUILD}/bin/mlir-tblgen)
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set(MLIR_TABLEGEN_EXE mlir-tblgen)
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@ -18,6 +18,7 @@
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#include <regex>
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#include <string>
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#include <tuple>
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#include <map>
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#include "mlir/Analysis/Verifier.h"
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#include "mlir/Dialect/StandardOps/Ops.h"
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@ -34,9 +35,10 @@
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#include "llvm/ADT/ScopedHashTable.h"
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#include "llvm/Support/raw_ostream.h"
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#include "frontend_dialect_transformer.hpp"
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#include "src/compiler/dialect/onnx/onnx_ops.hpp"
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#include "frontend_dialect_transformer.hpp"
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namespace onnf {
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namespace {
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@ -147,7 +149,14 @@ class FrontendGenImpl {
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}
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}
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void ImportInputTensor(onnx::ValueInfoProto& input) {
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/*!
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* Import an onnx input tensor type by determining and recording its type
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* in a list of input tensor mlir types.
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* @param input onnx input tensor ValueInfoProto.
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* @param arg_types list of mlir types representing types of graph input.
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*/
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void ImportInputTensorType(const onnx::ValueInfoProto& input,
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llvm::SmallVector<mlir::Type, 4>& arg_types) {
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std::vector<int64_t> dims;
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auto shape_proto = input.type().tensor_type().shape();
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auto input_tensor_legalized_name = legalize_name(input.name());
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@ -165,20 +174,28 @@ class FrontendGenImpl {
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dims.push_back(-1);
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}
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}
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if (!frontend_symbols_.ContainKey(input_tensor_legalized_name)) {
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mlir::Type elementType =
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TypeConvert(input.type().tensor_type().elem_type());
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llvm::ArrayRef<int64_t> llvmdimsAR(dims.data(), dims.size());
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auto dataType = mlir::RankedTensorType::get(llvmdimsAR, elementType);
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mlir::OperationState result(
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UnknownLoc(), "frontend.input " + input_tensor_legalized_name);
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result.addTypes(dataType);
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auto op = builder_.createOperation(result);
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auto value = op->getResult(0);
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frontend_symbols_.AddMapping(input_tensor_legalized_name, value);
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} else {
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// TODO Should not happen
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llvm::ArrayRef<int64_t> tensor_dims(dims.data(), dims.size());
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arg_types.emplace_back(
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mlir::RankedTensorType::get(tensor_dims, elementType));
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}
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/*!
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* Import a input tensor symbol by recording a new entry in frontend_symbols_
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* recording the mapping between legalized onnx tensor name and mlir::Value*
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* for further lookup in computation node importing.
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* @param input onnx input tensor ValueInfoProto.
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* @param symbol mlir input argument.
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*/
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void ImportInputTensorSymbol(
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const onnx::ValueInfoProto& input, mlir::Value* symbol) {
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auto input_tensor_legalized_name = legalize_name(input.name());
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assert(
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!frontend_symbols_.ContainKey(input_tensor_legalized_name) &&
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"Found duplicate legalized input tensor names.");
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frontend_symbols_.AddMapping(input_tensor_legalized_name, symbol);
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}
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void ImportNode(onnx::NodeProto node) {
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@ -237,59 +254,80 @@ class FrontendGenImpl {
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// TODO more info from node: attributes
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}
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void ImportOutputTensor(onnx::ValueInfoProto& output) {
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/*!
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* Import output tensor, by doing the following:
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* - Add the type of this output tensor to a list of tensor
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* types representing return types of this graph function.
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* - Add this output tensor to the list of mlir::Value*
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* to be returned by the function representing computation graph.
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* @param output onnx output tensor ValueInfoProto.
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* @param ret_types a vector of tensor types representing graph's
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* output tensor types.
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* @param ret_vals a vector of mlir Value* representing graph's
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* output tensor.
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*/
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void ImportOutputTensor(const onnx::ValueInfoProto& output,
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llvm::SmallVectorImpl<mlir::Type>& ret_types,
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llvm::SmallVectorImpl<mlir::Value*>& ret_vals) {
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auto output_tensor_legalized_name = legalize_name(output.name());
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if (frontend_symbols_.ContainKey(output_tensor_legalized_name)) {
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mlir::OperationState result(
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UnknownLoc(), "frontend.output " + output_tensor_legalized_name);
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mlir::Type elementType =
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TypeConvert(output.type().tensor_type().elem_type());
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result.addTypes(mlir::UnrankedTensorType::get(elementType));
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result.addOperands(frontend_symbols_.GetTensorByOnnxName(
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output_tensor_legalized_name));
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builder_.createOperation(result);
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} else {
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// TODO: Why not in the symbol table? something is wrong
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assert(false && "output name not found");
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}
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assert(
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frontend_symbols_.ContainKey(output_tensor_legalized_name) &&
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"Output tensor not found");
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auto tensor_val =
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frontend_symbols_.GetTensorByOnnxName(output_tensor_legalized_name);
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ret_types.emplace_back(tensor_val->getType());
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ret_vals.push_back(tensor_val);
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}
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void ImportGraph(onnx::GraphProto graph) {
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void ImportGraph(
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const onnx::GraphProto& graph, const std::string& name = "main") {
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// create a function for the graph
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// TODO:
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// * get name and type for the function.
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// * maintain a list of the defined graph
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llvm::SmallVector<mlir::Type, 4> ret_types;
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llvm::SmallVector<mlir::Type, 4> arg_types;
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auto func_type = builder_.getFunctionType(arg_types, ret_types);
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auto llvmfunction = mlir::FuncOp::create(
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UnknownLoc(), graph.name(), func_type, /* attrs = */ {});
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auto& entryBlock = *llvmfunction.addEntryBlock();
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builder_.setInsertionPointToStart(&entryBlock);
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module_.push_back(llvmfunction);
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// Import the input tensor types.
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for (const auto& input : graph.input()) {
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ImportInputTensorType(input, arg_types);
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}
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// TODO: import the initializer
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//
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auto func_type = builder_.getFunctionType(arg_types, {});
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auto main_func =
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mlir::FuncOp::create(UnknownLoc(), name, func_type, /* attrs = */ {});
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auto& entryBlock = *main_func.addEntryBlock();
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// import the input tensors
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for (auto input : graph.input()) {
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ImportInputTensor(input);
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builder_.setInsertionPointToStart(&entryBlock);
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module_.push_back(main_func);
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for (auto it : llvm::zip(graph.input(), entryBlock.getArguments())) {
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ImportInputTensorSymbol(std::get<0>(it), std::get<1>(it));
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}
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// import nodes in the graph
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auto node = graph.node();
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for (auto item : node) {
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for (const auto& item : node) {
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ImportNode(item);
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}
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// import the output tensors
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for (auto output : graph.output()) {
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ImportOutputTensor(output);
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llvm::SmallVector<mlir::Type, 4> ret_types;
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llvm::SmallVector<mlir::Value*, 4> ret_vals;
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// Import the output tensors
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for (const auto& output : graph.output()) {
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ImportOutputTensor(output, ret_types, ret_vals);
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}
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// Create a return operation to return all ONNX output tensors.
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builder_.create<mlir::ReturnOp>(UnknownLoc(), ret_vals);
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// Update main function signature to reflect types of newly imported
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// output tensors.
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func_type = builder_.getFunctionType(arg_types, ret_types);
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main_func.setType(func_type);
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}
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}; // FrontendGenImpl class
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} // namespace
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} // namespace onnf
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@ -14,12 +14,21 @@ add_library(
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pass/passes.hpp)
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# Include root src directory.
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target_include_directories(compiler PRIVATE ../..)
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target_include_directories(compiler PRIVATE ${CMAKE_SOURCE_DIR})
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target_include_directories(compiler PRIVATE ${CMAKE_BINARY_DIR})
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target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT})
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# Include third-party libraries.
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target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/isl/include)
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target_include_directories(compiler PRIVATE ${ONNF_BIN_ROOT}/third_party/isl/include)
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target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/Linq)
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target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/inja/src)
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target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/fmt/include)
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# Include tablegen generated header files.
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target_include_directories(compiler PRIVATE ${ONNF_BIN_ROOT})
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find_package(Boost 1.54.0
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COMPONENTS graph
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COMPONENTS
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graph
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program_options
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log_setup
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log
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@ -27,20 +36,14 @@ find_package(Boost 1.54.0
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filesystem
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REQUIRED)
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# target_link_libraries(compiler isl inja ${Boost_LIBRARIES})
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target_link_libraries(compiler
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${Boost_LIBRARIES}
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${MLIRLIBS} curses)
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${CMAKE_THREAD_LIBS_INIT}
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${CMAKE_DL_LIBS}
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${MLIRLIBS}
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curses)
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add_executable(onnf-opt
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tool/onnf_opt/onnf_opt.cpp)
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set(LIB_LIST MLIRAffineOps MLIRLoopOps MLIRTransformUtils MLIREDSC MLIRTransforms)
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whole_archive_link(onnf-opt ${LIB_LIST})
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target_link_libraries(onnf-opt ${Boost_LIBRARIES} ${MLIRLIBS} curses compiler)
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target_include_directories(onnf-opt PRIVATE ../..)
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target_include_directories(onnf-opt PRIVATE ${CMAKE_BINARY_DIR})
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add_subdirectory(tool)
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set(LLVM_TARGET_DEFINITIONS pass/shape_inference_interface.td)
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onnf_tablegen(shape_inference.hpp.inc -gen-op-interface-decls)
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|
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@ -21,29 +21,29 @@ class KrnlOpsDialect : public Dialect {
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KrnlOpsDialect(MLIRContext* context);
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static StringRef getDialectNamespace() { return "krnl"; }
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/// Parse a type registered to this dialect. Overriding this method is
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/// required for dialects that have custom types.
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/// Technically this is only needed to be able to round-trip to textual IR.
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mlir::Type parseType(
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llvm::StringRef tyData, mlir::Location loc) const override {
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MLIRContext* context = getContext();
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if (tyData.consume_front("loop"))
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return LoopType::get(context);
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else
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return (emitError(loc, "Unexpected type: " + tyData), Type());
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}
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||||
|
||||
/// Print a type registered to this dialect. Overriding this method is
|
||||
/// only required for dialects that have custom types.
|
||||
/// Technically this is only needed to be able to round-trip to textual IR.
|
||||
void printType(mlir::Type type, llvm::raw_ostream& os) const override {
|
||||
switch (type.getKind()) {
|
||||
case KrnlTypes::Loop:
|
||||
os << "loop";
|
||||
return;
|
||||
}
|
||||
}
|
||||
// /// Parse a type registered to this dialect. Overriding this method is
|
||||
// /// required for dialects that have custom types.
|
||||
// /// Technically this is only needed to be able to round-trip to textual IR.
|
||||
// mlir::Type parseType(
|
||||
// llvm::StringRef tyData, mlir::Location loc) const override {
|
||||
// MLIRContext* context = getContext();
|
||||
//
|
||||
// if (tyData.consume_front("loop"))
|
||||
// return LoopType::get(context);
|
||||
// else
|
||||
// return (emitError(loc, "Unexpected type: " + tyData), Type());
|
||||
// }
|
||||
//
|
||||
// /// Print a type registered to this dialect. Overriding this method is
|
||||
// /// only required for dialects that have custom types.
|
||||
// /// Technically this is only needed to be able to round-trip to textual IR.
|
||||
// void printType(mlir::Type type, llvm::raw_ostream& os) const override {
|
||||
// switch (type.getKind()) {
|
||||
// case KrnlTypes::Loop:
|
||||
// os << "loop";
|
||||
// return;
|
||||
// }
|
||||
// }
|
||||
};
|
||||
|
||||
#define GET_OP_CLASSES
|
||||
|
|
|
|||
|
|
@ -0,0 +1 @@
|
|||
add_subdirectory(onnf_opt)
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
add_executable(onnf-opt onnf_opt.cpp)
|
||||
|
||||
target_include_directories(onnf-opt PRIVATE ${ONNF_SRC_ROOT})
|
||||
target_include_directories(onnf-opt PRIVATE ${ONNF_BIN_ROOT})
|
||||
|
||||
set(LIB_LIST
|
||||
MLIRStandardOps
|
||||
MLIRAffineOps
|
||||
MLIRLoopOps
|
||||
MLIRTransformUtils
|
||||
MLIREDSC
|
||||
MLIRTransforms)
|
||||
whole_archive_link_mlir(onnf-opt ${LIB_LIST})
|
||||
|
||||
# TODO: need to investigate how to whole-archive link compiler pass to onnf-opt.
|
||||
target_link_libraries(onnf-opt compiler)
|
||||
|
|
@ -19,7 +19,6 @@
|
|||
|
||||
#include "src/compiler/dialect/krnl/krnl_ops.hpp"
|
||||
#include "src/compiler/dialect/onnx/onnx_ops.hpp"
|
||||
#include "src/compiler/helper.hpp"
|
||||
#include "src/compiler/pass/passes.hpp"
|
||||
|
||||
using namespace onnf;
|
||||
|
|
@ -49,6 +48,7 @@ int main(int argc, char** argv) {
|
|||
llvm::InitLLVM y(argc, argv);
|
||||
|
||||
mlir::registerDialect<mlir::ONNXOpsDialect>();
|
||||
mlir::registerDialect<mlir::KrnlOpsDialect>();
|
||||
|
||||
// Register any pass manager command line options.
|
||||
mlir::registerPassManagerCLOptions();
|
||||
|
|
@ -59,8 +59,10 @@ int main(int argc, char** argv) {
|
|||
// Set up the input file.
|
||||
std::string error_message;
|
||||
auto file = mlir::openInputFile(input_filename, &error_message);
|
||||
assert(file);
|
||||
|
||||
auto output = mlir::openOutputFile(output_filename, &error_message);
|
||||
assert(output);
|
||||
|
||||
return failed(mlir::MlirOptMain(output->os(), std::move(file), passPipeline,
|
||||
split_input_file, verify_diagnostics, verify_passes));
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ using namespace onnf;
|
|||
|
||||
void LoadMLIR(string inputFilename, mlir::MLIRContext& context,
|
||||
mlir::OwningModuleRef& module) {
|
||||
// Handle '.mlir' input to the DLC compiler.
|
||||
// Handle '.mlir' input to the ONNF frontend.
|
||||
// The mlir format indicates that one or more of the supported
|
||||
// representations are used in the file.
|
||||
llvm::ErrorOr<std::unique_ptr<llvm::MemoryBuffer>> fileOrErr =
|
||||
|
|
|
|||
|
|
@ -0,0 +1,4 @@
|
|||
add_subdirectory(models)
|
||||
add_subdirectory(nodes)
|
||||
|
||||
add_subdirectory(mlir)
|
||||
|
|
@ -0,0 +1,21 @@
|
|||
set(LLVM_LIT ${LLVM_SRC}/utils/lit/lit.py)
|
||||
set(LLVM_DEFAULT_EXTERNAL_LIT ${LLVM_BUILD}/bin/llvm-lit)
|
||||
|
||||
configure_lit_site_cfg(${CMAKE_CURRENT_SOURCE_DIR}/lit.site.cfg.py.in
|
||||
${CMAKE_CURRENT_BINARY_DIR}/lit.site.cfg.py
|
||||
MAIN_CONFIG
|
||||
${CMAKE_CURRENT_SOURCE_DIR}/lit.cfg.py)
|
||||
|
||||
set(ONNF_MLIR_TEST_DEPENDS onnf-opt)
|
||||
|
||||
add_lit_testsuite(check-mlir-lit
|
||||
"Running the ONNF MLIR regression tests"
|
||||
${CMAKE_CURRENT_BINARY_DIR}
|
||||
DEPENDS
|
||||
${ONNF_MLIR_TEST_DEPENDS})
|
||||
set_target_properties(check-mlir-lit PROPERTIES FOLDER "Tests")
|
||||
|
||||
add_lit_testsuites(ONNF_MLIR
|
||||
${CMAKE_CURRENT_SOURCE_DIR}
|
||||
DEPENDS
|
||||
${ONNF_MLIR_TEST_DEPS})
|
||||
|
|
@ -0,0 +1,29 @@
|
|||
|
||||
import lit.formats
|
||||
from lit.llvm import llvm_config
|
||||
from lit.llvm.subst import ToolSubst
|
||||
|
||||
# name: The name of this test suite.
|
||||
config.name = 'Open Neural Network Frontend'
|
||||
|
||||
config.test_format = lit.formats.ShTest(not llvm_config.use_lit_shell)
|
||||
|
||||
# test_source_root: The root path where tests are located.
|
||||
config.test_source_root = config.onnf_mlir_test_src_dir
|
||||
|
||||
# test_exec_root: The root path where tests should be run.
|
||||
config.test_exec_root = config.onnf_mlir_test_build_dir
|
||||
|
||||
llvm_config.use_default_substitutions()
|
||||
|
||||
# Tweak the PATH to include the tools dir.
|
||||
llvm_config.with_environment('PATH', config.llvm_tools_dir, append_path=True)
|
||||
|
||||
tool_dirs = [
|
||||
config.onnf_mlir_tools_dir, config.mlir_tools_dir, config.llvm_tools_dir
|
||||
]
|
||||
tool_names = [
|
||||
'onnf-opt', 'mlir-opt', 'mlir-translate'
|
||||
]
|
||||
tools = [ToolSubst(s, unresolved='ignore') for s in tool_names]
|
||||
llvm_config.add_tool_substitutions(tools, tool_dirs)
|
||||
|
|
@ -0,0 +1,16 @@
|
|||
|
||||
import lit.llvm
|
||||
|
||||
config.llvm_tools_dir = "@MLIR_TOOLS_DIR@"
|
||||
config.mlir_obj_root = "@MLIR_BUILD_DIR@"
|
||||
config.mlir_tools_dir = "@MLIR_TOOLS_DIR@"
|
||||
config.suffixes = ['.mlir']
|
||||
|
||||
config.onnf_mlir_tools_dir = "@ONNF_TOOLS_DIR@"
|
||||
config.onnf_mlir_test_src_dir = "@ONNF_LIT_TEST_SRC_DIR@"
|
||||
config.onnf_mlir_test_build_dir = "@ONNF_LIT_TEST_BUILD_DIR@"
|
||||
|
||||
lit.llvm.initialize(lit_config, config)
|
||||
|
||||
# Let the main config do the real work.
|
||||
lit_config.load_config(config, "@ONNF_LIT_TEST_SRC_DIR@/lit.cfg.py")
|
||||
|
|
@ -0,0 +1,14 @@
|
|||
// RUN: onnf-opt --canonicalize %s -split-input-file | FileCheck %s
|
||||
|
||||
//CHECK: module {
|
||||
module {
|
||||
func @test_sigmoid() {
|
||||
%0 = "frontend.input t1"() : () -> tensor<10x10xf32>
|
||||
%1 = "frontend.input t2"() : () -> tensor<10x10xf32>
|
||||
%2 = "frontend.input t3"() : () -> tensor<10x10xf32>
|
||||
// CHECK: %{{[0-9]+}} = "onnx.full_gemm"(%{{.*}}, %{{.*}}, %{{.*}}) : (tensor<10x10xf32>, tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
|
||||
%3 = "onnx.matmul"(%0, %1) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
|
||||
%4 = "onnx.add"(%3, %2) : (tensor<10x10xf32>, tensor<10x10xf32>) -> tensor<10x10xf32>
|
||||
%5 = "frontend.output t4"(%4) : (tensor<10x10xf32>) -> tensor<10x10xf32>
|
||||
}
|
||||
}
|
||||
Loading…
Reference in New Issue