[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

.buildbot/p9.sh

@@ -42,3 +42,6 @@ cmake3 -DONNF_ENABLE_MODEL_TEST_CPP=ON         \
 # Build and test:
 make -j "$(nproc)" install
 OMP_NUM_THREADS=20 OMP_THREAD_LIMIT=20 ctest3 -j "$(nproc)"
+
+# Run lit+FileCheck tests:
+make check-mlir-lit

CMakeLists.txt

@@ -10,7 +10,13 @@ project(onnf)
 
 set(CMAKE_CXX_FLAGS_DEBUG "-g")
 set(CMAKE_CXX_FLAGS_RELEASE "-O2 -DNDEBUG")
-set(ONNF_ROOT "${CMAKE_CURRENT_SOURCE_DIR}")
+
+set(ONNF_SRC_ROOT "${CMAKE_CURRENT_SOURCE_DIR}")
+set(ONNF_BIN_ROOT "${CMAKE_CURRENT_BINARY_DIR}")
+set(CMAKE_ARCHIVE_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+set(CMAKE_LIBRARY_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/lib)
+#TODO(eventually enable the following)
+#set(CMAKE_RUNTIME_OUTPUT_DIRECTORY ${CMAKE_BINARY_DIR}/bin)
 
 add_subdirectory(third_party/onnx)
 add_subdirectory(third_party/benchmark)
@@ -36,7 +42,6 @@ if(Boost_FOUND)
 endif()
 
 include(MLIR.cmake)
-
 add_subdirectory(src/builder)
 add_subdirectory(src/compiler)
 add_subdirectory(src)

MLIR.cmake

@@ -1,14 +1,11 @@
-# Flags to link with LLVM/MLIR libraries
-
 # Path to LLVM source folder.
 if(DEFINED ENV{LLVM_SRC})
   set(LLVM_SRC $ENV{LLVM_SRC})
   if(EXISTS ${LLVM_SRC})
     message(STATUS "LLVM_SRC " ${LLVM_SRC})
   else()
-    message(
+    message(FATAL_ERROR "The path specified by LLVM_SRC does not exist: "
-      FATAL_ERROR "The path specified by LLVM_SRC does not exist: "
+                        ${LLVM_SRC})
-                  ${LLVM_SRC})
   endif()
 else()
   message(FATAL_ERROR "env variable LLVM_SRC not set")
@@ -20,9 +17,8 @@ if(DEFINED ENV{LLVM_BUILD})
   if(EXISTS ${LLVM_BUILD})
     message(STATUS "LLVM_BUILD " ${LLVM_BUILD})
   else()
-    message(
+    message(FATAL_ERROR "The path specified by LLVM_BUILD does not exist: "
-      FATAL_ERROR "The path specified by LLVM_BUILD does not exist: "
+                        ${LLVM_BUILD})
-                  ${LLVM_BUILD})
   endif()
 else()
   message(FATAL_ERROR "env variable LLVM_BUILD not set")
@@ -36,9 +32,16 @@ set(LLVM_SRC_INCLUDE_PATH ${LLVM_SRC}/include)
 set(LLVM_BIN_INCLUDE_PATH ${LLVM_BUILD}/include)
 set(MLIR_SRC_INCLUDE_PATH ${LLVM_SRC}/projects/mlir/include)
 set(MLIR_BIN_INCLUDE_PATH ${LLVM_BUILD}/projects/mlir/include)
+set(MLIR_TOOLS_DIR ${LLVM_BUILD}/bin)
 
-set(MLIR_INCLUDE_PATHS
+set(ONNF_TOOLS_DIR ${ONNF_BIN_ROOT}/src/compiler/tool/onnf_opt)
-    ${LLVM_SRC_INCLUDE_PATH};${LLVM_BIN_INCLUDE_PATH};${MLIR_SRC_INCLUDE_PATH};${MLIR_BIN_INCLUDE_PATH})
+set(ONNF_LIT_TEST_SRC_DIR ${CMAKE_SOURCE_DIR}/test/mlir)
+set(ONNF_LIT_TEST_BUILD_DIR ${CMAKE_BINARY_DIR}/test/mlir)
+
+set(
+  MLIR_INCLUDE_PATHS
+  ${LLVM_SRC_INCLUDE_PATH};${LLVM_BIN_INCLUDE_PATH};${MLIR_SRC_INCLUDE_PATH};${MLIR_BIN_INCLUDE_PATH}
+  )
 include_directories(${MLIR_INCLUDE_PATHS})
 
 find_library(MLIR_LIB_ANALYSIS
@@ -112,7 +115,6 @@ set(MLIRLIBS
     ${MLIR_LIB_OPT_MAIN}
     ${MLIR_LIB_SUPPORT}
     ${MLIR_LIB_TRANSFORM_UTILS}
-
     ${MLIR_LIB_ANALYSIS}
     ${MLIR_LIB_IR}
     ${MLIR_LIB_PARSER}
@@ -123,32 +125,45 @@ set(MLIRLIBS
     ${MLIR_LIB_OPT_MAIN}
     ${MLIR_LIB_SUPPORT}
     ${MLIR_LIB_TRANSFORM_UTILS}
-
     ${LLVM_LIB_SUPPORT}
     Threads::Threads)
 
-function(whole_archive_link target)
+function(whole_archive_link target lib_dir)
+  get_property(link_flags TARGET ${target} PROPERTY LINK_FLAGS)
   if("${CMAKE_SYSTEM_NAME}" STREQUAL "Darwin")
-    set(link_flags "-L${LLVM_BUILD}/lib ")
+    set(link_flags "${link_flags} -L${lib_dir} ")
-    FOREACH(LIB ${ARGN})
+    foreach(LIB ${ARGN})
-      string(CONCAT link_flags ${link_flags} "-Wl,-force_load ${LLVM_BUILD}/lib/lib${LIB}.a ")
+      string(CONCAT link_flags ${link_flags}
-    ENDFOREACH(LIB)
+                    "-Wl,-force_load ${lib_dir}/lib${LIB}.a ")
+    endforeach(LIB)
   elseif(MSVC)
-    FOREACH(LIB ${ARGN})
+    foreach(LIB ${ARGN})
       string(CONCAT link_flags ${link_flags} "/WHOLEARCHIVE:${LIB} ")
-    ENDFOREACH(LIB)
+    endforeach(LIB)
   else()
-    set(link_flags "-L${LLVM_BUILD}/lib -Wl,--whole-archive,")
+    set(link_flags "${link_flags} -L${lib_dir} -Wl,--whole-archive,")
-    FOREACH(LIB ${ARGN})
+    foreach(LIB ${ARGN})
       string(CONCAT link_flags ${link_flags} "-l${LIB},")
-    ENDFOREACH(LIB)
+    endforeach(LIB)
     string(CONCAT link_flags ${link_flags} "--no-whole-archive")
   endif()
   set_target_properties(${target} PROPERTIES LINK_FLAGS ${link_flags})
 endfunction(whole_archive_link)
 
-# Set up TableGen environment.
+function(whole_archive_link_mlir target)
-include(${LLVM_BUILD}/lib/cmake/llvm/TableGen.cmake)
+  whole_archive_link(${target} ${LLVM_BUILD}/lib ${ARGN})
+endfunction(whole_archive_link_mlir)
+
+function(whole_archive_link_onnf target)
+  whole_archive_link(${target} ${CMAKE_BINARY_DIR}/lib ${ARGN})
+endfunction(whole_archive_link_onnf)
+
+set(LLVM_CMAKE_DIR
+    "${LLVM_BUILD}/lib/cmake/llvm"
+    CACHE PATH "Path to LLVM cmake modules")
+list(APPEND CMAKE_MODULE_PATH "${LLVM_CMAKE_DIR}")
+include(AddLLVM)
+include(TableGen)
 
 function(onnf_tablegen ofn)
   tablegen(MLIR
@@ -165,7 +180,5 @@ endfunction()
 # table gen utility itself can be detected and cause re-compilation of .td file.
 add_executable(mlir-tblgen IMPORTED)
 set_property(TARGET mlir-tblgen
-             PROPERTY IMPORTED_LOCATION
+             PROPERTY IMPORTED_LOCATION ${LLVM_BUILD}/bin/mlir-tblgen)
-                      ${LLVM_BUILD}/bin/mlir-tblgen)
 set(MLIR_TABLEGEN_EXE mlir-tblgen)
-

src/builder/frontend_dialect_transformer.cpp

@@ -18,6 +18,7 @@
 #include <regex>
 #include <string>
 #include <tuple>
+#include <map>
 
 #include "mlir/Analysis/Verifier.h"
 #include "mlir/Dialect/StandardOps/Ops.h"
@@ -34,9 +35,10 @@
 #include "llvm/ADT/ScopedHashTable.h"
 #include "llvm/Support/raw_ostream.h"
 
-#include "frontend_dialect_transformer.hpp"
 #include "src/compiler/dialect/onnx/onnx_ops.hpp"
 
+#include "frontend_dialect_transformer.hpp"
+
 namespace onnf {
 namespace {
 
@@ -147,7 +149,14 @@ class FrontendGenImpl {
     }
   }
 
-  void ImportInputTensor(onnx::ValueInfoProto& input) {
+  /*!
+   * Import an onnx input tensor type by determining and recording its type
+   * in a list of input tensor mlir types.
+   * @param input onnx input tensor ValueInfoProto.
+   * @param arg_types list of mlir types representing types of graph input.
+   */
+  void ImportInputTensorType(const onnx::ValueInfoProto& input,
+      llvm::SmallVector<mlir::Type, 4>& arg_types) {
     std::vector<int64_t> dims;
     auto shape_proto = input.type().tensor_type().shape();
     auto input_tensor_legalized_name = legalize_name(input.name());
@@ -165,20 +174,28 @@ class FrontendGenImpl {
         dims.push_back(-1);
       }
     }
-    if (!frontend_symbols_.ContainKey(input_tensor_legalized_name)) {
+
-      mlir::Type elementType =
+    mlir::Type elementType =
-          TypeConvert(input.type().tensor_type().elem_type());
+        TypeConvert(input.type().tensor_type().elem_type());
-      llvm::ArrayRef<int64_t> llvmdimsAR(dims.data(), dims.size());
+    llvm::ArrayRef<int64_t> tensor_dims(dims.data(), dims.size());
-      auto dataType = mlir::RankedTensorType::get(llvmdimsAR, elementType);
+    arg_types.emplace_back(
-      mlir::OperationState result(
+        mlir::RankedTensorType::get(tensor_dims, elementType));
-          UnknownLoc(), "frontend.input " + input_tensor_legalized_name);
+  }
-      result.addTypes(dataType);
+
-      auto op = builder_.createOperation(result);
+  /*!
-      auto value = op->getResult(0);
+   * Import a input tensor symbol by recording a new entry in frontend_symbols_
-      frontend_symbols_.AddMapping(input_tensor_legalized_name, value);
+   * recording the mapping between legalized onnx tensor name and mlir::Value*
-    } else {
+   * for further lookup in computation node importing.
-      // TODO  Should not happen
+   * @param input onnx input tensor ValueInfoProto.
-    }
+   * @param symbol mlir input argument.
+   */
+  void ImportInputTensorSymbol(
+      const onnx::ValueInfoProto& input, mlir::Value* symbol) {
+    auto input_tensor_legalized_name = legalize_name(input.name());
+    assert(
+        !frontend_symbols_.ContainKey(input_tensor_legalized_name) &&
+        "Found duplicate legalized input tensor names.");
+    frontend_symbols_.AddMapping(input_tensor_legalized_name, symbol);
   }
 
   void ImportNode(onnx::NodeProto node) {
@@ -237,59 +254,80 @@ class FrontendGenImpl {
     // TODO more info from node: attributes
   }
 
-  void ImportOutputTensor(onnx::ValueInfoProto& output) {
+  /*!
+   * Import output tensor, by doing the following:
+   * - Add the type of this output tensor to a list of tensor
+   *   types representing return types of this graph function.
+   * - Add this output tensor to the list of mlir::Value*
+   *   to be returned by the function representing computation graph.
+   * @param output onnx output tensor ValueInfoProto.
+   * @param ret_types a vector of tensor types representing graph's
+   *   output tensor types.
+   * @param ret_vals a vector of mlir Value* representing graph's
+   *   output tensor.
+   */
+  void ImportOutputTensor(const onnx::ValueInfoProto& output,
+      llvm::SmallVectorImpl<mlir::Type>& ret_types,
+      llvm::SmallVectorImpl<mlir::Value*>& ret_vals) {
     auto output_tensor_legalized_name = legalize_name(output.name());
-    if (frontend_symbols_.ContainKey(output_tensor_legalized_name)) {
+    assert(
-      mlir::OperationState result(
+        frontend_symbols_.ContainKey(output_tensor_legalized_name) &&
-	  UnknownLoc(), "frontend.output " + output_tensor_legalized_name);
+        "Output tensor not found");
-      mlir::Type elementType =
+
-          TypeConvert(output.type().tensor_type().elem_type());
+    auto tensor_val =
-      result.addTypes(mlir::UnrankedTensorType::get(elementType));
+        frontend_symbols_.GetTensorByOnnxName(output_tensor_legalized_name);
-      result.addOperands(frontend_symbols_.GetTensorByOnnxName(
+    ret_types.emplace_back(tensor_val->getType());
-	  output_tensor_legalized_name));
+    ret_vals.push_back(tensor_val);
-      builder_.createOperation(result);
-    } else {
-      // TODO: Why not in the symbol table? something is wrong
-      assert(false && "output name not found");
-    }
   }
 
-  void ImportGraph(onnx::GraphProto graph) {
+  void ImportGraph(
+      const onnx::GraphProto& graph, const std::string& name = "main") {
     // create a function for the graph
     // TODO:
     //  * get name and type for the function.
     //  * maintain a list of the defined graph
-    llvm::SmallVector<mlir::Type, 4> ret_types;
     llvm::SmallVector<mlir::Type, 4> arg_types;
-    auto func_type = builder_.getFunctionType(arg_types, ret_types);
+
-    auto llvmfunction = mlir::FuncOp::create(
+    // Import the input tensor types.
-        UnknownLoc(), graph.name(), func_type, /* attrs = */ {});
+    for (const auto& input : graph.input()) {
-    auto& entryBlock = *llvmfunction.addEntryBlock();
+      ImportInputTensorType(input, arg_types);
-    builder_.setInsertionPointToStart(&entryBlock);
+    }
-    module_.push_back(llvmfunction);
 
     // TODO: import the initializer
-    //
+    auto func_type = builder_.getFunctionType(arg_types, {});
+    auto main_func =
+        mlir::FuncOp::create(UnknownLoc(), name, func_type, /* attrs = */ {});
+    auto& entryBlock = *main_func.addEntryBlock();
 
-    // import the input tensors
+    builder_.setInsertionPointToStart(&entryBlock);
-    for (auto input : graph.input()) {
+    module_.push_back(main_func);
-      ImportInputTensor(input);
+
+    for (auto it : llvm::zip(graph.input(), entryBlock.getArguments())) {
+      ImportInputTensorSymbol(std::get<0>(it), std::get<1>(it));
     }
 
     // import nodes in the graph
     auto node = graph.node();
-    for (auto item : node) {
+    for (const auto& item : node) {
       ImportNode(item);
     }
 
-    // import the output tensors
+    llvm::SmallVector<mlir::Type, 4> ret_types;
-    for (auto output : graph.output()) {
+    llvm::SmallVector<mlir::Value*, 4> ret_vals;
-      ImportOutputTensor(output);
+    // Import the output tensors
+    for (const auto& output : graph.output()) {
+      ImportOutputTensor(output, ret_types, ret_vals);
     }
+
+    // Create a return operation to return all ONNX output tensors.
+    builder_.create<mlir::ReturnOp>(UnknownLoc(), ret_vals);
+    // Update main function signature to reflect types of newly imported
+    // output tensors.
+    func_type = builder_.getFunctionType(arg_types, ret_types);
+    main_func.setType(func_type);
   }
 
 };  // FrontendGenImpl class
-
 }  // namespace
 }  // namespace onnf
 

src/compiler/CMakeLists.txt

@@ -14,12 +14,21 @@ add_library(
         pass/passes.hpp)
 
 # Include root src directory.
-target_include_directories(compiler PRIVATE ../..)
+target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT})
-target_include_directories(compiler PRIVATE ${CMAKE_SOURCE_DIR})
+
-target_include_directories(compiler PRIVATE ${CMAKE_BINARY_DIR})
+# Include third-party libraries.
+target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/isl/include)
+target_include_directories(compiler PRIVATE ${ONNF_BIN_ROOT}/third_party/isl/include)
+target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/Linq)
+target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/inja/src)
+target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT}/third_party/fmt/include)
+
+# Include tablegen generated header files.
+target_include_directories(compiler PRIVATE ${ONNF_BIN_ROOT})
 
 find_package(Boost 1.54.0
-        COMPONENTS graph
+        COMPONENTS
+        graph
         program_options
         log_setup
         log
@@ -27,20 +36,14 @@ find_package(Boost 1.54.0
         filesystem
         REQUIRED)
 
-# target_link_libraries(compiler isl inja ${Boost_LIBRARIES})
 target_link_libraries(compiler
         ${Boost_LIBRARIES}
-        ${MLIRLIBS} curses)
+        ${CMAKE_THREAD_LIBS_INIT}
+        ${CMAKE_DL_LIBS}
+        ${MLIRLIBS}
+        curses)
 
-add_executable(onnf-opt
+add_subdirectory(tool)
-               tool/onnf_opt/onnf_opt.cpp)
-
-set(LIB_LIST MLIRAffineOps MLIRLoopOps MLIRTransformUtils MLIREDSC MLIRTransforms)
-whole_archive_link(onnf-opt ${LIB_LIST})
-
-target_link_libraries(onnf-opt ${Boost_LIBRARIES} ${MLIRLIBS} curses compiler)
-target_include_directories(onnf-opt PRIVATE ../..)
-target_include_directories(onnf-opt PRIVATE ${CMAKE_BINARY_DIR})
 
 set(LLVM_TARGET_DEFINITIONS pass/shape_inference_interface.td)
 onnf_tablegen(shape_inference.hpp.inc -gen-op-interface-decls)

src/compiler/dialect/krnl/krnl_ops.hpp

@@ -21,29 +21,29 @@ class KrnlOpsDialect : public Dialect {
   KrnlOpsDialect(MLIRContext* context);
   static StringRef getDialectNamespace() { return "krnl"; }
 
-  /// Parse a type registered to this dialect. Overriding this method is
+//  /// Parse a type registered to this dialect. Overriding this method is
-  /// required for dialects that have custom types.
+//  /// required for dialects that have custom types.
-  /// Technically this is only needed to be able to round-trip to textual IR.
+//  /// Technically this is only needed to be able to round-trip to textual IR.
-  mlir::Type parseType(
+//  mlir::Type parseType(
-      llvm::StringRef tyData, mlir::Location loc) const override {
+//      llvm::StringRef tyData, mlir::Location loc) const override {
-    MLIRContext* context = getContext();
+//    MLIRContext* context = getContext();
-
+//
-    if (tyData.consume_front("loop"))
+//    if (tyData.consume_front("loop"))
-      return LoopType::get(context);
+//      return LoopType::get(context);
-    else
+//    else
-      return (emitError(loc, "Unexpected type: " + tyData), Type());
+//      return (emitError(loc, "Unexpected type: " + tyData), Type());
-  }
+//  }
-
+//
-  /// Print a type registered to this dialect. Overriding this method is
+//  /// Print a type registered to this dialect. Overriding this method is
-  /// only required for dialects that have custom types.
+//  /// only required for dialects that have custom types.
-  /// Technically this is only needed to be able to round-trip to textual IR.
+//  /// 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 {
+//  void printType(mlir::Type type, llvm::raw_ostream& os) const override {
-    switch (type.getKind()) {
+//    switch (type.getKind()) {
-      case KrnlTypes::Loop:
+//      case KrnlTypes::Loop:
-        os << "loop";
+//        os << "loop";
-        return;
+//        return;
-    }
+//    }
-  }
+//  }
 };
 
 #define GET_OP_CLASSES

src/compiler/tool/CMakeLists.txt

@@ -0,0 +1 @@
+add_subdirectory(onnf_opt)

src/compiler/tool/onnf_opt/CMakeLists.txt

@@ -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)

src/compiler/tool/onnf_opt/onnf_opt.cpp

@@ -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));

src/main.cpp

@@ -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 =

test/CMakeLists.txt

@@ -0,0 +1,4 @@
+add_subdirectory(models)
+add_subdirectory(nodes)
+
+add_subdirectory(mlir)

test/mlir/CMakeLists.txt

@@ -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})

test/mlir/lit.cfg.py

@@ -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)

test/mlir/lit.site.cfg.py.in

@@ -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")

test/mlir/onnx/onnx_canonicalization.mlir

@@ -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>
+ }
+}