[circle-mlir] Apply ONNX-MLIR upgrade

circle-mlir/circle-mlir/lib/dialect/include/circle-mlir/dialect/CircleDialect.h

@@ -20,6 +20,7 @@
 #ifndef __CIRCLE_MLIR_DIALECT_CIRCLE_DIALECT_H__
 #define __CIRCLE_MLIR_DIALECT_CIRCLE_DIALECT_H__
 
+#include <mlir/Bytecode/BytecodeOpInterface.h>           // from @llvm-project
 #include <mlir/Dialect/Traits.h>                         // from @llvm-project
 #include <mlir/IR/Dialect.h>                             // from @llvm-project
 #include <mlir/IR/DialectImplementation.h>               // from @llvm-project
@@ -46,6 +47,7 @@ class ControlType : public Type::TypeBase<ControlType, Type, TypeStorage>
 {
 public:
   using Base::Base;
+  static constexpr StringLiteral name = "cir.control";
 };
 
 #include "mlir/CircleOpInterface.h.inc"

circle-mlir/circle-mlir/lib/dialect/mlir/CircleOps.td

@@ -20,7 +20,6 @@
 #ifndef CIRCLE_OPS
 #define CIRCLE_OPS
 
-include "mlir/IR/FunctionInterfaces.td"
 include "mlir/IR/OpBase.td"
 include "mlir/Interfaces/InferTypeOpInterface.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"

circle-mlir/circle-mlir/lib/dialect/src/NameUtils.cpp

@@ -46,7 +46,7 @@ std::string GetNameFromLoc(Location loc)
       // in functions where the op's name is first.
       auto name = name_loc.getName().strref().split('@').first;
       // Skip if the name is for op type.
-      if (!name.endswith(":"))
+      if (!name.ends_with(":"))
       {
         loc_names.push_back(name);
         if (!name.empty())

circle-mlir/circle-mlir/lib/import/src/CircleImport.cpp

@@ -39,8 +39,7 @@ inline constexpr unsigned int flatbuffer_size_max = 2147483648;
 #include <llvm/Support/FormatVariadic.h>
 #include <mlir/IR/Matchers.h> // m_Constant
 #include <mlir/Dialect/Func/IR/FuncOps.h>
-#include <mlir/Dialect/Quant/QuantOps.h>
-#include <mlir/Dialect/Quant/QuantTypes.h>
+#include <mlir/Dialect/Quant/IR/QuantTypes.h>
 
 #include <circle_schema/schema_generated.h>
 
@@ -226,8 +225,8 @@ template <typename T> llvm::SmallVector<mlir::APInt> ReadAsHostEndian(llvm::Arra
   const char *data_ptr = reinterpret_cast<const char *>(bytes.data());
   for (size_t i = 0; i < elem_count; i++)
   {
-    T val = llvm::support::endian::readNext<T, llvm::support::endianness::native,
-                                            llvm::support::unaligned>(data_ptr);
+    T val = llvm::support::endian::readNext<T, llvm::endianness::native, llvm::support::unaligned>(
+      data_ptr);
     ret.push_back(mlir::APInt(sizeof(T) * 8, val));
   }
   return ret;
@@ -254,9 +253,8 @@ std::optional<mlir::ElementsAttr> ConvertFloatBuffer(mlir::RankedTensorType shap
 
       for (int i = 0; i < elem_count; i++)
       {
-        uint32_t bit_repr =
-          llvm::support::endian::readNext<uint32_t, llvm::support::endianness::native,
-                                          llvm::support::unaligned>(data);
+        uint32_t bit_repr = llvm::support::endian::readNext<uint32_t, llvm::endianness::native,
+                                                            llvm::support::unaligned>(data);
         values.push_back(absl::bit_cast<float>(bit_repr));
       }
       auto num = shaped_type.getNumElements();

circle-mlir/circle-mlir/lib/pass/src/RewriteCirclePass.cpp

@@ -112,7 +112,7 @@ void RewriteCirclePass::applyActivationFusion()
 
   // TODO add more patterns
 
-  (void)applyPatternsAndFoldGreedily(func, std::move(patterns));
+  (void)applyPatternsGreedily(func, std::move(patterns));
 }
 
 std::unique_ptr<mlir::Pass> createRewriteCirclePass(void)

circle-mlir/circle-mlir/lib/pass/src/opt/ConvertMirrorPadPad32.h

@@ -57,7 +57,7 @@ struct ConvertMirrorPadPad32 : public OpRewritePattern<MirrorPadOp>
     auto intattr = DenseIntElementsAttr::get(si32stype, values);
     mlir::Value shape32 = rewriter.create<ConstOp>(opLoc, intattr);
 
-    auto pad_mutable = mirrorpad_op.getPadMutable();
+    auto &pad_mutable = mirrorpad_op.getPadMutable();
     pad_mutable.assign(shape32);
 
     return mlir::success();

circle-mlir/circle-mlir/lib/pass/src/opt/ConvertReshapeShape32.h

@@ -59,7 +59,7 @@ struct ConvertReshapeShape32 : public OpRewritePattern<ReshapeOp>
     mlir::Value shape32 =
       rewriter.create<ConstOp>(opLoc, DenseIntElementsAttr::get(si32stype, values));
 
-    auto shape_mutable = reshape_op.getShapeMutable();
+    auto &shape_mutable = reshape_op.getShapeMutable();
     shape_mutable.assign(shape32);
 
     return mlir::success();

circle-mlir/circle-mlir/lib/pass/src/opt/ConvertResizeNearestSize32.h

@@ -74,7 +74,7 @@ struct ConvertResizeNearestSize32 : public OpRewritePattern<ResizeNearestNeighbo
     mlir::Value size32 =
       rewriter.create<ConstOp>(opLoc, DenseIntElementsAttr::get(si32stype, values));
 
-    auto resize_mutable = resize_op.getSizeMutable();
+    auto &resize_mutable = resize_op.getSizeMutable();
     resize_mutable.assign(size32);
 
     return mlir::success();

circle-mlir/circle-mlir/lib/tools/converter-gen/converter_gen.cc

@@ -64,8 +64,8 @@ llvm::cl::opt<ActionType> action(
 
 // Returns the associated option name for the given op definition.
 static inline std::string GetOperatorOptionName(const Record &def) {
-  assert(def.getName().startswith("CIR_") && "unexpected op prefix");
-  assert(def.getName().endswith("Op") && "unexpected op suffix");
+  assert(def.getName().starts_with("CIR_") && "unexpected op prefix");
+  assert(def.getName().ends_with("Op") && "unexpected op suffix");
 
   auto *custom_option = dyn_cast<StringInit>(def.getValueInit("customOption"));
   std::ostringstream oss;
@@ -78,8 +78,8 @@ static inline std::string GetOperatorOptionName(const Record &def) {
 
 // Returns the builder function name for the given op definition.
 static inline std::string GetOperatorBuilderName(StringRef op_name) {
-  assert(op_name.startswith("CIR_") && "unexpected op prefix");
-  assert(op_name.endswith("Op") && "unexpected op suffix");
+  assert(op_name.starts_with("CIR_") && "unexpected op prefix");
+  assert(op_name.ends_with("Op") && "unexpected op suffix");
 
   // E.g., AddOp -> CreateAddOperator
   std::ostringstream oss;
@@ -92,7 +92,7 @@ static inline bool IsLstmOp(const StringRef op_name) {
 }
 
 static void EmitOptionBuilders(const RecordKeeper &record_keeper,
-                               const std::vector<Record *> &defs,
+                               const std::vector<const Record *> &defs,
                                raw_ostream *ostream) {
   raw_ostream &os = *ostream;
 
@@ -117,7 +117,7 @@ static void EmitOptionBuilders(const RecordKeeper &record_keeper,
     mlir::tblgen::Operator op(*def);
     for (unsigned i = 0, e = arg_values->getNumArgs(); i != e; ++i) {
       auto arg = arg_values->getArg(i);
-      DefInit *arg_def = dyn_cast<DefInit>(arg);
+      const auto *arg_def = dyn_cast<DefInit>(arg);
       if (!arg_def) continue;
       if (arg_def->getDef()->isSubClassOf(attr_type)) {
         // This binds the name of the attribute in the TD file with the name
@@ -175,7 +175,7 @@ static void EmitOptionBuilders(const RecordKeeper &record_keeper,
 // arguments that depend on op definitions should be auto-generated and then
 // operator should be built by the caller because it does not require
 // auto-generation.
-static void EmitOperatorBuilders(const std::vector<Record *> &defs,
+static void EmitOperatorBuilders(const std::vector<const Record *> &defs,
                                  raw_ostream *ostream) {
   raw_ostream &os = *ostream;
 
@@ -240,7 +240,7 @@ static inline std::string GetOperatorName(const Record &def) {
 //
 // TODO(hinsu): Consider converting this to a static constant associative
 // container instead of a series of if conditions, if required.
-static void EmitGetBuiltinOpCode(const std::vector<Record *> &defs,
+static void EmitGetBuiltinOpCode(const std::vector<const Record *> &defs,
                                  raw_ostream *ostream) {
   raw_ostream &os = *ostream;
 
@@ -279,7 +279,7 @@ static void EmitGetBuiltinOpCode(const std::vector<Record *> &defs,
 //   return {0, 0};
 // }
 static void EmitOperandNumbers(const RecordKeeper &record_keeper,
-                               const std::vector<Record *> &defs,
+                               const std::vector<const Record *> &defs,
                                raw_ostream *ostream) {
   raw_ostream &os = *ostream;
   const auto attr_type = record_keeper.getClass("Attr");
@@ -324,7 +324,7 @@ static void EmitOperandNumbers(const RecordKeeper &record_keeper,
 //       const std::vector<int32_t>& results,
 //       const std::vector<int32_t>& intermediates,
 //       flatbuffers::FlatBufferBuilder *fbb);
-static void EmitBuildOperator(const std::vector<Record *> &defs,
+static void EmitBuildOperator(const std::vector<const Record *> &defs,
                               raw_ostream *ostream) {
   raw_ostream &os = *ostream;
 
@@ -360,7 +360,7 @@ static void EmitBuildOperator(const std::vector<Record *> &defs,
 //     mlir::Builder builder,
 //     llvm::SmallVectorImpl<mlir::NamedAttribute> &attributes);
 static void EmitBuiltinOptionsToAttributes(const RecordKeeper &record_keeper,
-                                           const std::vector<Record *> &defs,
+                                           const std::vector<const Record *> &defs,
                                            raw_ostream *ostream) {
   raw_ostream &os = *ostream;
 
@@ -385,7 +385,7 @@ static void EmitBuiltinOptionsToAttributes(const RecordKeeper &record_keeper,
     auto *arg_values = def->getValueAsDag("arguments");
     for (unsigned i = 0, e = arg_values->getNumArgs(); i != e; ++i) {
       auto arg = arg_values->getArg(i);
-      DefInit *arg_def = dyn_cast<DefInit>(arg);
+      const auto *arg_def = dyn_cast<DefInit>(arg);
       if (!arg_def) continue;
       if (arg_def->getDef()->isSubClassOf(attr_type)) {
         StringRef arg_name = arg_values->getArgNameStr(i);
@@ -411,11 +411,11 @@ static void EmitBuiltinOptionsToAttributes(const RecordKeeper &record_keeper,
 // The function below has a non-constant reference as that is required by LLVM's
 // TableGenMain.
 // NOLINTNEXTLINE
-static bool OperatorWritersMain(raw_ostream &os, RecordKeeper &records) {
+static bool OperatorWritersMain(raw_ostream &os, const RecordKeeper &records) {
   emitSourceFileHeader("MLIR Circle FlatBuffer Builders", os);
 
   // Retrieve all the definitions derived from CIR_Op and sort by record name.
-  std::vector<Record *> defs = records.getAllDerivedDefinitions("CIR_Op");
+  std::vector<const Record *> defs = records.getAllDerivedDefinitions("CIR_Op");
   llvm::sort(defs, LessRecord());
 
   for (const auto *def : defs) {
@@ -424,10 +424,10 @@ static bool OperatorWritersMain(raw_ostream &os, RecordKeeper &records) {
     // The generated Circle op C++ class should be circle::<OpName>Op.
     // The generated operator's options should be circle::<OpName>Options.
     // The option builder should be Create<OpName>Options.
-    if (!def->getName().startswith("CIR_"))
+    if (!def->getName().starts_with("CIR_"))
       PrintFatalError(def->getLoc(),
                       "unexpected op name format: 'CIR_' prefix missing");
-    if (!def->getName().endswith("Op"))
+    if (!def->getName().ends_with("Op"))
       PrintFatalError(def->getLoc(),
                       "unexpected op name format: 'Op' suffix missing");
   }
@@ -448,7 +448,7 @@ static bool OperatorWritersMain(raw_ostream &os, RecordKeeper &records) {
 }
 
 static void GenOperandResultVerifier(raw_ostream &os,
-                                     llvm::ArrayRef<llvm::Init *> values,
+                                     llvm::ArrayRef<const llvm::Init *> values,
                                      StringRef valueKind) {
   mlir::tblgen::FmtContext fctx;
 
@@ -496,11 +496,12 @@ static void GenOperandResultVerifier(raw_ostream &os,
 }
 
 // NOLINTNEXTLINE
-static bool RuntimeVerifierWriterMain(raw_ostream &os, RecordKeeper &records) {
+static bool RuntimeVerifierWriterMain(raw_ostream &os,
+                                      const RecordKeeper &records) {
   emitSourceFileHeader("MLIR Circle Runtime Verifiers", os);
 
   // Retrieve all the definitions derived from CIR_Op and sort by record name.
-  std::vector<Record *> defs = records.getAllDerivedDefinitions("Op");
+  std::vector<const Record *> defs = records.getAllDerivedDefinitions("Op");
   llvm::sort(defs, LessRecord());
 
   // Iterate through all the ops defined.

circle-mlir/circle-mlir/tools/onnx2circle/src/onnx2circle.cpp

@@ -73,7 +73,7 @@ int loadONNX(const std::string &onnx_path, mlir::MLIRContext &context,
 {
   llvm::StringRef inputFilename(onnx_path);
   std::string errorMessage;
-  if (inputFilename.endswith(".mlir"))
+  if (inputFilename.ends_with(".mlir"))
   {
     auto input = mlir::openInputFile(inputFilename, &errorMessage);
     if (!input)
@@ -95,7 +95,7 @@ int loadONNX(const std::string &onnx_path, mlir::MLIRContext &context,
       return -1;
     }
   }
-  else if (inputFilename.endswith(".onnx"))
+  else if (inputFilename.ends_with(".onnx"))
   {
     onnx_mlir::ImportOptions options;
     options.useOnnxModelTypes = onnx_mlir::useOnnxModelTypes;

circle-mlir/externals/CMakeLists.txt

@@ -1,5 +1,5 @@
 # Match the minimum required version of LLVM and MLIR
-cmake_minimum_required(VERSION 3.13.4)
+cmake_minimum_required(VERSION 3.20.0)
 
 project(circle-mlir-externals)
 
@@ -105,7 +105,7 @@ ExternalProject_Add(externals-abseil-cpp
 # from https://github.com/onnx/onnx-mlir/blob/main/docs/BuildOnLinuxOSX.md
 ExternalProject_Add(externals-llvm-project
   GIT_REPOSITORY "https://github.com/llvm/llvm-project.git"
-  GIT_TAG        "91088978d712cd7b33610c59f69d87d5a39e3113"
+  GIT_TAG        "b270525f730be6e7196667925f5a9bfa153262e9"
   SOURCE_DIR     "${CMAKE_CURRENT_SOURCE_DIR}/llvm-project"
   SOURCE_SUBDIR  "llvm"
   BINARY_DIR     "${LP_BUILD_DIR}"
@@ -145,22 +145,24 @@ list(APPEND CMAKE_PREFIX_PATH ${PB_INSTALL_DIR})
 # build ONNX-MLIR
 ExternalProject_Add(externals-onnx-mlir
   GIT_REPOSITORY "https://github.com/onnx/onnx-mlir.git"
-  GIT_TAG        "40615b362fe474d6cce4fd9c31a7ec51acd8f88a" # v0.4.1.2
+  GIT_TAG        "660bd8efa664bd2d05801a7a793fe29925313b4b" # v0.5.0.0
+  GIT_SUBMODULES_RECURSE True
   SOURCE_DIR     "${CMAKE_CURRENT_SOURCE_DIR}/onnx-mlir"
   BINARY_DIR     "${OM_BUILD_DIR}"
   INSTALL_DIR    "${OM_INSTALL_DIR}"
-  PATCH_COMMAND  patch -p1 < ${CMAKE_CURRENT_SOURCE_DIR}/onnx_quantdequant_i16.diff -N || true
+  PATCH_COMMAND  patch -p1 < ${CMAKE_CURRENT_SOURCE_DIR}/onnx_mlir_0_5_0_0.diff -N || true
   CMAKE_ARGS     -DCMAKE_BUILD_TYPE=Release
                  -DCMAKE_PREFIX_PATH='${CMAKE_PREFIX_PATH}'
                  -DCMAKE_INSTALL_PREFIX='${OM_INSTALL_DIR}'
                  ${CIRCLE_MLIR_CLANG_OPTION}
                  -DMLIR_DIR='${LP_BUILD_DIR}/lib/cmake/mlir'
                  -DPython3_ROOT_DIR='$ENV{Python3_ROOT_DIR}'
                  -DONNX_MLIR_BUILD_TESTS=OFF
-                 -DONNX_MLIR_ENABLE_MHLO=OFF
-                 -DONNX_MLIR_DECOMP_ONNX_CONVTRANSPOSE=OFF
+                 -DONNX_MLIR_ENABLE_STABLEHLO=OFF
+                 -DONNX_MLIR_ENABLE_JAVA=OFF
                  -DLLVM_ENABLE_ASSERTIONS=ON
   DEPENDS        externals-llvm-project externals-protobuf
 )
-# NOTE onnx_quantdequant_i16.diff is to provide I16 type in
-#      DequantizeLinear/QuantizeLinear Ops
+# NOTE onnx_mlir_0_5_0_0.diff is to provide I16 type in DequantizeLinear/QuantizeLinear Ops
+#      and disable decompose for InstanceNormalization and ConvTranspose
+#      and not necessary test build.

circle-mlir/infra/overlay/prepare-venv

@@ -35,9 +35,9 @@ fi
 # NOTE version
 # - https://github.com/onnx/onnx/blob/master/docs/Versioning.md
 
-VER_TORCH=2.1.0
-VER_ONNX=1.16.0
-VER_ONNXRUNTIME=1.18.0
+VER_TORCH=2.6.0
+VER_ONNX=1.17.0
+VER_ONNXRUNTIME=1.21.0
 
 PIP_TRUSTED_HOST="--trusted-host pypi.org "
 PIP_TRUSTED_HOST+="--trusted-host pypi.python.org "
@@ -61,5 +61,5 @@ ${VENV_PYTHON} -m pip ${PIP_OPTIONS} install torch==${VER_TORCH}
 ${VENV_PYTHON} -m pip ${PIP_OPTIONS} install onnx==${VER_ONNX}
 ${VENV_PYTHON} -m pip ${PIP_OPTIONS} install onnxruntime==${VER_ONNXRUNTIME}
 
-${VENV_PYTHON} -m pip ${PIP_OPTIONS} install h5py einops
-${VENV_PYTHON} -m pip ${PIP_OPTIONS} install numpy==1.24.4
+${VENV_PYTHON} -m pip ${PIP_OPTIONS} install h5py==3.8.0 einops
+${VENV_PYTHON} -m pip ${PIP_OPTIONS} install numpy==1.24.3