FEAT-#128: oneDNN: Implement compilation and execution

CMakeLists.txt

@@ -96,12 +96,12 @@ if(GC_ENABLE_BINDINGS_PYTHON)
 endif()
 
 set(GC_LIB_LINKED_LIBS
-        GCPasses
-        MLIROneDNNGraph
+        GCJitWrapper
+        GCCpuRuntime
 )
-add_library(graph_compiler SHARED ${GC_LIB_SOURCES})
+add_mlir_library(graph_compiler SHARED ${GC_LIB_SOURCES})
 target_include_directories(graph_compiler PUBLIC ${GC_LIB_INCLUDES})
-target_compile_options(graph_compiler PRIVATE -fvisibility=hidden)
+target_compile_options(graph_compiler PRIVATE -fvisibility=hidden -fexceptions)
 target_link_options(graph_compiler PRIVATE -Wl,--gc-sections)
 target_link_libraries(graph_compiler PRIVATE ${GC_LIB_LINKED_LIBS})
 

src/dnnl/JsonParser.cpp

@@ -23,15 +23,18 @@
 
 #include "gc/Dialect/OneDNNGraph/OneDNNGraphDialect.h"
 
+#include "mlir/Dialect/LLVMIR/LLVMDialect.h"
 #include "mlir/ExecutionEngine/OptUtils.h"
 #include "mlir/IR/Builders.h"
 #include "mlir/IR/MLIRContext.h"
 #include "mlir/InitAllPasses.h"
 
 #include "JsonParser.h"
 
-mlir::ModuleOp JsonParser::parse() {
-  std::vector<size_t> inputPorts;
+mlir::ModuleOp
+JsonParser::parse(llvm::SmallVector<size_t> &outputIds,
+                  std::unordered_map<std::size_t, Strides> &strides) {
+  llvm::SmallVector<size_t> inputPorts;
   bool hasInputPorts = false;
   bool hasOutputPorts = false;
   _reader.begin_object();
@@ -57,7 +60,7 @@ mlir::ModuleOp JsonParser::parse() {
       readNumArray(inputPorts);
     } else if (_str == "output_ports") {
       hasOutputPorts = true;
-      readNumArray(_outputIds);
+      readNumArray(outputIds);
     } else if (_str == "graph") {
       _reader.begin_array();
       while (_reader.next_array_item()) {
@@ -87,13 +90,13 @@ mlir::ModuleOp JsonParser::parse() {
 
   if (!hasOutputPorts) {
     // If output_ports is not specified, using the last operation's outputs.
-    _outputIds = _uaS;
+    outputIds.append(_uaS.begin(), _uaS.end());
   }
 
   // The function return values.
-  std::vector<mlir::Value> outputs;
-  outputs.reserve(_outputIds.size());
-  for (auto id : _outputIds) {
+  llvm::SmallVector<mlir::Value> outputs;
+  outputs.reserve(outputIds.size());
+  for (auto id : outputIds) {
     auto entry = _valueMap.find(id);
     if (entry == _valueMap.end()) {
       _str = std::to_string(id);
@@ -103,13 +106,25 @@ mlir::ModuleOp JsonParser::parse() {
   }
   auto ret = _builder.create<mlir::func::ReturnOp>(_loc, outputs);
 
+  // Copying the strides for the inputs and outputs.
+  for (auto &ids : {&_inputIds, &outputIds}) {
+    for (auto id : *ids) {
+      auto entry = _strides.find(id);
+      if (entry != _strides.end()) {
+        strides[id] = entry->second;
+      }
+    }
+  }
+
   // Creating the final function and moving the entry block.
   mlir::OpBuilder builder(_builder.getContext());
   auto module = builder.create<mlir::ModuleOp>(_loc);
   auto func = builder.create<mlir::func::FuncOp>(
-      _loc, "main",
+      _loc, "compute",
       builder.getFunctionType(_entryBlock->getArgumentTypes(),
                               ret->getOperandTypes()));
+  func->setAttr(mlir::LLVM::LLVMDialect::getEmitCWrapperAttrName(),
+                mlir::UnitAttr::get(_builder.getContext()));
   auto entry = func.addEntryBlock();
   _entryBlock->moveBefore(entry);
   entry->erase();
@@ -251,7 +266,9 @@ inline mlir::Attribute JsonParser::readAttr() {
 
 mlir::Type JsonParser::readTensorType() {
   GetTypeFn getTypeFn = nullptr;
+  bool strided = false;
   _ia64.clear();
+  _ia642.clear();
   _reader.begin_object();
 
   while (_reader.next_object_item(&_str)) {
@@ -267,22 +284,17 @@ mlir::Type JsonParser::readTensorType() {
     } else if (_str == "shape") {
       readNumArray(_ia64);
     } else if (_str == "stride") {
-      _ia642.clear();
       readNumArray(_ia642);
-      if ((_ia642.size() > 1) ||
-          ((_ia642.size() == 1) &&
-           (_ia642[0] != std::numeric_limits<int64_t>::min()))) {
-        // TODO: Add support for strides
-        throwErr<std::logic_error>("Unsupported stride value: ");
-      }
     } else if (_str == "layout_type") {
       _reader.read_string(&_str);
-      if ((_str != "undef") && (_str != "any")) {
+      if (_str == "strided") {
+        strided = true;
+      } else if ((_str != "undef") && (_str != "any")) {
         throwErr<std::logic_error>("Unsupported layout_type: ");
       }
     } else if (_str == "property_type") {
       _reader.read_string(&_str);
-      if ((_str != "undef") && (_str != "constant")) {
+      if ((_str != "undef") && (_str != "variable") && (_str != "constant")) {
         throwErr<std::logic_error>("Unsupported property_type: ");
       }
     } else {
@@ -295,6 +307,10 @@ mlir::Type JsonParser::readTensorType() {
     throwErr<std::invalid_argument>("dtype is not specified");
   }
 
+  if (strided) {
+    _strides[_uS].assign(_ia642.begin(), _ia642.end());
+  }
+
   if ((_ia64.size() == 1) &&
       (_ia64[0] == std::numeric_limits<int64_t>::min())) {
     return mlir::UnrankedTensorType::get(getTypeFn(_builder));

src/dnnl/JsonParser.h

@@ -43,22 +43,25 @@ using float32_t = float;
 #include "mlir/Parser/Parser.h"
 #include "mlir/Tools/mlir-opt/MlirOptMain.h"
 
+#include "dnnl_types.h"
 #include "graph/utils/json.hpp"
 
+using Strides = llvm::SmallVector<int64_t, DNNL_MAX_NDIMS>;
+
 class JsonParser {
   dnnl::impl::graph::utils::json::json_reader_t _reader;
   mlir::OpBuilder _builder;
   mlir::Location _loc;
   mlir::Block *_entryBlock;
-  std::vector<size_t> &_inputIds;
-  std::vector<size_t> &_outputIds;
+  llvm::SmallVector<size_t> &_inputIds;
+  std::unordered_map<std::size_t, Strides> _strides;
   // Function input and operations output values. Used to connect the
   // operations inputs and outputs.
   std::unordered_map<std::size_t, mlir::Value> _valueMap;
   // Temporary value holders, used by the parser
-  std::vector<mlir::Value> _operands;
-  std::vector<mlir::Type> _resultTypes;
-  std::vector<mlir::NamedAttribute> _attributes;
+  llvm::SmallVector<mlir::Value> _operands;
+  llvm::SmallVector<mlir::Type> _resultTypes;
+  llvm::SmallVector<mlir::NamedAttribute> _attributes;
   std::string _str;
   std::string _str2;
   std::size_t _uS;
@@ -70,9 +73,9 @@ class JsonParser {
   std::vector<std::float32_t> _fa32;
 
   JsonParser(mlir::MLIRContext &context, std::istream &stream,
-             std::vector<size_t> &inputIds, std::vector<size_t> &outputIds)
+             llvm::SmallVector<size_t> &inputIds)
       : _reader(&stream), _builder(&context), _loc(_builder.getUnknownLoc()),
-        _inputIds(inputIds), _outputIds(outputIds), _valueMap(), _operands(),
+        _inputIds(inputIds), _strides(), _valueMap(), _operands(),
         _resultTypes(), _attributes(), _str(), _str2(), _uS(), _i64(), _f32(),
         _uaS(), _ia64(), _ia642(), _fa32() {
     // Creating a dummy function since we don't know the actual type yet.
@@ -82,7 +85,8 @@ class JsonParser {
     _builder.setInsertionPointToStart(_entryBlock);
   }
 
-  mlir::ModuleOp parse();
+  mlir::ModuleOp parse(llvm::SmallVector<size_t> &outputIds,
+                       std::unordered_map<std::size_t, Strides> &strides);
   void readOp();
   mlir::Attribute readAttr();
   mlir::Type readTensorType();
@@ -120,11 +124,12 @@ class JsonParser {
     }
   }
 
-  template <typename T> inline void readNumArray(std::vector<T> &vec) {
+  template <typename T, template <typename...> class Container, typename... Any>
+  inline void readNumArray(Container<T, Any...> &c) {
     _reader.begin_array();
     for (T value; _reader.next_array_item();) {
       _reader.read_number(&value);
-      vec.push_back(value);
+      c.push_back(value);
     }
   }
 
@@ -175,14 +180,16 @@ class JsonParser {
    * @param json JSON string containing the oneDNN graph.
    * @param inputIds Input tensor IDs are added to this vector.
    * @param outputIds Output tensor IDs are added to this vector.
+   * @param strides Strides for each tensor are added to this map.
    * @return The resulting MLIR module.
    */
-  static mlir::ModuleOp parse(mlir::MLIRContext &context,
-                              const std::string_view &json,
-                              std::vector<size_t> &inputIds,
-                              std::vector<size_t> &outputIds) {
+  static mlir::ModuleOp
+  parse(mlir::MLIRContext &context, const std::string_view &json,
+        llvm::SmallVector<size_t> &inputIds,
+        llvm::SmallVector<size_t> &outputIds,
+        std::unordered_map<std::size_t, Strides> &strides) {
     std::istringstream stream(json.data());
-    JsonParser parser(context, stream, inputIds, outputIds);
-    return parser.parse();
+    JsonParser parser(context, stream, inputIds);
+    return parser.parse(outputIds, strides);
   }
 };