From c9f7c370fcf96f941774648da5b80955299bf80a Mon Sep 17 00:00:00 2001
From: lonely eagle <75576166+linuxlonelyeagle@users.noreply.github.com>
Date: Tue, 19 Sep 2023 14:01:56 +0800
Subject: [PATCH] fix toy DSL. (#202)

fix toy DSL.
---
 examples/ToyDSL/main.cpp | 18 ++++++++++++++----
 1 file changed, 14 insertions(+), 4 deletions(-)

diff --git a/examples/ToyDSL/main.cpp b/examples/ToyDSL/main.cpp
index 616193f07c..f5355e739b 100644
--- a/examples/ToyDSL/main.cpp
+++ b/examples/ToyDSL/main.cpp
@@ -45,6 +45,7 @@
 #include "mlir/Parser/Parser.h"
 #include "mlir/Pass/Pass.h"
 #include "mlir/Pass/PassManager.h"
+#include "mlir/Target/LLVMIR/Dialect/Builtin/BuiltinToLLVMIRTranslation.h"
 #include "mlir/Target/LLVMIR/Dialect/LLVMIR/LLVMToLLVMIRTranslation.h"
 #include "mlir/Target/LLVMIR/Export.h"
 #include "mlir/Transforms/Passes.h"
@@ -135,7 +136,6 @@ int loadAndProcessMLIR(mlir::MLIRContext &context,
     // Now that there is only one function, we can infer the shapes of each of
     // the operations.
     mlir::OpPassManager &optPM = pm.nest<mlir::toy::FuncOp>();
-    optPM.addPass(mlir::createCanonicalizerPass());
     optPM.addPass(mlir::toy::createShapeInferencePass());
     optPM.addPass(mlir::createCanonicalizerPass());
     optPM.addPass(mlir::createCSEPass());
@@ -152,8 +152,8 @@ int loadAndProcessMLIR(mlir::MLIRContext &context,
 
     // Add optimizations if enabled.
     if (enableOpt) {
-      optPM.addPass(mlir::createLoopFusionPass());
-      optPM.addPass(mlir::createAffineScalarReplacementPass());
+      optPM.addPass(mlir::affine::createLoopFusionPass());
+      optPM.addPass(mlir::affine::createAffineScalarReplacementPass());
     }
   }
 
@@ -191,7 +191,16 @@ int dumpLLVMIR(mlir::ModuleOp module) {
   // Initialize LLVM targets.
   llvm::InitializeNativeTarget();
   llvm::InitializeNativeTargetAsmPrinter();
-  mlir::ExecutionEngine::setupTargetTriple(llvmModule.get());
+
+  auto tmBuilderOrError = llvm::orc::JITTargetMachineBuilder::detectHost();
+  if (!tmBuilderOrError) {
+    llvm::errs() << "Could not create JITTargetMachineBuilder\n";
+    return -1;
+  }
+
+  auto tmOrError = tmBuilderOrError->createTargetMachine();
+  mlir::ExecutionEngine::setupTargetTripleAndDataLayout(llvmModule.get(),
+                                                        tmOrError.get().get());
 
   /// Optionally run an optimization pipeline over the llvm module.
   auto optPipeline = mlir::makeOptimizingTransformer(
@@ -212,6 +221,7 @@ int runJit(mlir::ModuleOp module) {
 
   // Register the translation from MLIR to LLVM IR, which must happen before we
   // can JIT-compile.
+  mlir::registerBuiltinDialectTranslation(*module->getContext());
   mlir::registerLLVMDialectTranslation(*module->getContext());
 
   // An optimization pipeline to use within the execution engine.