Error fix3 (#145)

* removed warning missing return, dangling else

* fixed errors, made sure to return false in all shape inference failures

* shape inference use LogicalResults as return value

* format fixed

* format error

Co-authored-by: Tian Jin <tjingrant@gmail.com>

src/Conversion/ONNXToKrnl/Math/Elementwise.cpp

@@ -490,6 +490,7 @@ Value emitScalarOpFor<ONNXNegOp>(ConversionPatternRewriter &rewriter,
     return rewriter.create<mlir::SubIOp>(loc, zero, operand); // 0 - X = -X
   } else {
     emitError(loc, "unsupported element type");
+    return nullptr;
   }
 }
 

src/Conversion/ONNXToKrnl/Math/MatMul.cpp

@@ -258,12 +258,12 @@ struct ONNXMatMulOpLowering : public ConversionPattern {
         for (auto arg : loopBatchIVs)
           loopBatchKNIVs.emplace_back(arg);
       loopBatchKNIVs.emplace_back(loopKIVs[0]);
-      if (BShape.size() >= 2)
+      if (BShape.size() >= 2) {
         if (AShape.size() >= 2)
           loopBatchKNIVs.emplace_back(loopMNIVs[1]);
         else
           loopBatchKNIVs.emplace_back(loopMNIVs[0]);
-
+      }
       // Matmul computation
       auto loadedA = rewriter.create<LoadOp>(loc, A, loopBatchMKIVs);
       auto loadedB = rewriter.create<LoadOp>(loc, B, loopBatchKNIVs);

src/Dialect/Krnl/KrnlOps.hpp

@@ -32,6 +32,7 @@ public:
       return LoopType::get(parser.getBuilder().getContext());
 
     parser.emitError(parser.getCurrentLocation(), "Unknown type");
+    return nullptr;
   }
 
   /// Print a type registered to this dialect.

src/Interface/ShapeInferenceInterface.td

@@ -25,7 +25,7 @@ def ShapeInferenceOpInterface : OpInterface<"ShapeInference"> {
 
   let methods = [
     InterfaceMethod<"Infer and set the output shape for the current operation.",
-                    "bool", "inferShapes">
+                    "LogicalResult", "inferShapes">
   ];
 }
 

src/Transform/ONNX/ShapeInferencePass.cpp

@@ -36,7 +36,7 @@ public:
     f.walk([&](mlir::Operation *op) {
       if (returnsDynamicShape(op)) {
         if (auto shape_op = dyn_cast<ShapeInference>(op)) {
-          if (!shape_op.inferShapes()) {
+          if (failed(shape_op.inferShapes())) {
             op->emitError("unable to infer shape of operation without shape "
                           "inference method");
             return signalPassFailure();