Add Ch.5 of the toy tutorial.

This chapter adds a partial lowering of toy operations, all but PrintOp, to a combination of the Affine and Std dialects. This chapter focuses on introducing the conversion framework, the benefits of partial lowering, and how easily dialects may co-exist in the IR.

PiperOrigin-RevId: 275150649

Author: River707

examples/toy/Ch3/mlir/Dialect.cpp

@@ -55,22 +55,27 @@ static void buildConstantOp(mlir::Builder *builder, mlir::OperationState &state,
   ConstantOp::build(builder, state, dataType, dataAttribute);
 }
 
-/// Verifier for constant operation.
+/// Verifier for the constant operation. This corresponds to the `::verify(...)`
+/// in the op definition.
 static mlir::LogicalResult verify(ConstantOp op) {
   // If the return type of the constant is not an unranked tensor, the shape
   // must match the shape of the attribute holding the data.
   auto resultType = op.getResult()->getType().cast<RankedTensorType>();
   if (!resultType)
     return success();
 
+  // Check that the rank of the attribute type matches the rank of the constant
+  // result type.
   auto attrType = op.value().getType().cast<mlir::TensorType>();
   if (attrType.getRank() != resultType.getRank()) {
     return op.emitOpError(
                "return type must match the one of the attached value "
                "attribute: ")
            << attrType.getRank() << " != " << resultType.getRank();
   }
-  for (int dim = 0; dim < attrType.getRank(); ++dim) {
+
+  // Check that each of the dimensions match between the two types.
+  for (int dim = 0, dimE = attrType.getRank(); dim < dimE; ++dim) {
     if (attrType.getShape()[dim] != resultType.getShape()[dim]) {
       return op.emitOpError(
                  "return type shape mismatches its attribute at dimension ")

examples/toy/Ch4/mlir/Dialect.cpp

@@ -118,14 +118,18 @@ static mlir::LogicalResult verify(ConstantOp op) {
   if (!resultType)
     return success();
 
+  // Check that the rank of the attribute type matches the rank of the constant
+  // result type.
   auto attrType = op.value().getType().cast<mlir::TensorType>();
   if (attrType.getRank() != resultType.getRank()) {
     return op.emitOpError(
                "return type must match the one of the attached value "
                "attribute: ")
            << attrType.getRank() << " != " << resultType.getRank();
   }
-  for (int dim = 0; dim < attrType.getRank(); ++dim) {
+
+  // Check that each of the dimensions match between the two types.
+  for (int dim = 0, dimE = attrType.getRank(); dim < dimE; ++dim) {
     if (attrType.getShape()[dim] != resultType.getShape()[dim]) {
       return op.emitOpError(
                  "return type shape mismatches its attribute at dimension ")

examples/toy/Ch4/mlir/MLIRGen.cpp

@@ -79,7 +79,7 @@ class MLIRGenImpl {
     // the structural properties of the IR and invoke any specific verifiers we
     // have on the Toy operations.
     if (failed(mlir::verify(theModule))) {
-      theModule.emitError("Module verification error");
+      theModule.emitError("module verification error");
       return nullptr;
     }
 
@@ -229,7 +229,7 @@ class MLIRGenImpl {
     if (auto *variable = symbolTable.lookup(expr.getName()))
       return variable;
 
-    emitError(loc(expr.loc()), "Error: unknown variable '")
+    emitError(loc(expr.loc()), "error: unknown variable '")
         << expr.getName() << "'";
     return nullptr;
   }
@@ -289,7 +289,8 @@ class MLIRGenImpl {
     auto dataAttribute =
         mlir::DenseElementsAttr::get(dataType, llvm::makeArrayRef(data));
 
-    // Build the MLIR op `toy.constant`.
+    // Build the MLIR op `toy.constant`. This invokes the `ConstantOp::build`
+    // method.
     return builder.create<ConstantOp>(loc(lit.loc()), type, dataAttribute);
   }
 
@@ -389,7 +390,7 @@ class MLIRGenImpl {
     auto init = vardecl.getInitVal();
     if (!init) {
       emitError(loc(vardecl.loc()),
-                "Missing initializer in variable declaration");
+                "missing initializer in variable declaration");
       return nullptr;
     }
 

examples/toy/Ch5/CMakeLists.txt

@@ -1,40 +1,42 @@
+add_subdirectory(include)
+
 set(LLVM_LINK_COMPONENTS
   Support
   )
 
+set(LLVM_TARGET_DEFINITIONS mlir/ToyCombine.td)
+mlir_tablegen(ToyCombine.inc -gen-rewriters "-I${CMAKE_CURRENT_SOURCE_DIR}/include")
+add_public_tablegen_target(ToyCh5CombineIncGen)
+
 add_toy_chapter(toyc-ch5
   toyc.cpp
   parser/AST.cpp
-  mlir/EarlyLowering.cpp
-  mlir/LateLowering.cpp
   mlir/MLIRGen.cpp
+  mlir/Dialect.cpp
+  mlir/DeadFunctionEliminationPass.cpp
+  mlir/LowerToAffineLoops.cpp
   mlir/ShapeInferencePass.cpp
-  mlir/ToyDialect.cpp
   mlir/ToyCombine.cpp
   )
+
+add_dependencies(toyc-ch5 ToyCh5ShapeInferenceInterfaceIncGen)
+add_dependencies(toyc-ch5 ToyCh5OpsIncGen)
+add_dependencies(toyc-ch5 ToyCh5CombineIncGen)
+add_dependencies(toyc-ch5 MLIRCallOpInterfacesIncGen)
 include_directories(include/)
-include_directories(../../Linalg/Linalg1/include/)
-include_directories(../../Linalg/Linalg2/include/)
-include_directories(../../Linalg/Linalg3/include/)
+include_directories(${CMAKE_CURRENT_BINARY_DIR})
+include_directories(${CMAKE_CURRENT_BINARY_DIR}/include/)
 target_link_libraries(toyc-ch5
   PRIVATE
-    Linalg3DialectConstruction
-    Linalg3
-    Linalg2
-    Linalg1
+    MLIRAffineOps
     MLIRAnalysis
-    MLIREDSC
-    MLIRExecutionEngine
     MLIRIR
-    MLIRLLVMIR
     MLIRParser
     MLIRPass
-    MLIRTargetLLVMIR
-    MLIRTransforms
-    MLIRSupport
-)
+    MLIRStandardOps
+    MLIRTransforms)
+
 whole_archive_link(toyc-ch5
   MLIRAffineOps
   MLIRStandardOps
-)
-
+  )

examples/toy/Ch5/include/CMakeLists.txt

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

examples/toy/Ch5/include/toy/AST.h

@@ -33,10 +33,9 @@
 
 namespace toy {
 
-/// A variable
+/// A variable type with shape information.
 struct VarType {
-  enum { TY_FLOAT, TY_INT } elt_ty;
-  std::vector<int> shape;
+  std::vector<int64_t> shape;
 };
 
 /// Base class for all expression nodes.
@@ -50,9 +49,7 @@ class ExprAST {
     Expr_Var,
     Expr_BinOp,
     Expr_Call,
-    Expr_Print, // builtin
-    Expr_If,
-    Expr_For,
+    Expr_Print,
   };
 
   ExprAST(ExprASTKind kind, Location location)
@@ -85,7 +82,7 @@ class NumberExprAST : public ExprAST {
   static bool classof(const ExprAST *C) { return C->getKind() == Expr_Num; }
 };
 
-///
+/// Expression class for a literal value.
 class LiteralExprAST : public ExprAST {
   std::vector<std::unique_ptr<ExprAST>> values;
   std::vector<int64_t> dims;
@@ -116,7 +113,7 @@ class VariableExprAST : public ExprAST {
   static bool classof(const ExprAST *C) { return C->getKind() == Expr_Var; }
 };
 
-///
+/// Expression class for defining a variable.
 class VarDeclExprAST : public ExprAST {
   std::string name;
   VarType type;
@@ -136,7 +133,7 @@ class VarDeclExprAST : public ExprAST {
   static bool classof(const ExprAST *C) { return C->getKind() == Expr_VarDecl; }
 };
 
-///
+/// Expression class for a return operator.
 class ReturnExprAST : public ExprAST {
   llvm::Optional<std::unique_ptr<ExprAST>> expr;
 

examples/toy/Ch5/include/toy/CMakeLists.txt

@@ -0,0 +1,9 @@
+set(LLVM_TARGET_DEFINITIONS Ops.td)
+mlir_tablegen(Ops.h.inc -gen-op-decls "-I${CMAKE_CURRENT_SOURCE_DIR}/..")
+mlir_tablegen(Ops.cpp.inc -gen-op-defs "-I${CMAKE_CURRENT_SOURCE_DIR}/..")
+add_public_tablegen_target(ToyCh5OpsIncGen)
+
+set(LLVM_TARGET_DEFINITIONS ShapeInferenceInterface.td)
+mlir_tablegen(ShapeInferenceOpInterfaces.h.inc -gen-op-interface-decls)
+mlir_tablegen(ShapeInferenceOpInterfaces.cpp.inc -gen-op-interface-defs)
+add_public_tablegen_target(ToyCh5ShapeInferenceInterfaceIncGen)