[mlir][Pass][NFC] Replace usages of ModulePass with OperationPass<ModuleOp>

[rriddle]

Summary

ModulePass doesn't provide any special utilities and thus doesn't give enough benefit to warrant a special pass class. This revision replaces all usages with the more general OperationPass.

[rriddle]

Update

[rriddle]

Rebase

[rriddle]

Rebase

mlir/docs/Tutorials/Toy/Ch-6.md

 ```
 
 ### Full Lowering
 
 We want to completely lower to LLVM, so we use a `FullConversion`. This ensures
 that only legal operations will remain after the conversion.
 
 ```c++
-  mlir::ModuleOp module = getModule();
+  mlir::ModuleOp module = getOperation();
   if (mlir::failed(mlir::applyFullConversion(module, target, patterns,
                                              &typeConverter)))
     signalPassFailure();
 ```
 
 Looking back at our current working example:
 
 ```mlir

mlir/examples/toy/Ch6/mlir/LowerToLLVM.cpp

 };
 } // end anonymous namespace
 
 //===----------------------------------------------------------------------===//
 // ToyToLLVMLoweringPass
 //===----------------------------------------------------------------------===//
 
 namespace {
-struct ToyToLLVMLoweringPass : public ModulePass<ToyToLLVMLoweringPass> {
-  void runOnModule() final;
+struct ToyToLLVMLoweringPass
+    : public OperationPass<ToyToLLVMLoweringPass, ModuleOp> {
+  void runOnOperation() final;
 };
 } // end anonymous namespace
 
-void ToyToLLVMLoweringPass::runOnModule() {
+void ToyToLLVMLoweringPass::runOnOperation() {
   // The first thing to define is the conversion target. This will define the
   // final target for this lowering. For this lowering, we are only targeting
   // the LLVM dialect.
   LLVMConversionTarget target(getContext());
   target.addLegalOp<ModuleOp, ModuleTerminatorOp>();
 
   // During this lowering, we will also be lowering the MemRef types, that are
   // currently being operated on, to a representation in LLVM. Do perform this
void ToyToLLVMLoweringPass::runOnOperation() {
   populateStdToLLVMConversionPatterns(typeConverter, patterns);
 
   // The only remaining operation to lower from the `toy` dialect, is the
   // PrintOp.
   patterns.insert<PrintOpLowering>(&getContext());
 
   // We want to completely lower to LLVM, so we use a `FullConversion`. This
   // ensures that only legal operations will remain after the conversion.
-  auto module = getModule();
+  auto module = getOperation();
   if (failed(applyFullConversion(module, target, patterns, &typeConverter)))
     signalPassFailure();
 }
 
 /// Create a pass for lowering operations the remaining `Toy` operations, as
 /// well as `Affine` and `Std`, to the LLVM dialect for codegen.
 std::unique_ptr<mlir::Pass> mlir::toy::createLowerToLLVMPass() {
   return std::make_unique<ToyToLLVMLoweringPass>();
 }

mlir/examples/toy/Ch7/mlir/LowerToLLVM.cpp

 };
 } // end anonymous namespace
 
 //===----------------------------------------------------------------------===//
 // ToyToLLVMLoweringPass
 //===----------------------------------------------------------------------===//
 
 namespace {
-struct ToyToLLVMLoweringPass : public ModulePass<ToyToLLVMLoweringPass> {
-  void runOnModule() final;
+struct ToyToLLVMLoweringPass
+    : public OperationPass<ToyToLLVMLoweringPass, ModuleOp> {
+  void runOnOperation() final;
 };
 } // end anonymous namespace
 
-void ToyToLLVMLoweringPass::runOnModule() {
+void ToyToLLVMLoweringPass::runOnOperation() {
   // The first thing to define is the conversion target. This will define the
   // final target for this lowering. For this lowering, we are only targeting
   // the LLVM dialect.
   LLVMConversionTarget target(getContext());
   target.addLegalOp<ModuleOp, ModuleTerminatorOp>();
 
   // During this lowering, we will also be lowering the MemRef types, that are
   // currently being operated on, to a representation in LLVM. Do perform this
void ToyToLLVMLoweringPass::runOnOperation() {
   populateStdToLLVMConversionPatterns(typeConverter, patterns);
 
   // The only remaining operation to lower from the `toy` dialect, is the
   // PrintOp.
   patterns.insert<PrintOpLowering>(&getContext());
 
   // We want to completely lower to LLVM, so we use a `FullConversion`. This
   // ensures that only legal operations will remain after the conversion.
-  auto module = getModule();
+  auto module = getOperation();
   if (failed(applyFullConversion(module, target, patterns, &typeConverter)))
     signalPassFailure();
 }
 
 /// Create a pass for lowering operations the remaining `Toy` operations, as
 /// well as `Affine` and `Std`, to the LLVM dialect for codegen.
 std::unique_ptr<mlir::Pass> mlir::toy::createLowerToLLVMPass() {
   return std::make_unique<ToyToLLVMLoweringPass>();
 }

mlir/include/mlir/Pass/Pass.h

template <typename T> struct FunctionPass : public OperationPass<T, FuncOp> {
   virtual void runOnFunction() = 0;
 
   /// The polymorphic API that runs the pass over the currently held operation.
   void runOnOperation() final {
     if (!getFunction().isExternal())
       runOnFunction();
   }
 
-  /// Return the current module being transformed.
+  /// Return the current function being transformed.
   FuncOp getFunction() { return this->getOperation(); }
 };
-
-/// A model for providing module pass specific utilities.
-///
-/// Derived module passes are expected to provide the following:
-///   - A 'void runOnModule()' method.
-template <typename T> struct ModulePass : public OperationPass<T, ModuleOp> {
-  /// The polymorphic API that runs the pass over the currently held module.
-  virtual void runOnModule() = 0;
-
-  /// The polymorphic API that runs the pass over the currently held operation.
-  void runOnOperation() final { runOnModule(); }
-
-  /// Return the current module being transformed.
-  ModuleOp getModule() { return this->getOperation(); }
-};
 } // end namespace mlir
 
 #endif // MLIR_PASS_PASS_H

mlir/lib/Conversion/AVX512ToLLVM/ConvertAVX512ToLLVM.cpp

void mlir::populateAVX512ToLLVMConversionPatterns(
   patterns.insert<MaskRndScaleOpPS512Conversion,
                   MaskRndScaleOpPD512Conversion,
                   ScaleFOpPS512Conversion,
                   ScaleFOpPD512Conversion>(ctx, converter);
   // clang-format on
 }
 
 namespace {
-struct ConvertAVX512ToLLVMPass : public ModulePass<ConvertAVX512ToLLVMPass> {
+struct ConvertAVX512ToLLVMPass
+    : public OperationPass<ConvertAVX512ToLLVMPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertAVX512ToLLVM
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void ConvertAVX512ToLLVMPass::runOnModule() {
+void ConvertAVX512ToLLVMPass::runOnOperation() {
   // Convert to the LLVM IR dialect.
   OwningRewritePatternList patterns;
   LLVMTypeConverter converter(&getContext());
   populateAVX512ToLLVMConversionPatterns(converter, patterns);
   populateVectorToLLVMConversionPatterns(converter, patterns);
   populateStdToLLVMConversionPatterns(converter, patterns);
 
   ConversionTarget target(getContext());
   target.addLegalDialect<LLVM::LLVMDialect>();
   target.addLegalDialect<LLVM::LLVMAVX512Dialect>();
   target.addIllegalDialect<avx512::AVX512Dialect>();
   target.addDynamicallyLegalOp<FuncOp>(
       [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
-  if (failed(
-          applyPartialConversion(getModule(), target, patterns, &converter))) {
+  if (failed(applyPartialConversion(getOperation(), target, patterns,
+                                    &converter))) {
     signalPassFailure();
   }
 }
 
 std::unique_ptr<OpPassBase<ModuleOp>> mlir::createConvertAVX512ToLLVMPass() {
   return std::make_unique<ConvertAVX512ToLLVMPass>();
 }

mlir/lib/Conversion/GPUToCUDA/ConvertLaunchFuncToCudaCalls.cpp

 /// * mcuModuleLoad        -- loads the module given the cubin data
 /// * mcuModuleGetFunction -- gets a handle to the actual kernel function
 /// * mcuGetStreamHelper   -- initializes a new CUDA stream
 /// * mcuLaunchKernelName  -- launches the kernel on a stream
 /// * mcuStreamSynchronize -- waits for operations on the stream to finish
 ///
 /// Intermediate data structures are allocated on the stack.
 class GpuLaunchFuncToCudaCallsPass
-    : public ModulePass<GpuLaunchFuncToCudaCallsPass> {
+    : public OperationPass<GpuLaunchFuncToCudaCallsPass, ModuleOp> {
 private:
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertGpuLaunchFuncToCudaCalls
 #include "mlir/Conversion/Passes.h.inc"
 
   LLVM::LLVMDialect *getLLVMDialect() { return llvmDialect; }
 
   llvm::LLVMContext &getLLVMContext() {
void addParamToList(OpBuilder &builder, Location loc, Value param, Value list,
                       unsigned pos, Value one);
   Value setupParamsArray(gpu::LaunchFuncOp launchOp, OpBuilder &builder);
   Value generateKernelNameConstant(StringRef name, Location loc,
                                    OpBuilder &builder);
   void translateGpuLaunchCalls(mlir::gpu::LaunchFuncOp launchOp);
 
 public:
   // Run the dialect converter on the module.
-  void runOnModule() override {
+  void runOnOperation() override {
     // Cache the LLVMDialect for the current module.
     llvmDialect = getContext().getRegisteredDialect<LLVM::LLVMDialect>();
     // Cache the used LLVM types.
     initializeCachedTypes();
 
-    getModule().walk([this](mlir::gpu::LaunchFuncOp op) {
-      translateGpuLaunchCalls(op);
-    });
+    getOperation().walk(
+        [this](mlir::gpu::LaunchFuncOp op) { translateGpuLaunchCalls(op); });
 
     // GPU kernel modules are no longer necessary since we have a global
     // constant with the CUBIN data.
     for (auto m :
-         llvm::make_early_inc_range(getModule().getOps<gpu::GPUModuleOp>()))
+         llvm::make_early_inc_range(getOperation().getOps<gpu::GPUModuleOp>()))
       m.erase();
   }
 
 private:
   LLVM::LLVMDialect *llvmDialect;
   LLVM::LLVMType llvmVoidType;
   LLVM::LLVMType llvmPointerType;
   LLVM::LLVMType llvmPointerPointerType;
   LLVM::LLVMType llvmInt8Type;
   LLVM::LLVMType llvmInt32Type;
   LLVM::LLVMType llvmInt64Type;
   LLVM::LLVMType llvmIntPtrType;
 };
 
 } // anonymous namespace
 
 // Adds declarations for the needed helper functions from the CUDA wrapper.
 // The types in comments give the actual types expected/returned but the API
 // uses void pointers. This is fine as they have the same linkage in C.
 void GpuLaunchFuncToCudaCallsPass::declareCudaFunctions(Location loc) {
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
   OpBuilder builder(module.getBody()->getTerminator());
   if (!module.lookupSymbol(cuModuleLoadName)) {
     builder.create<LLVM::LLVMFuncOp>(
         loc, cuModuleLoadName,
         LLVM::LLVMType::getFunctionTy(
             getCUResultType(),
             {
                 getPointerPointerType(), /* CUmodule *module */
void GpuLaunchFuncToCudaCallsPass::translateGpuLaunchCalls(
   OpBuilder builder(launchOp);
   Location loc = launchOp.getLoc();
   declareCudaFunctions(loc);
 
   auto zero = builder.create<LLVM::ConstantOp>(loc, getInt32Type(),
                                                builder.getI32IntegerAttr(0));
   // Create an LLVM global with CUBIN extracted from the kernel annotation and
   // obtain a pointer to the first byte in it.
-  auto kernelModule = getModule().lookupSymbol<gpu::GPUModuleOp>(
+  auto kernelModule = getOperation().lookupSymbol<gpu::GPUModuleOp>(
       launchOp.getKernelModuleName());
   assert(kernelModule && "expected a kernel module");
 
   auto cubinAttr = kernelModule.getAttrOfType<StringAttr>(kCubinAnnotation);
   if (!cubinAttr) {
     kernelModule.emitOpError()
         << "missing " << kCubinAnnotation << " attribute";
     return signalPassFailure();
   }
 
   SmallString<128> nameBuffer(kernelModule.getName());
   nameBuffer.append(kCubinStorageSuffix);
   Value data = LLVM::createGlobalString(
       loc, builder, nameBuffer.str(), cubinAttr.getValue(),
       LLVM::Linkage::Internal, getLLVMDialect());
 
   // Emit the load module call to load the module data. Error checking is done
   // in the called helper function.
   auto cuModule = allocatePointer(builder, loc);
   auto cuModuleLoad =
-      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleLoadName);
+      getOperation().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleLoadName);
   builder.create<LLVM::CallOp>(loc, ArrayRef<Type>{getCUResultType()},
                                builder.getSymbolRefAttr(cuModuleLoad),
                                ArrayRef<Value>{cuModule, data});
   // Get the function from the module. The name corresponds to the name of
   // the kernel function.
   auto cuOwningModuleRef =
       builder.create<LLVM::LoadOp>(loc, getPointerType(), cuModule);
   auto kernelName = generateKernelNameConstant(launchOp.kernel(), loc, builder);
   auto cuFunction = allocatePointer(builder, loc);
   auto cuModuleGetFunction =
-      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleGetFunctionName);
+      getOperation().lookupSymbol<LLVM::LLVMFuncOp>(cuModuleGetFunctionName);
   builder.create<LLVM::CallOp>(
       loc, ArrayRef<Type>{getCUResultType()},
       builder.getSymbolRefAttr(cuModuleGetFunction),
       ArrayRef<Value>{cuFunction, cuOwningModuleRef, kernelName});
   // Grab the global stream needed for execution.
   auto cuGetStreamHelper =
-      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuGetStreamHelperName);
+      getOperation().lookupSymbol<LLVM::LLVMFuncOp>(cuGetStreamHelperName);
   auto cuStream = builder.create<LLVM::CallOp>(
       loc, ArrayRef<Type>{getPointerType()},
       builder.getSymbolRefAttr(cuGetStreamHelper), ArrayRef<Value>{});
   // Invoke the function with required arguments.
   auto cuLaunchKernel =
-      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuLaunchKernelName);
+      getOperation().lookupSymbol<LLVM::LLVMFuncOp>(cuLaunchKernelName);
   auto cuFunctionRef =
       builder.create<LLVM::LoadOp>(loc, getPointerType(), cuFunction);
   auto paramsArray = setupParamsArray(launchOp, builder);
   if (!paramsArray) {
     launchOp.emitOpError() << "cannot pass given parameters to the kernel";
     return signalPassFailure();
   }
   auto nullpointer =
       builder.create<LLVM::IntToPtrOp>(loc, getPointerPointerType(), zero);
   builder.create<LLVM::CallOp>(
       loc, ArrayRef<Type>{getCUResultType()},
       builder.getSymbolRefAttr(cuLaunchKernel),
       ArrayRef<Value>{cuFunctionRef, launchOp.getOperand(0),
                       launchOp.getOperand(1), launchOp.getOperand(2),
                       launchOp.getOperand(3), launchOp.getOperand(4),
                       launchOp.getOperand(5), zero, /* sharedMemBytes */
                       cuStream.getResult(0),        /* stream */
                       paramsArray,                  /* kernel params */
                       nullpointer /* extra */});
   // Sync on the stream to make it synchronous.
   auto cuStreamSync =
-      getModule().lookupSymbol<LLVM::LLVMFuncOp>(cuStreamSynchronizeName);
+      getOperation().lookupSymbol<LLVM::LLVMFuncOp>(cuStreamSynchronizeName);
   builder.create<LLVM::CallOp>(loc, ArrayRef<Type>{getCUResultType()},
                                builder.getSymbolRefAttr(cuStreamSync),
                                ArrayRef<Value>(cuStream.getResult(0)));
   launchOp.erase();
 }
 
 std::unique_ptr<mlir::OpPassBase<mlir::ModuleOp>>
 mlir::createConvertGpuLaunchFuncToCudaCallsPass() {
   return std::make_unique<GpuLaunchFuncToCudaCallsPass>();
 }

mlir/lib/Conversion/GPUToSPIRV/ConvertGPUToSPIRVPass.cpp

 /// inside gpu.module ops. i.e., the function that are referenced in
 /// gpu.launch_func ops. For each such function
 ///
 /// 1) Create a spirv::ModuleOp, and clone the function into spirv::ModuleOp
 /// (the original function is still needed by the gpu::LaunchKernelOp, so cannot
 /// replace it).
 ///
 /// 2) Lower the body of the spirv::ModuleOp.
-struct GPUToSPIRVPass : public ModulePass<GPUToSPIRVPass> {
+struct GPUToSPIRVPass : public OperationPass<GPUToSPIRVPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertGpuToSPIRV
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void GPUToSPIRVPass::runOnModule() {
+void GPUToSPIRVPass::runOnOperation() {
   MLIRContext *context = &getContext();
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
 
   SmallVector<Operation *, 1> kernelModules;
   OpBuilder builder(context);
   module.walk([&builder, &kernelModules](gpu::GPUModuleOp moduleOp) {
     // For each kernel module (should be only 1 for now, but that is not a
     // requirement here), clone the module for conversion because the
     // gpu.launch function still needs the kernel module.
     builder.setInsertionPoint(moduleOp.getOperation());

mlir/lib/Conversion/GPUToVulkan/ConvertGPULaunchFuncToVulkanLaunchFunc.cpp

 
 namespace {
 
 /// A pass to convert gpu launch op to vulkan launch call op, by creating a
 /// SPIR-V binary shader from `spirv::ModuleOp` using `spirv::serialize`
 /// function and attaching binary data and entry point name as an attributes to
 /// created vulkan launch call op.
 class ConvertGpuLaunchFuncToVulkanLaunchFunc
-    : public ModulePass<ConvertGpuLaunchFuncToVulkanLaunchFunc> {
+    : public OperationPass<ConvertGpuLaunchFuncToVulkanLaunchFunc, ModuleOp> {
 public:
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertGpuLaunchFuncToVulkanLaunchFunc
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 
 private:
   /// Creates a SPIR-V binary shader from the given `module` using
   /// `spirv::serialize` function.
   LogicalResult createBinaryShader(ModuleOp module,
                                    std::vector<char> &binaryShader);
 
   /// Converts the given `launchOp` to vulkan launch call.
   void convertGpuLaunchFunc(gpu::LaunchFuncOp launchOp);
 
   /// Checks where the given type is supported by Vulkan runtime.
   bool isSupportedType(Type type) {
     // TODO(denis0x0D): Handle other types.
     if (auto memRefType = type.dyn_cast_or_null<MemRefType>())
       return memRefType.hasRank() &&
              (memRefType.getRank() >= 1 && memRefType.getRank() <= 3);
     return false;
   }
 
   /// Declares the vulkan launch function. Returns an error if the any type of
   /// operand is unsupported by Vulkan runtime.
   LogicalResult declareVulkanLaunchFunc(Location loc,
                                         gpu::LaunchFuncOp launchOp);
-
 };
 
 } // anonymous namespace
 
-void ConvertGpuLaunchFuncToVulkanLaunchFunc::runOnModule() {
+void ConvertGpuLaunchFuncToVulkanLaunchFunc::runOnOperation() {
   bool done = false;
-  getModule().walk([this, &done](gpu::LaunchFuncOp op) {
+  getOperation().walk([this, &done](gpu::LaunchFuncOp op) {
     if (done) {
       op.emitError("should only contain one 'gpu::LaunchFuncOp' op");
       return signalPassFailure();
     }
     done = true;
     convertGpuLaunchFunc(op);
   });
 
   // Erase `gpu::GPUModuleOp` and `spirv::Module` operations.
   for (auto gpuModule :
-       llvm::make_early_inc_range(getModule().getOps<gpu::GPUModuleOp>()))
+       llvm::make_early_inc_range(getOperation().getOps<gpu::GPUModuleOp>()))
     gpuModule.erase();
 
   for (auto spirvModule :
-       llvm::make_early_inc_range(getModule().getOps<spirv::ModuleOp>()))
+       llvm::make_early_inc_range(getOperation().getOps<spirv::ModuleOp>()))
     spirvModule.erase();
 }
 
 LogicalResult ConvertGpuLaunchFuncToVulkanLaunchFunc::declareVulkanLaunchFunc(
     Location loc, gpu::LaunchFuncOp launchOp) {
-  OpBuilder builder(getModule().getBody()->getTerminator());
+  OpBuilder builder(getOperation().getBody()->getTerminator());
   // TODO: Workgroup size is written into the kernel. So to properly modelling
   // vulkan launch, we cannot have the local workgroup size configuration here.
   SmallVector<Type, 8> vulkanLaunchTypes{launchOp.getOperandTypes()};
 
   // Check that all operands have supported types except those for the launch
   // configuration.
   for (auto type :
        llvm::drop_begin(vulkanLaunchTypes, gpu::LaunchOp::kNumConfigOperands)) {
LogicalResult ConvertGpuLaunchFuncToVulkanLaunchFunc::createBinaryShader(
   binaryShader.resize(binary.size() * sizeof(uint32_t));
   std::memcpy(binaryShader.data(), reinterpret_cast<char *>(binary.data()),
               binaryShader.size());
   return success();
 }
 
 void ConvertGpuLaunchFuncToVulkanLaunchFunc::convertGpuLaunchFunc(
     gpu::LaunchFuncOp launchOp) {
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
   OpBuilder builder(launchOp);
   Location loc = launchOp.getLoc();
 
   // Serialize `spirv::Module` into binary form.
   std::vector<char> binary;
   if (failed(createBinaryShader(module, binary)))
     return signalPassFailure();
 

mlir/lib/Conversion/GPUToVulkan/ConvertLaunchFuncToVulkanCalls.cpp

 /// * bindMemRef           -- binds memref
 /// * setBinaryShader      -- sets the binary shader data
 /// * setEntryPoint        -- sets the entry point name
 /// * setNumWorkGroups     -- sets the number of a local workgroups
 /// * runOnVulkan          -- runs vulkan runtime
 /// * deinitVulkan         -- deinitializes vulkan runtime
 ///
 class VulkanLaunchFuncToVulkanCallsPass
-    : public ModulePass<VulkanLaunchFuncToVulkanCallsPass> {
+    : public OperationPass<VulkanLaunchFuncToVulkanCallsPass, ModuleOp> {
 private:
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertVulkanLaunchFuncToVulkanCalls
 #include "mlir/Conversion/Passes.h.inc"
 
   LLVM::LLVMDialect *getLLVMDialect() { return llvmDialect; }
 
   llvm::LLVMContext &getLLVMContext() {
#include "mlir/Conversion/Passes.h.inc"
 
   /// Collects SPIRV attributes from the given `vulkanLaunchCallOp`.
   void collectSPIRVAttributes(LLVM::CallOp vulkanLaunchCallOp);
 
   /// Deduces a rank from the given 'ptrToMemRefDescriptor`.
   LogicalResult deduceMemRefRank(Value ptrToMemRefDescriptor, uint32_t &rank);
 
 public:
-  void runOnModule() override;
+  void runOnOperation() override;
 
 private:
   LLVM::LLVMDialect *llvmDialect;
   LLVM::LLVMType llvmFloatType;
   LLVM::LLVMType llvmVoidType;
   LLVM::LLVMType llvmPointerType;
   LLVM::LLVMType llvmInt32Type;
   LLVM::LLVMType llvmInt64Type;
   LLVM::LLVMType llvmMemRef1DFloat;
   LLVM::LLVMType llvmMemRef2DFloat;
   LLVM::LLVMType llvmMemRef3DFloat;
 
   // TODO: Use an associative array to support multiple vulkan launch calls.
   std::pair<StringAttr, StringAttr> spirvAttributes;
 };
 
 } // anonymous namespace
 
-void VulkanLaunchFuncToVulkanCallsPass::runOnModule() {
+void VulkanLaunchFuncToVulkanCallsPass::runOnOperation() {
   initializeCachedTypes();
 
   // Collect SPIR-V attributes such as `spirv_blob` and
   // `spirv_entry_point_name`.
-  getModule().walk([this](LLVM::CallOp op) {
+  getOperation().walk([this](LLVM::CallOp op) {
     if (isVulkanLaunchCallOp(op))
       collectSPIRVAttributes(op);
   });
 
   // Convert vulkan launch call op into a sequence of Vulkan runtime calls.
-  getModule().walk([this](LLVM::CallOp op) {
+  getOperation().walk([this](LLVM::CallOp op) {
     if (isCInterfaceVulkanLaunchCallOp(op))
       translateVulkanLaunchCall(op);
   });
 }
 
 void VulkanLaunchFuncToVulkanCallsPass::collectSPIRVAttributes(
     LLVM::CallOp vulkanLaunchCallOp) {
   // Check that `kSPIRVBinary` and `kSPIRVEntryPoint` are present in attributes
if (llvmDescriptorTy.getStructNumElements() == 3) {
     return success();
   }
 
   rank = llvmDescriptorTy.getStructElementType(3).getArrayNumElements();
   return success();
 }
 
 void VulkanLaunchFuncToVulkanCallsPass::declareVulkanFunctions(Location loc) {
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
   OpBuilder builder(module.getBody()->getTerminator());
 
   if (!module.lookupSymbol(kSetEntryPoint)) {
     builder.create<LLVM::LLVMFuncOp>(
         loc, kSetEntryPoint,
         LLVM::LLVMType::getFunctionTy(getVoidType(),
                                       {getPointerType(), getPointerType()},
                                       /*isVarArg=*/false));

mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp

patterns.insert<RangeOpConversion, ReshapeOpConversion, SliceOpConversion,
                   TransposeOpConversion, YieldOpConversion>(ctx, converter);
 
   // Populate the type conversions for the linalg types.
   converter.addConversion(
       [&](RangeType type) { return convertRangeType(type, converter); });
 }
 
 namespace {
-struct ConvertLinalgToLLVMPass : public ModulePass<ConvertLinalgToLLVMPass> {
+struct ConvertLinalgToLLVMPass
+    : public OperationPass<ConvertLinalgToLLVMPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertLinalgToLLVM
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void ConvertLinalgToLLVMPass::runOnModule() {
-  auto module = getModule();
+void ConvertLinalgToLLVMPass::runOnOperation() {
+  auto module = getOperation();
 
   // Convert to the LLVM IR dialect using the converter defined above.
   OwningRewritePatternList patterns;
   LLVMTypeConverter converter(&getContext());
   populateAffineToStdConversionPatterns(patterns, &getContext());
   populateLoopToStdConversionPatterns(patterns, &getContext());
   populateStdToLLVMConversionPatterns(converter, patterns);
   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);

mlir/lib/Conversion/LinalgToSPIRV/LinalgToSPIRVPass.cpp

 #include "mlir/Dialect/SPIRV/SPIRVDialect.h"
 #include "mlir/Dialect/SPIRV/SPIRVLowering.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
 /// A pass converting MLIR Linalg ops into SPIR-V ops.
-class LinalgToSPIRVPass : public ModulePass<LinalgToSPIRVPass> {
+class LinalgToSPIRVPass : public OperationPass<LinalgToSPIRVPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertLinalgToSPIRV
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void LinalgToSPIRVPass::runOnModule() {
+void LinalgToSPIRVPass::runOnOperation() {
   MLIRContext *context = &getContext();
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
 
   auto targetAttr = spirv::lookupTargetEnvOrDefault(module);
   std::unique_ptr<ConversionTarget> target =
       spirv::SPIRVConversionTarget::get(targetAttr);
 
   SPIRVTypeConverter typeConverter(targetAttr);
   OwningRewritePatternList patterns;
   populateLinalgToSPIRVPatterns(context, typeConverter, patterns);

mlir/lib/Conversion/StandardToLLVM/StandardToLLVM.cpp

for (auto it : llvm::zip(opOperands, operands)) {
 
     promotedOperands.push_back(operand);
   }
   return promotedOperands;
 }
 
 namespace {
 /// A pass converting MLIR operations into the LLVM IR dialect.
-struct LLVMLoweringPass : public ModulePass<LLVMLoweringPass> {
+struct LLVMLoweringPass : public OperationPass<LLVMLoweringPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertStandardToLLVM
 #include "mlir/Conversion/Passes.h.inc"
 
   /// Creates an LLVM lowering pass.
   LLVMLoweringPass(bool useBarePtrCallConv, bool emitCWrappers,
                    unsigned indexBitwidth) {
     this->useBarePtrCallConv = useBarePtrCallConv;
     this->emitCWrappers = emitCWrappers;
     this->indexBitwidth = indexBitwidth;
   }
   explicit LLVMLoweringPass() {}
   LLVMLoweringPass(const LLVMLoweringPass &pass) {}
 
   /// Run the dialect converter on the module.
-  void runOnModule() override {
+  void runOnOperation() override {
     if (useBarePtrCallConv && emitCWrappers) {
-      getModule().emitError()
+      getOperation().emitError()
           << "incompatible conversion options: bare-pointer calling convention "
              "and C wrapper emission";
       signalPassFailure();
       return;
     }
 
-    ModuleOp m = getModule();
+    ModuleOp m = getOperation();
 
     LLVMTypeConverterCustomization customs;
     customs.funcArgConverter = useBarePtrCallConv ? barePtrFuncArgTypeConverter
                                                   : structFuncArgTypeConverter;
     customs.indexBitwidth = indexBitwidth;
     LLVMTypeConverter typeConverter(&getContext(), customs);
 
     OwningRewritePatternList patterns;

mlir/lib/Conversion/StandardToSPIRV/ConvertStandardToSPIRVPass.cpp

 #include "mlir/Dialect/SPIRV/SPIRVLowering.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
 /// A pass converting MLIR Standard operations into the SPIR-V dialect.
 class ConvertStandardToSPIRVPass
-    : public ModulePass<ConvertStandardToSPIRVPass> {
+    : public OperationPass<ConvertStandardToSPIRVPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertStandardToSPIRV
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void ConvertStandardToSPIRVPass::runOnModule() {
+void ConvertStandardToSPIRVPass::runOnOperation() {
   MLIRContext *context = &getContext();
-  ModuleOp module = getModule();
+  ModuleOp module = getOperation();
 
   auto targetAttr = spirv::lookupTargetEnvOrDefault(module);
   std::unique_ptr<ConversionTarget> target =
       spirv::SPIRVConversionTarget::get(targetAttr);
 
   SPIRVTypeConverter typeConverter(targetAttr);
   OwningRewritePatternList patterns;
   populateStandardToSPIRVPatterns(context, typeConverter, patterns);

mlir/lib/Conversion/VectorToLLVM/ConvertVectorToLLVM.cpp

 
 void mlir::populateVectorToLLVMMatrixConversionPatterns(
     LLVMTypeConverter &converter, OwningRewritePatternList &patterns) {
   MLIRContext *ctx = converter.getDialect()->getContext();
   patterns.insert<VectorMatmulOpConversion>(ctx, converter);
 }
 
 namespace {
-struct LowerVectorToLLVMPass : public ModulePass<LowerVectorToLLVMPass> {
+struct LowerVectorToLLVMPass
+    : public OperationPass<LowerVectorToLLVMPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_ConvertVectorToLLVM
 #include "mlir/Conversion/Passes.h.inc"
 
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void LowerVectorToLLVMPass::runOnModule() {
+void LowerVectorToLLVMPass::runOnOperation() {
   // Perform progressive lowering of operations on slices and
   // all contraction operations. Also applies folding and DCE.
   {
     OwningRewritePatternList patterns;
     populateVectorSlicesLoweringPatterns(patterns, &getContext());
     populateVectorContractLoweringPatterns(patterns, &getContext());
-    applyPatternsGreedily(getModule(), patterns);
+    applyPatternsGreedily(getOperation(), patterns);
   }
 
   // Convert to the LLVM IR dialect.
   LLVMTypeConverter converter(&getContext());
   OwningRewritePatternList patterns;
   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
   populateVectorToLLVMConversionPatterns(converter, patterns);
   populateVectorToLLVMMatrixConversionPatterns(converter, patterns);
   populateStdToLLVMConversionPatterns(converter, patterns);
 
   LLVMConversionTarget target(getContext());
   target.addDynamicallyLegalOp<FuncOp>(
       [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
-  if (failed(
-          applyPartialConversion(getModule(), target, patterns, &converter))) {
+  if (failed(applyPartialConversion(getOperation(), target, patterns,
+                                    &converter))) {
     signalPassFailure();
   }
 }
 
 std::unique_ptr<OpPassBase<ModuleOp>> mlir::createConvertVectorToLLVMPass() {
   return std::make_unique<LowerVectorToLLVMPass>();
 }

mlir/lib/Dialect/GPU/Transforms/KernelOutlining.cpp

 ///
 /// This pass moves the kernel code of each LaunchOp into a function created
 /// inside a nested module. It also creates an external function of the same
 /// name in the parent module.
 ///
 /// The gpu.modules are intended to be compiled to a cubin blob independently in
 /// a separate pass. The external functions can then be annotated with the
 /// symbol of the cubin accessor function.
-class GpuKernelOutliningPass : public ModulePass<GpuKernelOutliningPass> {
+class GpuKernelOutliningPass
+    : public OperationPass<GpuKernelOutliningPass, ModuleOp> {
 public:
 /// Include the generated pass utilities.
 #define GEN_PASS_GpuKernelOutlining
 #include "mlir/Dialect/GPU/Passes.h.inc"
 
-  void runOnModule() override {
-    SymbolTable symbolTable(getModule());
+  void runOnOperation() override {
+    SymbolTable symbolTable(getOperation());
     bool modified = false;
-    for (auto func : getModule().getOps<FuncOp>()) {
+    for (auto func : getOperation().getOps<FuncOp>()) {
       // Insert just after the function.
       Block::iterator insertPt(func.getOperation()->getNextNode());
       auto funcWalkResult = func.walk([&](gpu::LaunchOp op) {
         llvm::SetVector<Value> operands;
         std::string kernelFnName =
             Twine(op.getParentOfType<FuncOp>().getName(), "_kernel").str();
 
         // Pull in instructions that can be sunk
for (auto func : getOperation().getOps<FuncOp>()) {
       });
       if (funcWalkResult.wasInterrupted())
         return signalPassFailure();
     }
 
     // If any new module was inserted in this module, annotate this module as
     // a container module.
     if (modified)
-      getModule().setAttr(gpu::GPUDialect::getContainerModuleAttrName(),
+      getOperation().setAttr(gpu::GPUDialect::getContainerModuleAttrName(),
                              UnitAttr::get(&getContext()));
   }
 
 private:
   // Returns a gpu.module containing kernelFunc and all callees (recursive).
   gpu::GPUModuleOp createKernelModule(gpu::GPUFuncOp kernelFunc,
                                       const SymbolTable &parentSymbolTable) {
     // TODO: This code cannot use an OpBuilder because it must be inserted into
     // a SymbolTable by the caller. SymbolTable needs to be refactored to
     // prevent manual building of Ops with symbols in code using SymbolTables
     // and then this needs to use the OpBuilder.
-    auto context = getModule().getContext();
+    auto context = getOperation().getContext();
     Builder builder(context);
     OperationState state(kernelFunc.getLoc(),
                          gpu::GPUModuleOp::getOperationName());
     gpu::GPUModuleOp::build(&builder, state, kernelFunc.getName());
     auto kernelModule = cast<gpu::GPUModuleOp>(Operation::create(state));
     SymbolTable symbolTable(kernelModule);
     symbolTable.insert(kernelFunc);
 

mlir/lib/Dialect/SPIRV/Transforms/DecorateSPIRVCompositeTypeLayoutPass.cpp

 static void populateSPIRVLayoutInfoPatterns(OwningRewritePatternList &patterns,
                                             MLIRContext *ctx) {
   patterns.insert<SPIRVGlobalVariableOpLayoutInfoDecoration,
                   SPIRVAddressOfOpLayoutInfoDecoration>(ctx);
 }
 
 namespace {
 class DecorateSPIRVCompositeTypeLayoutPass
-    : public ModulePass<DecorateSPIRVCompositeTypeLayoutPass> {
+    : public OperationPass<DecorateSPIRVCompositeTypeLayoutPass, ModuleOp> {
 private:
-  void runOnModule() override;
+  void runOnOperation() override;
 };
 } // namespace
 
-void DecorateSPIRVCompositeTypeLayoutPass::runOnModule() {
-  auto module = getModule();
+void DecorateSPIRVCompositeTypeLayoutPass::runOnOperation() {
+  auto module = getOperation();
   OwningRewritePatternList patterns;
   populateSPIRVLayoutInfoPatterns(patterns, module.getContext());
   ConversionTarget target(*(module.getContext()));
   target.addLegalDialect<spirv::SPIRVDialect>();
   target.addLegalOp<FuncOp>();
   target.addDynamicallyLegalOp<spirv::GlobalVariableOp>(
       [](spirv::GlobalVariableOp op) {
         return VulkanLayoutUtils::isLegalType(op.type());

mlir/lib/Transforms/OpStats.cpp

 #include "mlir/Transforms/Passes.h"
 #include "llvm/ADT/DenseMap.h"
 #include "llvm/Support/Format.h"
 #include "llvm/Support/raw_ostream.h"
 
 using namespace mlir;
 
 namespace {
-struct PrintOpStatsPass : public ModulePass<PrintOpStatsPass> {
+struct PrintOpStatsPass : public OperationPass<PrintOpStatsPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_PrintOpStats
 #include "mlir/Transforms/Passes.h.inc"
 
   explicit PrintOpStatsPass(raw_ostream &os = llvm::errs()) : os(os) {}
 
   // Prints the resultant operation statistics post iterating over the module.
-  void runOnModule() override;
+  void runOnOperation() override;
 
   // Print summary of op stats.
   void printSummary();
 
 private:
   llvm::StringMap<int64_t> opCount;
   raw_ostream &os;
 };
 } // namespace
 
-void PrintOpStatsPass::runOnModule() {
+void PrintOpStatsPass::runOnOperation() {
   opCount.clear();
 
   // Compute the operation statistics for each function in the module.
-  for (auto &op : getModule())
+  for (auto &op : getOperation())
     op.walk([&](Operation *op) { ++opCount[op->getName().getStringRef()]; });
   printSummary();
 }
 
 void PrintOpStatsPass::printSummary() {
   os << "Operations encountered:\n";
   os << "-----------------------\n";
   SmallVector<StringRef, 64> sorted(opCount.keys());

mlir/lib/Transforms/ViewOpGraph.cpp

 }
 
 } // end namespace llvm
 
 namespace {
 // PrintOpPass is simple pass to write graph per function.
 // Note: this is a module pass only to avoid interleaving on the same ostream
 // due to multi-threading over functions.
-struct PrintOpPass : public ModulePass<PrintOpPass> {
+struct PrintOpPass : public OperationPass<PrintOpPass, ModuleOp> {
 /// Include the generated pass utilities.
 #define GEN_PASS_PrintOpGraph
 #include "mlir/Transforms/Passes.h.inc"
 
   explicit PrintOpPass(raw_ostream &os = llvm::errs(), bool short_names = false,
                        const Twine &title = "")
       : os(os), title(title.str()), short_names(short_names) {}
 
for (Operation &op : module) {
                                : ("__" + llvm::utostr(indexed_block.index()));
           llvm::WriteGraph(os, &indexed_block.value(), short_names,
                            Twine(title) + opName + blockName);
         }
       }
     }
   }
 
-  void runOnModule() override { processModule(getModule()); }
+  void runOnOperation() override { processModule(getOperation()); }
 
 private:
   raw_ostream &os;
   std::string title;
   int unnamedOpCtr = 0;
   bool short_names;
 };
 } // namespace

mlir/test/lib/Dialect/Test/TestPatterns.cpp

struct TestTypeConverter : public TypeConverter {
   Operation *materializeConversion(PatternRewriter &rewriter, Type resultType,
                                    ArrayRef<Value> inputs,
                                    Location loc) override {
     return rewriter.create<TestCastOp>(loc, resultType, inputs);
   }
 };
 
 struct TestLegalizePatternDriver
-    : public ModulePass<TestLegalizePatternDriver> {
+    : public OperationPass<TestLegalizePatternDriver, ModuleOp> {
   /// The mode of conversion to use with the driver.
   enum class ConversionMode { Analysis, Full, Partial };
 
   TestLegalizePatternDriver(ConversionMode mode) : mode(mode) {}
 
-  void runOnModule() override {
+  void runOnOperation() override {
     TestTypeConverter converter;
     mlir::OwningRewritePatternList patterns;
     populateWithGenerated(&getContext(), &patterns);
     patterns.insert<
         TestRegionRewriteBlockMovement, TestRegionRewriteUndo, TestCreateBlock,
         TestCreateIllegalBlock, TestPassthroughInvalidOp, TestSplitReturnType,
         TestChangeProducerTypeI32ToF32, TestChangeProducerTypeF32ToF64,
         TestChangeProducerTypeF32ToInvalid, TestUpdateConsumerType,
void runOnOperation() override {
     // Check support for marking certain operations as recursively legal.
     target.markOpRecursivelyLegal<FuncOp, ModuleOp>([](Operation *op) {
       return static_cast<bool>(
           op->getAttrOfType<UnitAttr>("test.recursively_legal"));
     });
 
     // Handle a partial conversion.
     if (mode == ConversionMode::Partial) {
-      (void)applyPartialConversion(getModule(), target, patterns, &converter);
+      (void)applyPartialConversion(getOperation(), target, patterns,
+                                   &converter);
       return;
     }
 
     // Handle a full conversion.
     if (mode == ConversionMode::Full) {
       // Check support for marking unknown operations as dynamically legal.
       target.markUnknownOpDynamicallyLegal([](Operation *op) {
         return (bool)op->getAttrOfType<UnitAttr>("test.dynamically_legal");
       });
 
-      (void)applyFullConversion(getModule(), target, patterns, &converter);
+      (void)applyFullConversion(getOperation(), target, patterns, &converter);
       return;
     }
 
     // Otherwise, handle an analysis conversion.
     assert(mode == ConversionMode::Analysis);
 
     // Analyze the convertible operations.
     DenseSet<Operation *> legalizedOps;
-    if (failed(applyAnalysisConversion(getModule(), target, patterns,
+    if (failed(applyAnalysisConversion(getOperation(), target, patterns,
                                        legalizedOps, &converter)))
       return signalPassFailure();
 
     // Emit remarks for each legalizable operation.
     for (auto *op : legalizedOps)
       op->emitRemark() << "op '" << op->getName() << "' is legalizable";
   }
 

mlir/test/lib/IR/TestFunc.cpp

 //===- TestFunctionLike.cpp - Pass to test helpers on FunctionLike --------===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 
 #include "mlir/IR/Function.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
 /// This is a test pass for verifying FuncOp's eraseArgument method.
-struct TestFuncEraseArg : public ModulePass<TestFuncEraseArg> {
-  void runOnModule() override {
-    auto module = getModule();
+struct TestFuncEraseArg : public OperationPass<TestFuncEraseArg, ModuleOp> {
+  void runOnOperation() override {
+    auto module = getOperation();
 
     for (FuncOp func : module.getOps<FuncOp>()) {
       SmallVector<unsigned, 4> indicesToErase;
       for (auto argIndex : llvm::seq<int>(0, func.getNumArguments())) {
         if (func.getArgAttr(argIndex, "test.erase_this_arg")) {
           // Push back twice to test that duplicate arg indices are handled
           // correctly.
           indicesToErase.push_back(argIndex);
           indicesToErase.push_back(argIndex);
         }
       }
       // Reverse the order to test that unsorted index lists are handled
       // correctly.
       std::reverse(indicesToErase.begin(), indicesToErase.end());
       func.eraseArguments(indicesToErase);
     }
   }
 };
 
 /// This is a test pass for verifying FuncOp's setType method.
-struct TestFuncSetType : public ModulePass<TestFuncSetType> {
-  void runOnModule() override {
-    auto module = getModule();
+struct TestFuncSetType : public OperationPass<TestFuncSetType, ModuleOp> {
+  void runOnOperation() override {
+    auto module = getOperation();
     SymbolTable symbolTable(module);
 
     for (FuncOp func : module.getOps<FuncOp>()) {
       auto sym = func.getAttrOfType<FlatSymbolRefAttr>("test.set_type_from");
       if (!sym)
         continue;
       func.setType(symbolTable.lookup<FuncOp>(sym.getValue()).getType());
     }

mlir/test/lib/IR/TestSideEffects.cpp

 //===- TestSidEffects.cpp - Pass to test side effects ---------------------===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 
 #include "TestDialect.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
-struct SideEffectsPass : public ModulePass<SideEffectsPass> {
-  void runOnModule() override {
-    auto module = getModule();
+struct SideEffectsPass : public OperationPass<SideEffectsPass, ModuleOp> {
+  void runOnOperation() override {
+    auto module = getOperation();
 
     // Walk operations detecting side effects.
     SmallVector<MemoryEffects::EffectInstance, 8> effects;
     module.walk([&](MemoryEffectOpInterface op) {
       effects.clear();
       op.getEffects(effects);
 
       // Check to see if this operation has any memory effects.

mlir/test/lib/IR/TestSymbolUses.cpp

 #include "mlir/IR/Function.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
 /// This is a symbol test pass that tests the symbol uselist functionality
 /// provided by the symbol table along with erasing from the symbol table.
-struct SymbolUsesPass : public ModulePass<SymbolUsesPass> {
+struct SymbolUsesPass : public OperationPass<SymbolUsesPass, ModuleOp> {
   WalkResult operateOnSymbol(Operation *symbol, ModuleOp module,
                              SmallVectorImpl<FuncOp> &deadFunctions) {
     // Test computing uses on a non symboltable op.
     Optional<SymbolTable::UseRange> symbolUses =
         SymbolTable::getSymbolUses(symbol);
 
     // Test the conservative failure case.
     if (!symbolUses) {
for (SymbolTable::SymbolUse symbolUse : *symbolUses) {
             << "found use of symbol : " << symbolUse.getSymbolRef() << " : "
             << symbol->getAttr(SymbolTable::getSymbolAttrName());
       }
     }
     symbol->emitRemark() << "symbol has " << llvm::size(*symbolUses) << " uses";
     return WalkResult::advance();
   }
 
-  void runOnModule() override {
-    auto module = getModule();
+  void runOnOperation() override {
+    auto module = getOperation();
 
     // Walk nested symbols.
     SmallVector<FuncOp, 4> deadFunctions;
     module.getBodyRegion().walk([&](Operation *nestedOp) {
       if (SymbolTable::isSymbol(nestedOp))
         return operateOnSymbol(nestedOp, module, deadFunctions);
       return WalkResult::advance();
     });
for (Operation *op : deadFunctions) {
              "expected erased operation to be unknown now");
       module.emitRemark() << name << " function successfully erased";
     }
   }
 };
 
 /// This is a symbol test pass that tests the symbol use replacement
 /// functionality provided by the symbol table.
-struct SymbolReplacementPass : public ModulePass<SymbolReplacementPass> {
-  void runOnModule() override {
-    auto module = getModule();
+struct SymbolReplacementPass
+    : public OperationPass<SymbolReplacementPass, ModuleOp> {
+  void runOnOperation() override {
+    auto module = getOperation();
 
     // Walk nested functions and modules.
     module.getBodyRegion().walk([&](Operation *nestedOp) {
       StringAttr newName = nestedOp->getAttrOfType<StringAttr>("sym.new_name");
       if (!newName)
         return;
       if (succeeded(SymbolTable::replaceAllSymbolUses(
               nestedOp, newName.getValue(), &module.getBodyRegion())))

mlir/test/lib/Pass/TestPassManager.cpp

 //===- TestPassManager.cpp - Test pass manager functionality --------------===//
 //
 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 //
 //===----------------------------------------------------------------------===//
 
 #include "mlir/IR/Function.h"
 #include "mlir/Pass/Pass.h"
 #include "mlir/Pass/PassManager.h"
 
 using namespace mlir;
 
 namespace {
-struct TestModulePass : public ModulePass<TestModulePass> {
-  void runOnModule() final {}
+struct TestModulePass : public OperationPass<TestModulePass, ModuleOp> {
+  void runOnOperation() final {}
 };
 struct TestFunctionPass : public FunctionPass<TestFunctionPass> {
   void runOnFunction() final {}
 };
 class TestOptionsPass : public FunctionPass<TestOptionsPass> {
 public:
   struct Options : public PassPipelineOptions<Options> {
     ListOption<int> listOption{*this, "list",

mlir/test/lib/Transforms/TestAllReduceLowering.cpp

 #include "mlir/Dialect/GPU/Passes.h"
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
 struct TestAllReduceLoweringPass
-    : public ModulePass<TestAllReduceLoweringPass> {
-  void runOnModule() override {
+    : public OperationPass<TestAllReduceLoweringPass, ModuleOp> {
+  void runOnOperation() override {
     OwningRewritePatternList patterns;
     populateGpuRewritePatterns(&getContext(), patterns);
-    applyPatternsGreedily(getModule(), patterns);
+    applyPatternsGreedily(getOperation(), patterns);
   }
 };
 } // namespace
 
 namespace mlir {
 void registerTestAllReduceLoweringPass() {
   PassRegistration<TestAllReduceLoweringPass> pass(
       "test-all-reduce-lowering",
       "Lowers gpu.all-reduce ops within the GPU dialect.");
 }
 } // namespace mlir

mlir/test/lib/Transforms/TestCallGraph.cpp

 //===----------------------------------------------------------------------===//
 
 #include "mlir/Analysis/CallGraph.h"
 #include "mlir/Pass/Pass.h"
 
 using namespace mlir;
 
 namespace {
-struct TestCallGraphPass : public ModulePass<TestCallGraphPass> {
-  void runOnModule() {
-    llvm::errs() << "Testing : " << getModule().getAttr("test.name") << "\n";
+struct TestCallGraphPass : public OperationPass<TestCallGraphPass, ModuleOp> {
+  void runOnOperation() override {
+    llvm::errs() << "Testing : " << getOperation().getAttr("test.name") << "\n";
     getAnalysis<CallGraph>().print(llvm::errs());
   }
 };
 } // end anonymous namespace
 
 namespace mlir {
 void registerTestCallGraphPass() {
   PassRegistration<TestCallGraphPass> pass(
       "test-print-callgraph", "Print the contents of a constructed callgraph.");
 }
 } // namespace mlir

mlir/test/lib/Transforms/TestOpaqueLoc.cpp

 
 using namespace mlir;
 
 namespace {
 /// Pass that changes locations to opaque locations for each operation.
 /// It also takes all operations that are not function operations or
 /// terminators and clones them with opaque locations which store the initial
 /// locations.
-struct TestOpaqueLoc : public ModulePass<TestOpaqueLoc> {
+struct TestOpaqueLoc : public OperationPass<TestOpaqueLoc, ModuleOp> {
 
   /// A simple structure which is used for testing as an underlying location in
   /// OpaqueLoc.
   struct MyLocation {
     MyLocation() : id(42) {}
     MyLocation(int id) : id(id) {}
     int getId() { return id; }
 
     int id;
   };
 
-  void runOnModule() override {
+  void runOnOperation() override {
     std::vector<std::unique_ptr<MyLocation>> myLocs;
     int last_it = 0;
 
-    getModule().walk([&](Operation *op) {
+    getOperation().walk([&](Operation *op) {
       myLocs.push_back(std::make_unique<MyLocation>(last_it++));
 
       Location loc = op->getLoc();
 
       /// Set opaque location without fallback location to test the
       /// corresponding get method.
       op->setLoc(
           OpaqueLoc::get<MyLocation *>(myLocs.back().get(), &getContext()));
ScopedDiagnosticHandler diagHandler(&getContext(), [](Diagnostic &diag) {
           os << "MyLocation: " << loc->id;
         else
           os << "nullptr";
       }
       os << ": " << diag << '\n';
       os.flush();
     });
 
-    getModule().walk([&](Operation *op) { op->emitOpError(); });
+    getOperation().walk([&](Operation *op) { op->emitOpError(); });
   }
 };
 
 } // end anonymous namespace
 
 namespace mlir {
 void registerTestOpaqueLoc() {
   PassRegistration<TestOpaqueLoc> pass(
       "test-opaque-loc", "Changes all leaf locations to opaque locations");
 }
 } // namespace mlir