[mlir][Linalg] NFC - Cleanup Linalg Pass locations and namespacing

[nicolasvasilache]

Summary

This diff moves the conversion pass declaration closer to its definition
and makes the namespacing of passes consistent with the rest of the
infrastructure (i.e. mlir::linalg::createXXXPass -> mlir::createXXXPass).

[merge_guards_bot]

Unit tests: pass. 61804 tests passed, 0 failed and 781 were skipped.

clang-tidy: unknown.

clang-format: fail. Please format your changes with clang-format by running git-clang-format HEAD^ or applying this patch.

Build artifacts: diff.json, clang-format.patch, CMakeCache.txt, console-log.txt, test-results.xml

[nicolasvasilache]

clang-format

[merge_guards_bot]

Unit tests: pass. 61892 tests passed, 0 failed and 782 were skipped.

clang-tidy: unknown.

clang-format: pass.

Build artifacts: diff.json, clang-format.patch, CMakeCache.txt, console-log.txt, test-results.xml

mlir/include/mlir/Conversion/LinalgToLLVM/LinalgToLLVM.h

 //===- LinalgToLLVM.h - Utils to convert from the linalg dialect ----------===//
 //
 // Part of the MLIR 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
 //
 //===----------------------------------------------------------------------===//
 #ifndef MLIR_CONVERSION_LINALGTOLLVM_LINALGTOLLVM_H_
 #define MLIR_CONVERSION_LINALGTOLLVM_LINALGTOLLVM_H_
 
 #include "mlir/Conversion/StandardToLLVM/ConvertStandardToLLVM.h"
 #include "mlir/Transforms/DialectConversion.h"
 
 namespace mlir {
 class MLIRContext;
+class ModuleOp;
+template <typename T>
+class OpPassBase;
 
 class LinalgTypeConverter : public LLVMTypeConverter {
 public:
   using LLVMTypeConverter::LLVMTypeConverter;
   Type convertType(Type t) override;
 };
 
 /// Populate the given list with patterns that convert from Linalg to LLVM.
 void populateLinalgToLLVMConversionPatterns(LinalgTypeConverter &converter,
                                             OwningRewritePatternList &patterns,
                                             MLIRContext *ctx);
 
+/// Create a pass to convert Linalg operations to the LLVMIR dialect.
+std::unique_ptr<OpPassBase<ModuleOp>> createConvertLinalgToLLVMPass();
+
 } // namespace mlir
 
 #endif // MLIR_CONVERSION_LINALGTOLLVM_LINALGTOLLVM_H_

mlir/include/mlir/Dialect/Linalg/Passes.h

 #include "mlir/Support/LLVM.h"
 #include "llvm/ADT/ArrayRef.h"
 
 namespace mlir {
 class FuncOp;
 class ModuleOp;
 template <typename T> class OpPassBase;
 
-namespace linalg {
 std::unique_ptr<OpPassBase<FuncOp>> createLinalgFusionPass();
 
 std::unique_ptr<OpPassBase<FuncOp>>
 createLinalgTilingPass(ArrayRef<int64_t> tileSizes = {});
 
 std::unique_ptr<OpPassBase<FuncOp>>
 createLinalgPromotionPass(bool dynamicBuffers);
 
 /// Create a pass to convert Linalg operations to loop.for loops and
 /// std.load/std.store accesses.
 std::unique_ptr<OpPassBase<FuncOp>> createConvertLinalgToLoopsPass();
 
 /// Create a pass to convert Linalg operations to affine.for loops and
 /// affine_load/affine_store accesses.
 /// Placeholder for now, this is NYI.
 std::unique_ptr<OpPassBase<FuncOp>> createConvertLinalgToAffineLoopsPass();
 
-/// Create a pass to convert Linalg operations to the LLVMIR dialect.
-std::unique_ptr<OpPassBase<ModuleOp>> createConvertLinalgToLLVMPass();
-
-} // namespace linalg
 } // namespace mlir
 
 #endif // MLIR_DIALECT_LINALG_PASSES_H_

mlir/lib/Conversion/LinalgToLLVM/LinalgToLLVM.cpp

void ConvertLinalgToLLVMPass::runOnModule() {
   target.addLegalDialect<LLVM::LLVMDialect>();
   target.addDynamicallyLegalOp<FuncOp>(
       [&](FuncOp op) { return converter.isSignatureLegal(op.getType()); });
   target.addLegalOp<ModuleOp, ModuleTerminatorOp>();
   if (failed(applyFullConversion(module, target, patterns, &converter)))
     signalPassFailure();
 }
 
-std::unique_ptr<OpPassBase<ModuleOp>>
-mlir::linalg::createConvertLinalgToLLVMPass() {
+std::unique_ptr<OpPassBase<ModuleOp>> mlir::createConvertLinalgToLLVMPass() {
   return std::make_unique<ConvertLinalgToLLVMPass>();
 }
 
 static PassRegistration<ConvertLinalgToLLVMPass> pass(
     "convert-linalg-to-llvm",
     "Convert the operations from the linalg dialect into the LLVM dialect");

mlir/lib/Dialect/Linalg/Transforms/Fusion.cpp

 }
 
 namespace {
 struct LinalgFusionPass : public FunctionPass<LinalgFusionPass> {
   void runOnFunction() override { fuseLinalgOpsGreedily(getFunction()); }
 };
 } // namespace
 
-std::unique_ptr<OpPassBase<FuncOp>> mlir::linalg::createLinalgFusionPass() {
+std::unique_ptr<OpPassBase<FuncOp>> mlir::createLinalgFusionPass() {
   return std::make_unique<LinalgFusionPass>();
 }
 
 static PassRegistration<LinalgFusionPass>
     pass("linalg-fusion", "Fuse operations in the linalg dialect");

mlir/lib/Dialect/Linalg/Transforms/LinalgToLoops.cpp

void LowerLinalgToLoopsPass<LoopType, IndexedValueType>::runOnFunction() {
   AffineApplyOp::getCanonicalizationPatterns(patterns, context);
   patterns.insert<FoldAffineOp>(context);
   // Just apply the patterns greedily.
   applyPatternsGreedily(this->getFunction(), patterns);
 }
 
 /// Create a pass to convert Linalg operations to loop.for loops and
 /// std.load/std.store accesses.
-std::unique_ptr<OpPassBase<FuncOp>>
-mlir::linalg::createConvertLinalgToLoopsPass() {
+std::unique_ptr<OpPassBase<FuncOp>> mlir::createConvertLinalgToLoopsPass() {
   return std::make_unique<
       LowerLinalgToLoopsPass<loop::ForOp, IndexedStdValue>>();
 }
 
 /// Create a pass to convert Linalg operations to affine.for loops and
 /// affine_load/affine_store accesses.
 /// Placeholder for now, this is NYI.
 std::unique_ptr<OpPassBase<FuncOp>>
-mlir::linalg::createConvertLinalgToAffineLoopsPass() {
+mlir::createConvertLinalgToAffineLoopsPass() {
   return std::make_unique<
       LowerLinalgToLoopsPass<AffineForOp, IndexedAffineValue>>();
 }
 
 // Emits a loop nest of `loop.for` with the proper body for `op`.
 template <typename ConcreteOp>
 LogicalResult mlir::linalg::linalgOpToLoops(PatternRewriter &rewriter,
                                             Operation *op) {

mlir/lib/Dialect/Linalg/Transforms/Promotion.cpp

void runOnFunction() override {
     promoteSubViews(getFunction(), dynamicBuffers);
   }
 
   bool dynamicBuffers;
 };
 } // namespace
 
 std::unique_ptr<OpPassBase<FuncOp>>
-mlir::linalg::createLinalgPromotionPass(bool dynamicBuffers) {
+mlir::createLinalgPromotionPass(bool dynamicBuffers) {
   return std::make_unique<LinalgPromotionPass>(dynamicBuffers);
 }
 
 static PassRegistration<LinalgPromotionPass>
     pass("linalg-promote-subviews", "promote subview ops to local buffers", [] {
       return std::make_unique<LinalgPromotionPass>(clPromoteDynamic);
     });

mlir/lib/Dialect/Linalg/Transforms/Tiling.cpp

 };
 } // namespace
 
 LinalgTilingPass::LinalgTilingPass(ArrayRef<int64_t> sizes) {
   this->tileSizes.assign(sizes.begin(), sizes.end());
 }
 
 std::unique_ptr<OpPassBase<FuncOp>>
-mlir::linalg::createLinalgTilingPass(ArrayRef<int64_t> tileSizes) {
+mlir::createLinalgTilingPass(ArrayRef<int64_t> tileSizes) {
   return std::make_unique<LinalgTilingPass>(tileSizes);
 }
 
 static PassRegistration<LinalgTilingPass>
     pass("linalg-tile", "Tile operations in the linalg dialect", [] {
       auto pass = std::make_unique<LinalgTilingPass>();
       pass->tileSizes.assign(clTileSizes.begin(), clTileSizes.end());
       return pass;
     });