[Mlir-commits] [mlir] 8199a43 - [mlir][Affine] Add pass options to supervectorizer

[Javier Setoain]

Author: Javier Setoain
Date: 2022-10-03T10:50:31+01:00
New Revision: 8199a43a8995d23f8ea95fd97b896d93370b8140

URL: https://github.com/llvm/llvm-project/commit/8199a43a8995d23f8ea95fd97b896d93370b8140
DIFF: https://github.com/llvm/llvm-project/commit/8199a43a8995d23f8ea95fd97b896d93370b8140.diff

LOG: [mlir][Affine] Add pass options to supervectorizer

The only current options to create a supervectorization pass from an
external dialect is to use `createSuperVectorizePass` with the virtual
vector dimensions as a parameter, but the pass accepts other parameters.

This patch enables external users to create a supervectorizer pass
exposing all available option.

Differential Revision: https://reviews.llvm.org/D134632

Added: 
    

Modified: 
    mlir/include/mlir/Dialect/Affine/Passes.h
    mlir/include/mlir/Dialect/Affine/Passes.td
    mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp

Removed: 
    


################################################################################
diff  --git a/mlir/include/mlir/Dialect/Affine/Passes.h b/mlir/include/mlir/Dialect/Affine/Passes.h
index e4601ed4a468c..8cc6f8c277d88 100644
--- a/mlir/include/mlir/Dialect/Affine/Passes.h
+++ b/mlir/include/mlir/Dialect/Affine/Passes.h
@@ -106,13 +106,6 @@ createLoopUnrollAndJamPass(int unrollJamFactor = -1);
 /// memory hierarchy.
 std::unique_ptr<OperationPass<func::FuncOp>> createPipelineDataTransferPass();
 
-/// Creates a pass to vectorize loops, operations and data types using a
-/// target-independent, n-D super-vector abstraction.
-std::unique_ptr<OperationPass<func::FuncOp>>
-createSuperVectorizePass(ArrayRef<int64_t> virtualVectorSize);
-/// Overload relying on pass options for initialization.
-std::unique_ptr<OperationPass<func::FuncOp>> createSuperVectorizePass();
-
 /// Populate patterns that expand affine index operations into more fundamental
 /// operations (not necessarily restricted to Affine dialect).
 void populateAffineExpandIndexOpsPatterns(RewritePatternSet &patterns);

diff  --git a/mlir/include/mlir/Dialect/Affine/Passes.td b/mlir/include/mlir/Dialect/Affine/Passes.td
index 63dc795293bde..2faa3b9dc44dd 100644
--- a/mlir/include/mlir/Dialect/Affine/Passes.td
+++ b/mlir/include/mlir/Dialect/Affine/Passes.td
@@ -344,7 +344,6 @@ def AffineScalarReplacement : Pass<"affine-scalrep", "func::FuncOp"> {
 
 def AffineVectorize : Pass<"affine-super-vectorize", "func::FuncOp"> {
   let summary = "Vectorize to a target independent n-D vector abstraction";
-  let constructor = "mlir::createSuperVectorizePass()";
   let dependentDialects = ["vector::VectorDialect"];
   let options = [
     ListOption<"vectorSizes", "virtual-vector-size", "int64_t",

diff  --git a/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp b/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
index e490b8c94a695..c8f465331baa9 100644
--- a/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
+++ b/mlir/lib/Dialect/Affine/Transforms/SuperVectorize.cpp
@@ -616,17 +616,13 @@ namespace {
 /// Base state for the vectorize pass.
 /// Command line arguments are preempted by non-empty pass arguments.
 struct Vectorize : public impl::AffineVectorizeBase<Vectorize> {
-  Vectorize() = default;
-  Vectorize(ArrayRef<int64_t> virtualVectorSize);
+  using Base::Base;
+
   void runOnOperation() override;
 };
 
 } // namespace
 
-Vectorize::Vectorize(ArrayRef<int64_t> virtualVectorSize) {
-  vectorSizes = virtualVectorSize;
-}
-
 static void vectorizeLoopIfProfitable(Operation *loop, unsigned depthInPattern,
                                       unsigned patternDepth,
                                       VectorizationStrategy *strategy) {
@@ -1717,14 +1713,6 @@ static void vectorizeLoops(Operation *parentOp, DenseSet<Operation *> &loops,
   LLVM_DEBUG(dbgs() << "\n");
 }
 
-std::unique_ptr<OperationPass<func::FuncOp>>
-createSuperVectorizePass(ArrayRef<int64_t> virtualVectorSize) {
-  return std::make_unique<Vectorize>(virtualVectorSize);
-}
-std::unique_ptr<OperationPass<func::FuncOp>> createSuperVectorizePass() {
-  return std::make_unique<Vectorize>();
-}
-
 /// Applies vectorization to the current function by searching over a bunch of
 /// predetermined patterns.
 void Vectorize::runOnOperation() {
@@ -1872,12 +1860,4 @@ vectorizeAffineLoopNest(std::vector<SmallVector<AffineForOp, 2>> &loops,
   return vectorizeLoopNest(loops, strategy);
 }
 
-std::unique_ptr<OperationPass<func::FuncOp>>
-createSuperVectorizePass(ArrayRef<int64_t> virtualVectorSize) {
-  return std::make_unique<Vectorize>(virtualVectorSize);
-}
-std::unique_ptr<OperationPass<func::FuncOp>> createSuperVectorizePass() {
-  return std::make_unique<Vectorize>();
-}
-
 } // namespace mlir