[mlir][Linalg] Small refactoring of ConvOpVectorization

[limo1996]

Summary

This commit addresses comments that were requested on D86619
after it was landed.

[limo1996]

synced

mlir/include/mlir/Dialect/Linalg/Transforms/Transforms.h

 ///   iterator_types = ["reduction", "reduction", "reduction"]} %0, %1,
 ///   %c0_f32 : vector<3x3x3xf32>, vector<3x3x3xf32> into f32
 /// store %2, %arg2[%c0, %c0, %c0, %c0] : memref<?x?x?x?xf32>
 /// ```
 /// where first 2 operations read input and kernel memory buffers into vectors.
 /// Subsequently, they are contracted together and the result is written to
 /// the first entry of the output buffer.
 template <typename ConvOp, int N>
-struct ConvOpVectorization : public OpRewritePattern<ConvOp> {
+class ConvOpVectorization : public OpRewritePattern<ConvOp> {
   using OpRewritePattern<ConvOp>::OpRewritePattern;
   SmallVector<bool, 4> mask;
 
+public:
   ConvOpVectorization(MLIRContext *context, SmallVector<bool, 4> msk)
       : OpRewritePattern<ConvOp>(context) {
     assert(msk.size() == N && "Mask size does not match rank");
     this->mask = msk;
   }
 
   LogicalResult matchAndRewrite(ConvOp minOp,
                                 PatternRewriter &rewriter) const override;

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

LogicalResult LinalgCopyVTWForwardingPattern::matchAndRewrite(
   rewriter.eraseOp(xferOp);
 
   return success();
 }
 
 template <class ConvOp, int N>
 LogicalResult ConvOpVectorization<ConvOp, N>::matchAndRewrite(
     ConvOp op, PatternRewriter &rewriter) const {
-  const unsigned dimSize = 3;
+  unsigned dimSize = 3;
   Location loc = op.getLoc();
   MLIRContext *context = op.getContext();
   edsc::ScopedContext scope(rewriter, loc);
 
   ShapedType inShapeType = op.getInputShapedType(0);
   ShapedType kShapeType = op.getInputShapedType(1);
 
   ArrayRef<int64_t> inShape = inShapeType.getShape();