mlir/lib/Dialect/Utils/StructuredOpsUtils.cpp

//===- StructuredOpsUtils.cpp - Utilities used by structured ops ----------===//
//
// 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/Dialect/Utils/StructuredOpsUtils.h"
#include "mlir/IR/AffineMap.h"
#include "mlir/IR/BuiltinAttributes.h"

using namespace mlir;

bool mlir::isRowMajorMatmul(ArrayAttr indexingMaps) {
  if (indexingMaps.size() != 3)
    return false;

  auto map0 = indexingMaps[0].cast<AffineMapAttr>().getValue();
  auto map1 = indexingMaps[1].cast<AffineMapAttr>().getValue();
  auto map2 = indexingMaps[2].cast<AffineMapAttr>().getValue();

  if (map0.getNumResults() != 2 || map1.getNumResults() != 2 ||
      map2.getNumResults() != 2 || map0.getNumInputs() != 3 ||
      map1.getNumInputs() != 3 || map2.getNumInputs() != 3) {
    return false;
  }

  // Extract dimensions for MxK * KxN -> MxN
  AffineExpr m = map2.getResult(0);
  AffineExpr n = map2.getResult(1);
  AffineExpr k = map0.getResult(1);
  auto *context = indexingMaps.getContext();
  auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {m, k}, context));
  auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {k, n}, context));
  auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {m, n}, context));
  auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
  return indexingMaps == maps;
}

bool mlir::isColumnMajorMatmul(ArrayAttr indexingMaps) {
  if (indexingMaps.size() != 3)
    return false;

  auto map0 = indexingMaps[0].cast<AffineMapAttr>().getValue();
  auto map1 = indexingMaps[1].cast<AffineMapAttr>().getValue();
  auto map2 = indexingMaps[2].cast<AffineMapAttr>().getValue();

  if (map0.getNumResults() != 2 || map1.getNumResults() != 2 ||
      map2.getNumResults() != 2 || map0.getNumInputs() != 3 ||
      map1.getNumInputs() != 3 || map2.getNumInputs() != 3) {
    return false;
  }

  // Extract dimensions for KxM * NxK -> NxM
  AffineExpr n = map2.getResult(0);
  AffineExpr m = map2.getResult(1);
  AffineExpr k = map0.getResult(0);
  auto *context = indexingMaps.getContext();
  auto mapA = AffineMapAttr::get(AffineMap::get(3, 0, {k, m}, context));
  auto mapB = AffineMapAttr::get(AffineMap::get(3, 0, {n, k}, context));
  auto mapC = AffineMapAttr::get(AffineMap::get(3, 0, {n, m}, context));
  auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
  return indexingMaps == maps;
}

bool mlir::isRowMajorBatchMatmul(ArrayAttr indexingMaps) {
  if (indexingMaps.size() != 3)
    return false;

  auto map0 = indexingMaps[0].cast<AffineMapAttr>().getValue();
  auto map1 = indexingMaps[1].cast<AffineMapAttr>().getValue();
  auto map2 = indexingMaps[2].cast<AffineMapAttr>().getValue();

  if (map0.getNumResults() != 3 || map1.getNumResults() != 3 ||
      map2.getNumResults() != 3 || map0.getNumInputs() != 4 ||
      map1.getNumInputs() != 4 || map2.getNumInputs() != 4) {
    return false;
  }

  // Extract dimensions for BxMxK * BxKxN -> BxMxN
  AffineExpr b = map2.getResult(0);
  AffineExpr m = map2.getResult(1);
  AffineExpr n = map2.getResult(2);
  AffineExpr k = map0.getResult(2);
  auto *context = indexingMaps.getContext();
  auto mapA = AffineMapAttr::get(AffineMap::get(4, 0, {b, m, k}, context));
  auto mapB = AffineMapAttr::get(AffineMap::get(4, 0, {b, k, n}, context));
  auto mapC = AffineMapAttr::get(AffineMap::get(4, 0, {b, m, n}, context));
  auto maps = ArrayAttr::get(context, {mapA, mapB, mapC});
  return indexingMaps == maps;
}