[mlir][linalg] Convert tensor.generate to destination style

This can be a pre-processing for bufferization and allows for more efficient lowerings without an alloc.

Differential Revision: https://reviews.llvm.org/D142205

1 files changed, 78 insertions, 0 deletions

diff --git a/mlir/lib/Dialect/Linalg/Transforms/ConvertToDestinationStyle.cpp b/mlir/lib/Dialect/Linalg/Transforms/ConvertToDestinationStyle.cpp
new file mode 100644
index 000000000000..859657cbfaec
--- /dev/null
+++ b/mlir/lib/Dialect/Linalg/Transforms/ConvertToDestinationStyle.cpp
@@ -0,0 +1,78 @@
+//===- ConvertToDestinationStyle.cpp - Convert non-DPS to DPS 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
+//
+//===----------------------------------------------------------------------===//
+//
+// This file contains patterns to convert non-DPS ops to DPS ops. New
+// tensor.empty ops are inserted as a destination. Such tensor.empty can be
+// eliminated with "empty tensor elimination", allowing them to bufferize
+// without an allocation (assuming there are no further conflicts).
+//
+//===----------------------------------------------------------------------===//
+//
+#include "mlir/Dialect/Arith/IR/Arith.h"
+#include "mlir/Dialect/Linalg/IR/Linalg.h"
+#include "mlir/Dialect/Linalg/Transforms/Transforms.h"
+#include "mlir/Dialect/Tensor/IR/Tensor.h"
+#include "mlir/IR/PatternMatch.h"
+#include "llvm/Support/Debug.h"
+
+using namespace mlir;
+using namespace mlir::tensor;
+
+namespace {
+
+/// Lower tensor.generate to linalg.generic.
+struct GenerateOpConverter : public OpRewritePattern<GenerateOp> {
+  using OpRewritePattern<GenerateOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(GenerateOp generateOp,
+                                PatternRewriter &rewriter) const override {
+    // Only ops with exactly one block are supported.
+    if (!generateOp.getBody().hasOneBlock())
+      return failure();
+
+    Location loc = generateOp.getLoc();
+    RankedTensorType tensorType = generateOp.getType().cast<RankedTensorType>();
+
+    // Create tensor.empty.
+    auto emptyOp = rewriter.create<EmptyOp>(loc, tensorType,
+                                            generateOp.getDynamicExtents());
+
+    // Create linalg.generic.
+    SmallVector<utils::IteratorType> iteratorTypes(
+        tensorType.getRank(), utils::IteratorType::parallel);
+    SmallVector<AffineMap> indexingMaps(
+        1, rewriter.getMultiDimIdentityMap(tensorType.getRank()));
+    auto genericOp = rewriter.create<linalg::GenericOp>(
+        loc, tensorType, /*inputs=*/ValueRange(),
+        /*outputs=*/ValueRange{emptyOp.getResult()}, /*indexingMaps=*/
+        indexingMaps, iteratorTypes);
+    Block *body = rewriter.createBlock(&genericOp->getRegion(0), {},
+                                       tensorType.getElementType(), loc);
+    rewriter.setInsertionPointToStart(body);
+    SmallVector<Value> bbArgReplacements;
+    for (int64_t i = 0; i < tensorType.getRank(); ++i)
+      bbArgReplacements.push_back(rewriter.create<linalg::IndexOp>(loc, i));
+    rewriter.mergeBlocks(&generateOp.getBody().front(), body,
+                         bbArgReplacements);
+
+    // Update terminator.
+    auto yieldOp = cast<tensor::YieldOp>(body->getTerminator());
+    rewriter.replaceOpWithNewOp<linalg::YieldOp>(yieldOp, yieldOp.getValue());
+
+    // Replace tensor.generate.
+    rewriter.replaceOp(generateOp, genericOp->getResult(0));
+    return success();
+  }
+};
+
+} // namespace
+
+void linalg::populateConvertToDestinationStylePatterns(
+    RewritePatternSet &patterns) {
+  patterns.insert<GenerateOpConverter>(patterns.getContext());
+}