[Mlir-commits] [mlir] [mlir][linalg] Add folder for transpose(transpose) -> transpose (PR #93606)
Ryan Holt
llvmlistbot at llvm.org
Tue May 28 13:05:05 PDT 2024
https://github.com/ryan-holt-1 created https://github.com/llvm/llvm-project/pull/93606
Back to back `linalg.transpose` can be rewritten to a single transpose
>From 561e76d1fe9f21c095f2e33e67c98e7a911e5fe3 Mon Sep 17 00:00:00 2001
From: ryan-holt-1 <ryanholt at mathworks.com>
Date: Tue, 28 May 2024 15:20:18 -0400
Subject: [PATCH] [mlir][linalg] Add folder for transpose(transpose) ->
transpose
Back to back `linalg.transpose` can be rewritten to a single transpose
---
.../Dialect/Linalg/IR/LinalgStructuredOps.td | 1 +
mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp | 30 +++++++++++++++
mlir/test/Dialect/Linalg/canonicalize.mlir | 37 +++++++++++++++++++
3 files changed, 68 insertions(+)
diff --git a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
index 5ee363ed32572..ac61117c3d6e3 100644
--- a/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
+++ b/mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
@@ -458,6 +458,7 @@ def TransposeOp : LinalgStructuredBase_Op<"transpose", [
}];
let hasFolder = 1;
+ let hasCanonicalizer = 1;
let hasCustomAssemblyFormat = 1;
let hasVerifier = 1;
}
diff --git a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
index 6a5f25a7605f1..1171505c61658 100644
--- a/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
+++ b/mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
@@ -1866,6 +1866,36 @@ LogicalResult TransposeOp::fold(FoldAdaptor adaptor,
return failure();
}
+/// Fold transpose with transpose.
+struct FoldTransposeWithTranspose : OpRewritePattern<linalg::TransposeOp> {
+ using OpRewritePattern<linalg::TransposeOp>::OpRewritePattern;
+
+ LogicalResult matchAndRewrite(linalg::TransposeOp transposeOp,
+ PatternRewriter &rewriter) const override {
+ if (auto defTransposeOp =
+ transposeOp.getInput().getDefiningOp<TransposeOp>()) {
+
+ auto defPerms = defTransposeOp.getPermutation();
+ auto perms = transposeOp.getPermutation();
+ SmallVector<int64_t> foldedPerms;
+ foldedPerms.reserve(perms.size());
+ for (auto perm : perms)
+ foldedPerms.push_back(defPerms[perm]);
+
+ rewriter.replaceOpWithNewOp<TransposeOp>(
+ transposeOp, defTransposeOp.getInput(), transposeOp.getInit(),
+ foldedPerms);
+ return success();
+ }
+ return failure();
+ }
+};
+
+void TransposeOp::getCanonicalizationPatterns(RewritePatternSet &results,
+ MLIRContext *context) {
+ results.add<FoldTransposeWithTranspose>(context);
+}
+
//===----------------------------------------------------------------------===//
// BroadcastOp
//===----------------------------------------------------------------------===//
diff --git a/mlir/test/Dialect/Linalg/canonicalize.mlir b/mlir/test/Dialect/Linalg/canonicalize.mlir
index 19cea6c2066c9..d381b5dfd9fc5 100644
--- a/mlir/test/Dialect/Linalg/canonicalize.mlir
+++ b/mlir/test/Dialect/Linalg/canonicalize.mlir
@@ -1051,3 +1051,40 @@ func.func @transpose_identity_perm(%input: tensor<16x32x64xf32>,
// CHECK-NOT: linalg.transpose
// CHECK: return %[[INPUT]] : tensor<16x32x64xf32>
+// -----
+
+func.func @transpose_transpose_cancel(%input: tensor<5x4x3xf32>,
+ %init1: tensor<4x3x5xf32>,
+ %init2: tensor<5x4x3xf32>) -> tensor<5x4x3xf32> {
+ // CHECK-LABEL: @transpose_transpose_cancel
+ // CHECK-NOT: linalg.transpose
+ %transpose1 = linalg.transpose
+ ins(%input:tensor<5x4x3xf32>)
+ outs(%init1:tensor<4x3x5xf32>)
+ permutation = [1, 2, 0]
+ %transpose2 = linalg.transpose
+ ins(%transpose1:tensor<4x3x5xf32>)
+ outs(%init2:tensor<5x4x3xf32>)
+ permutation = [2, 0, 1]
+ func.return %transpose2 : tensor<5x4x3xf32>
+}
+
+// -----
+
+func.func @transpose_transpose_fold(%input: tensor<5x4x3xf32>,
+ %init1: tensor<4x3x5xf32>,
+ %init2: tensor<3x4x5xf32>) -> tensor<3x4x5xf32> {
+// CHECK-LABEL: @transpose_transpose_fold
+// CHECK: linalg.transpose ins(%{{.+}} : tensor<5x4x3xf32>) outs(%{{.+}} : tensor<3x4x5xf32>) permutation = [2, 1, 0]
+// CHECK-NOT: linalg.transpose
+ %transpose1 = linalg.transpose
+ ins(%input:tensor<5x4x3xf32>)
+ outs(%init1:tensor<4x3x5xf32>)
+ permutation = [1, 2, 0]
+ %transpose2 = linalg.transpose
+ ins(%transpose1:tensor<4x3x5xf32>)
+ outs(%init2:tensor<3x4x5xf32>)
+ permutation = [1, 0, 2]
+ func.return %transpose2 : tensor<3x4x5xf32>
+}
+
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