From: Quinn Dawkins <quinn@nod-labs.com>
Date: Mon, 20 Feb 2023 19:49:38 +0000 (-0500)
Subject: [mlir][tensor] Fix transpose permutation in tensor.pack generalization pattern
X-Git-Tag: upstream/17.0.6~16748
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=bbf1d80d67db5076e4cd02caa754c0688239fe76;p=platform%2Fupstream%2Fllvm.git

[mlir][tensor] Fix transpose permutation in tensor.pack generalization pattern

The generalization pattern for tensor.pack was inverting the
innerDimsPos permutation when normalizing. Thus, the transpose op
produced by the generalization would be incorrect.

Differential Revision: https://reviews.llvm.org/D144425
---

diff --git a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
index 3b2cd0d..96c29e4 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/Transforms.cpp
@@ -578,6 +578,13 @@ LogicalResult GeneralizeOuterUnitDimsPackOpPattern::matchAndRewrite(
   // 2. Transpose the tile to match the inner tile order.
   SmallVector<int64_t> perm =
       getPackUnpackNormalizedInnerPerm(srcRank, packOp.getInnerDimsPos());
+  // The permutation is inverted when normalizing so invert back to match the
+  // ordering in the pack op.
+  perm = invertPermutationVector(perm);
+
+  LLVM_DEBUG(DBGS() << "Pack permutation: " << packOp << "\n";
+             llvm::interleaveComma(perm, DBGS() << "perm: "); DBGSNL(););
+
   SmallVector<int64_t> transpShape = readShape;
   applyPermutationToVector<int64_t>(transpShape, perm);
 
diff --git a/mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir b/mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir
index 3feb165..8e9b77e 100644
--- a/mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir
+++ b/mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir
@@ -58,3 +58,21 @@ func.func @simple_NC_to_CNnc(%arg0: tensor<32x8xf32>, %arg1: tensor<1x1x32x8xf32
 // CHECK:         %[[INSERT:.+]] = tensor.insert_slice %[[TRANSP]] into %[[DEST]]
 // CHECK-SAME:      [0, 0, 0, 0] [1, 1, 32, 8] [1, 1, 1, 1]
 // CHECK:         return %[[INSERT]]
+
+// -----
+
+func.func @simple_CHW_to_CHWhwc(%arg0: tensor<3x5x7xf32>, %arg1: tensor<1x1x1x5x7x3xf32>) -> tensor<1x1x1x5x7x3xf32> {
+  %0 = tensor.pack %arg0 inner_dims_pos = [1, 2, 0] inner_tiles = [5, 7, 3] into %arg1 : tensor<3x5x7xf32> -> tensor<1x1x1x5x7x3xf32>
+  return %0 : tensor<1x1x1x5x7x3xf32>
+}
+// CHECK-LABEL: func.func @simple_CHW_to_CHWhwc
+// CHECK-SAME:    %[[SRC:[a-zA-Z0-9]+]]
+// CHECK-SAME:    %[[DEST:[a-zA-Z0-9]+]]
+// CHECK:         %[[EMPTY:.+]] = tensor.empty() : tensor<5x7x3xf32>
+// CHECK:         %[[TRANSP:.+]] =  linalg.transpose
+// CHECK-SAME:      ins(%[[SRC]] : tensor<3x5x7xf32>)
+// CHECK-SAME:      outs(%[[EMPTY]] : tensor<5x7x3xf32>)
+// CHECK-SAME:      permutation = [1, 2, 0]
+// CHECK:         %[[INSERT:.+]] = tensor.insert_slice %[[TRANSP]] into %[[DEST]]
+// CHECK-SAME:      [0, 0, 0, 0, 0, 0] [1, 1, 1, 5, 7, 3] [1, 1, 1, 1, 1, 1]
+// CHECK:         return %[[INSERT]]