[Mlir-commits] [mlir] 75f7295 - [mlir][Tensor] Fix unpack -> transpose folding pattern for padded unpacks (#90678)
llvmlistbot at llvm.org
llvmlistbot at llvm.org
Tue Apr 30 17:17:39 PDT 2024
Author: Quinn Dawkins
Date: 2024-04-30T20:17:35-04:00
New Revision: 75f7295419606380a7b5deea06359794a23429d9
URL: https://github.com/llvm/llvm-project/commit/75f7295419606380a7b5deea06359794a23429d9
DIFF: https://github.com/llvm/llvm-project/commit/75f7295419606380a7b5deea06359794a23429d9.diff
LOG: [mlir][Tensor] Fix unpack -> transpose folding pattern for padded unpacks (#90678)
Previously if the producer tensor.unpack op had "unpadding" semantics,
the folding pattern would construct a destination that does not match
with the result type of the transpose. Because both ops are DPS we can
just reuse the destination of the transpose.
Additionally cleans up a bunch of trailing whitespace in the test file.
Added:
Modified:
mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
mlir/test/Dialect/Tensor/fold-into-pack-and-unpack.mlir
Removed:
################################################################################
diff --git a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
index 7011ce23b55a6b..ebcb34e9ef024e 100644
--- a/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
+++ b/mlir/lib/Dialect/Tensor/Transforms/PackAndUnpackPatterns.cpp
@@ -374,13 +374,10 @@ struct FoldProducerUnPackWithConsumerLinalgTransposeOp
for (auto dim : innerDimsPos)
newInnerDimsPosVec.push_back(transposePermutation[dim]);
- Value output = unPackOp.createDestinationTensor(
- rewriter, transposeOp.getLoc(), unPackOp.getSource(),
- unPackOp.getMixedTiles(), newInnerDimsPosVec, newOuterDimsPermVec);
-
+ // Reuse the destination of the transpose op.
rewriter.replaceOpWithNewOp<UnPackOp>(
- transposeOp, unPackOp.getSource(), output, newInnerDimsPosVec,
- unPackOp.getMixedTiles(), newOuterDimsPermVec);
+ transposeOp, unPackOp.getSource(), transposeOp.getDpsInits()[0],
+ newInnerDimsPosVec, unPackOp.getMixedTiles(), newOuterDimsPermVec);
return success();
}
diff --git a/mlir/test/Dialect/Tensor/fold-into-pack-and-unpack.mlir b/mlir/test/Dialect/Tensor/fold-into-pack-and-unpack.mlir
index aa860e33cf3517..9f486f9146ad88 100644
--- a/mlir/test/Dialect/Tensor/fold-into-pack-and-unpack.mlir
+++ b/mlir/test/Dialect/Tensor/fold-into-pack-and-unpack.mlir
@@ -137,7 +137,7 @@ func.func @tensor_pack_linalg_transpose_fold(%arg0: tensor<56x57x1x64xf32>) -> t
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x57x56x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 1, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -163,7 +163,7 @@ func.func @tensor_pack_linalg_transpose_fold_with_padding(%arg0: tensor<56x57x1x
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x57x56x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] padding_value(%[[PADDING]] : f32)
// CHECK-SAME: outer_dims_perm = [2, 1, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -188,7 +188,7 @@ func.func @tensor_pack_linalg_transpose_fold_no_outer_dims_perm(%arg0: tensor<56
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x2x56x57x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 3, 0, 1]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -214,7 +214,7 @@ func.func @tensor_pack_linalg_transpose_fold_tile_dims_transpose(%arg0: tensor<5
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<12x56x4x9x32x8x2xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 0, 3, 1]
-// CHECK-SAME: inner_dims_pos = [3, 1, 2] inner_tiles = [32, 8, 2]
+// CHECK-SAME: inner_dims_pos = [3, 1, 2] inner_tiles = [32, 8, 2]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -256,7 +256,7 @@ func.func @tensor_pack_linalg_transpose_fold_dynamic_outer_dims(%arg0: tensor<56
outs(%1 : tensor<1x57x56x2x32xf32>)
permutation = [2, 3, 0, 1, 4]
- %return_value = tensor.cast %transposed : tensor<1x57x56x2x32xf32> to tensor<?x?x56x2x32xf32>
+ %return_value = tensor.cast %transposed : tensor<1x57x56x2x32xf32> to tensor<?x?x56x2x32xf32>
return %return_value : tensor<?x?x56x2x32xf32>
}
// CHECK: func @tensor_pack_linalg_transpose_fold_dynamic_outer_dims(
@@ -268,7 +268,7 @@ func.func @tensor_pack_linalg_transpose_fold_dynamic_outer_dims(%arg0: tensor<56
// CHECK: %[[INIT:.+]] = tensor.empty(%[[dim_0]], %[[dim]]) : tensor<?x?x56x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 1, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -286,14 +286,14 @@ func.func @tensor_pack_linalg_transpose_fold_dynamic_outer_and_tile_dims(%arg0:
ins(%pack : tensor<56x9x12x4x8x2x32xf32>)
outs(%1 : tensor<12x4x56x9x32x8x2xf32>)
permutation = [2, 3, 0, 1, 6, 4, 5]
-
- %return_value = tensor.cast %transposed : tensor<12x4x56x9x32x8x2xf32> to tensor<?x?x56x9x32x8x2xf32>
+
+ %return_value = tensor.cast %transposed : tensor<12x4x56x9x32x8x2xf32> to tensor<?x?x56x9x32x8x2xf32>
return %return_value : tensor<?x?x56x9x32x8x2xf32>
}
// CHECK-DAG: #[[$MAP0:.+]] = affine_map<()[s0] -> (s0 ceildiv 8)>
// CHECK-DAG: #[[$MAP1:.+]] = affine_map<()[s0] -> (s0 ceildiv 2)>
// CHECK-LABEL: func.func @tensor_pack_linalg_transpose_fold_dynamic_outer_and_tile_dims(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<56x?x?x128xf32>)
+// CHECK-SAME: %[[ARG0:.+]]: tensor<56x?x?x128xf32>)
// CHECK-DAG: %[[c1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[c2:.+]] = arith.constant 2 : index
// CHECK: %[[dim:.+]] = tensor.dim %[[ARG0]], %[[c1]] : tensor<56x?x?x128xf32>
@@ -328,7 +328,7 @@ func.func @tensor_pack_linalg_transpose_fold_dynamic_outer_dims_tile_dims_tile_s
// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?x?xf32>,
// CHECK-SAME: %[[PACK_DEST:.+]]: tensor<?x?x?x?x?x?x?xf32>, %[[TRANSPOSE_DEST:.+]]: tensor<?x?x?x?x?x?x?xf32>,
// CHECK-SAME: %[[ARG1:.+]]: index, %[[ARG2:.+]]: index,
-// CHECK-SAME: %[[ARG3:.+]]: index)
+// CHECK-SAME: %[[ARG3:.+]]: index)
// CHECK-DAG: %[[c0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[c1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[c2:.+]] = arith.constant 2 : index
@@ -367,7 +367,7 @@ func.func @linalg_transpose_tensor_pack_fold(%arg0: tensor<56x57x1x64xf32>) -> t
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x57x56x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 1, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -379,7 +379,7 @@ func.func @linalg_transpose_tensor_pack_fold_with_padding(%arg0: tensor<56x57x1x
ins(%arg0 : tensor<56x57x1x55xf32>)
outs(%0 : tensor<1x56x57x55xf32>)
permutation = [2, 0, 1, 3]
-
+
%1 = tensor.empty() : tensor<1x57x56x2x32xf32>
%pack = tensor.pack %transpose padding_value(%padding : f32)
outer_dims_perm = [0, 2, 1, 3]
@@ -393,7 +393,7 @@ func.func @linalg_transpose_tensor_pack_fold_with_padding(%arg0: tensor<56x57x1x
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x57x56x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]] padding_value(%[[PADDING]] : f32)
// CHECK-SAME: outer_dims_perm = [2, 1, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -405,7 +405,7 @@ func.func @linalg_transpose_tensor_pack_fold_no_outer_dims_perm(%arg0: tensor<56
ins(%arg0 : tensor<56x57x1x64xf32>)
outs(%0 : tensor<1x56x57x64xf32>)
permutation = [2, 0, 1, 3]
-
+
%1 = tensor.empty() : tensor<1x56x57x2x32xf32>
%pack = tensor.pack %transposed
inner_dims_pos = [3]
@@ -418,7 +418,7 @@ func.func @linalg_transpose_tensor_pack_fold_no_outer_dims_perm(%arg0: tensor<56
// CHECK: %[[INIT:.+]] = tensor.empty() : tensor<1x56x57x2x32xf32>
// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
// CHECK-SAME: outer_dims_perm = [2, 0, 1, 3]
-// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
+// CHECK-SAME: inner_dims_pos = [3] inner_tiles = [32]
// CHECK-SAME: into %[[INIT]]
// CHECK: return %[[PACK]]
@@ -429,7 +429,7 @@ func.func @linalg_transpose_tensor_pack_fold_complex_inner_dims_change(%arg0: te
ins(%arg0 : tensor<25x30x35x40xf32>)
outs(%transpose_dest : tensor<35x40x25x30xf32>)
permutation = [2, 3, 0, 1]
-
+
%pack = tensor.pack %transposed
outer_dims_perm = [3, 0, 2, 1]
inner_dims_pos = [1, 3, 2]
@@ -438,15 +438,15 @@ func.func @linalg_transpose_tensor_pack_fold_complex_inner_dims_change(%arg0: te
return %pack : tensor<3x35x5x8x5x10x5xf32>
}
//CHECK-LABEL: func.func @linalg_transpose_tensor_pack_fold_complex_inner_dims_change(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<25x30x35x40xf32>,
-// CHECK-SAME: %[[ARG1:.+]]: tensor<35x40x25x30xf32>,
+// CHECK-SAME: %[[ARG0:.+]]: tensor<25x30x35x40xf32>,
+// CHECK-SAME: %[[ARG1:.+]]: tensor<35x40x25x30xf32>,
// CHECK-SAME: %[[ARG2:.+]]: tensor<3x35x5x8x5x10x5xf32>) -> tensor<3x35x5x8x5x10x5xf32> {
// CHECK: %[[VAL0:.+]] = tensor.empty() : tensor<3x35x5x8x5x10x5xf32>
-// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
-// CHECK-SAME: outer_dims_perm = [1, 2, 0, 3]
-// CHECK-SAME: inner_dims_pos = [3, 1, 0]
-// CHECK-SAME: inner_tiles = [5, 10, 5]
-// CHECK-SAME: into %[[VAL0]]
+// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
+// CHECK-SAME: outer_dims_perm = [1, 2, 0, 3]
+// CHECK-SAME: inner_dims_pos = [3, 1, 0]
+// CHECK-SAME: inner_tiles = [5, 10, 5]
+// CHECK-SAME: into %[[VAL0]]
// CHECK: return %[[PACK]]
// -----
@@ -456,7 +456,7 @@ func.func @linalg_transpose_tensor_pack_fold_dynamic_outer_dims_tile_dims_tile_s
ins(%arg0 : tensor<?x?x?x?xf32>)
outs(%transpose_dest : tensor<?x?x?x?xf32>)
permutation = [2, 3, 0, 1]
-
+
%pack = tensor.pack %transposed
outer_dims_perm = [3, 0, 2, 1]
inner_dims_pos = [1, 3, 2]
@@ -466,7 +466,7 @@ func.func @linalg_transpose_tensor_pack_fold_dynamic_outer_dims_tile_dims_tile_s
}
// CHECK: #[[$MAP:.+]] = affine_map<()[s0, s1] -> (s0 ceildiv s1)>
//CHECK-LABEL: func.func @linalg_transpose_tensor_pack_fold_dynamic_outer_dims_tile_dims_tile_sizes(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?x?xf32>,
+// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?x?xf32>,
// CHECK-SAME: %[[ARG2:.+]]: tensor<?x?x?x?x?x?x?xf32>, %[[ARG3:.+]]: index, %[[ARG4:.+]]: index, %[[ARG5:.+]]: index) -> tensor<?x?x?x?x?x?x?xf32> {
// CHECK-DAG: %[[C0:.+]] = arith.constant 0 : index
// CHECK-DAG: %[[C1:.+]] = arith.constant 1 : index
@@ -491,17 +491,17 @@ func.func @linalg_transpose_tensor_pack_multiple_tiles(%arg0: tensor<?x32x128xbf
%dim = tensor.dim %arg0, %c0 : tensor<?x32x128xbf16>
%0 = tensor.empty(%dim) : tensor<32x128x?xbf16>
- %transposed = linalg.transpose
- ins(%arg0 : tensor<?x32x128xbf16>)
- outs(%0 : tensor<32x128x?xbf16>)
+ %transposed = linalg.transpose
+ ins(%arg0 : tensor<?x32x128xbf16>)
+ outs(%0 : tensor<32x128x?xbf16>)
permutation = [1, 2, 0]
%2 = tensor.empty(%dim) : tensor<32x?x64x16x2xbf16>
- %pack = tensor.pack %transposed
- padding_value(%cst : bf16)
- outer_dims_perm = [0, 2, 1]
- inner_dims_pos = [2, 1]
- inner_tiles = [16, 2]
+ %pack = tensor.pack %transposed
+ padding_value(%cst : bf16)
+ outer_dims_perm = [0, 2, 1]
+ inner_dims_pos = [2, 1]
+ inner_tiles = [16, 2]
into %2 : tensor<32x128x?xbf16> -> tensor<32x?x64x16x2xbf16>
return %pack : tensor<32x?x64x16x2xbf16>
}
@@ -513,11 +513,11 @@ func.func @linalg_transpose_tensor_pack_multiple_tiles(%arg0: tensor<?x32x128xbf
// CHECK: %[[DIM:.+]] = tensor.dim %[[ARG0]], %[[C0]] : tensor<?x32x128xbf16>
// CHECK: %[[VAL0:.+]] = affine.apply #[[$MAP]]()[%[[DIM]]]
// CHECK: %[[VAL1:.+]] = tensor.empty(%[[VAL0]]) : tensor<32x?x64x16x2xbf16>
-// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
-// CHECK-SAME: padding_value(%[[CST]] : bf16)
-// CHECK-SAME: outer_dims_perm = [1, 0, 2]
-// CHECK-SAME: inner_dims_pos = [0, 2]
-// CHECK-SAME: inner_tiles = [16, 2]
+// CHECK: %[[PACK:.+]] = tensor.pack %[[ARG0]]
+// CHECK-SAME: padding_value(%[[CST]] : bf16)
+// CHECK-SAME: outer_dims_perm = [1, 0, 2]
+// CHECK-SAME: inner_dims_pos = [0, 2]
+// CHECK-SAME: inner_tiles = [16, 2]
// CHECK-SAME: into %[[VAL1]] : tensor<?x32x128xbf16> -> tensor<32x?x64x16x2xbf16>
// CHECK: return %[[PACK]] : tensor<32x?x64x16x2xbf16>
// CHECK: }
@@ -526,24 +526,24 @@ func.func @linalg_transpose_tensor_pack_multiple_tiles(%arg0: tensor<?x32x128xbf
func.func @linalg_transpose_tensor_unpack_fold(%arg0: tensor<1x1x4x16xi32>) -> tensor<16x4xi32> {
%0 = tensor.empty() : tensor<1x1x16x4xi32>
- %transposed = linalg.transpose ins(%arg0 : tensor<1x1x4x16xi32>)
- outs(%0 : tensor<1x1x16x4xi32>)
+ %transposed = linalg.transpose ins(%arg0 : tensor<1x1x4x16xi32>)
+ outs(%0 : tensor<1x1x16x4xi32>)
permutation = [1, 0, 3, 2]
%1 = tensor.empty() : tensor<16x4xi32>
- %unpack = tensor.unpack %transposed
- outer_dims_perm = [0, 1]
- inner_dims_pos = [0, 1]
- inner_tiles = [16, 4] into
+ %unpack = tensor.unpack %transposed
+ outer_dims_perm = [0, 1]
+ inner_dims_pos = [0, 1]
+ inner_tiles = [16, 4] into
%1 : tensor<1x1x16x4xi32> -> tensor<16x4xi32>
return %unpack : tensor<16x4xi32>
}
//CHECK-LABEL: func.func @linalg_transpose_tensor_unpack_fold(
// CHECK-SAME: %[[ARG0:.+]]: tensor<1x1x4x16xi32>) -> tensor<16x4xi32> {
// CHECK: %[[OUT:.+]] = tensor.empty() : tensor<16x4xi32>
-// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
-// CHECK-SAME: outer_dims_perm = [1, 0]
-// CHECK-SAME: inner_dims_pos = [1, 0]
-// CHECK-SAME: inner_tiles = [4, 16]
+// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
+// CHECK-SAME: outer_dims_perm = [1, 0]
+// CHECK-SAME: inner_dims_pos = [1, 0]
+// CHECK-SAME: inner_tiles = [4, 16]
// CHEKC-SAME: into %[[OUT]] : tensor<1x1x4x16xi32> -> tensor<16x4xi32>
// CHECK: return %[[UNPACK]] : tensor<16x4xi32>
// CHECK: }
@@ -555,7 +555,7 @@ func.func @linalg_transpose_tensor_unpack_fold_dynamic_outer_dims_tile_dims_tile
ins(%arg0 : tensor<?x?x?x?xf32>)
outs(%transpose_dest : tensor<?x?x?x?xf32>)
permutation = [1, 0, 3, 2]
-
+
%unpack = tensor.unpack %transposed
outer_dims_perm = [1, 0]
inner_dims_pos = [0, 1]
@@ -565,7 +565,7 @@ func.func @linalg_transpose_tensor_unpack_fold_dynamic_outer_dims_tile_dims_tile
}
// CHECK: #[[$MAP:.+]] = affine_map<()[s0, s1] -> (s0 * s1)>
// CHECK-LABEL: func.func @linalg_transpose_tensor_unpack_fold_dynamic_outer_dims_tile_dims_tile_sizes(
-// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?x?xf32>, %[[ARG2:.+]]: tensor<?x?xf32>,
+// CHECK-SAME: %[[ARG0:.+]]: tensor<?x?x?x?xf32>, %[[ARG1:.+]]: tensor<?x?x?x?xf32>, %[[ARG2:.+]]: tensor<?x?xf32>,
// CHECK-SAME: %[[IDX1:.+]]: index, %[[IDX2:.+]]: index) -> tensor<?x?xf32> {
// CHECK-DAG: %[[CST1:.+]] = arith.constant 1 : index
// CHECK-DAG: %[[CST0:.+]] = arith.constant 0 : index
@@ -574,10 +574,10 @@ func.func @linalg_transpose_tensor_unpack_fold_dynamic_outer_dims_tile_dims_tile
// CHECK-DAG: %[[AMAP0:.+]] = affine.apply #[[$MAP]]()[%[[DIM1]], %[[IDX2]]]
// CHECK-DAG: %[[AMAP1:.+]] = affine.apply #[[$MAP]]()[%[[DIM0]], %[[IDX1]]]
// CHECK: %[[OUT:.+]] = tensor.empty(%[[AMAP1]], %[[AMAP0]]) : tensor<?x?xf32>
-// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
-// CHECK-SAME: outer_dims_perm = [0, 1]
-// CHECK-SAME: inner_dims_pos = [1, 0]
-// CHECK-SAME: inner_tiles = [%[[IDX2]], %[[IDX1]]]
+// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
+// CHECK-SAME: outer_dims_perm = [0, 1]
+// CHECK-SAME: inner_dims_pos = [1, 0]
+// CHECK-SAME: inner_tiles = [%[[IDX2]], %[[IDX1]]]
// CHECK-SAME: into %[[OUT]] : tensor<?x?x?x?xf32> -> tensor<?x?xf32>
// CHECK: return %[[UNPACK]] : tensor<?x?xf32>
// CHECK: }
@@ -602,10 +602,37 @@ func.func @tensor_unpack_linalg_transpose_fold(%arg0: tensor<56x57x1x64xf32>) ->
// CHECK-LABEL: func.func @tensor_unpack_linalg_transpose_fold(
// CHECK-SAME: %[[ARG0:.+]]: tensor<56x57x1x64xf32>) -> tensor<3648x56xf32> {
// CHECK: %[[OUT:.+]] = tensor.empty() : tensor<3648x56xf32>
-// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
-// CHECK-SAME: outer_dims_perm = [1, 0]
-// CHECK-SAME: inner_dims_pos = [1, 0]
-// CHECK-SAME: inner_tiles = [1, 64]
+// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
+// CHECK-SAME: outer_dims_perm = [1, 0]
+// CHECK-SAME: inner_dims_pos = [1, 0]
+// CHECK-SAME: inner_tiles = [1, 64]
// CHECK-SAME: into %[[OUT:.+]] : tensor<56x57x1x64xf32> -> tensor<3648x56xf32>
// CHECK: return %[[UNPACK]] : tensor<3648x56xf32>
// CHECK: }
+
+// -----
+
+func.func @tensor_padded_unpack_linalg_transpose_fold(%arg0: tensor<71x7x4x16x16xf32>) -> tensor<100x71x64xf32> {
+ %0 = tensor.empty() : tensor<71x100x64xf32>
+ %pack = tensor.unpack %arg0
+ inner_dims_pos = [1, 2]
+ inner_tiles = [16, 16]
+ into %0 : tensor<71x7x4x16x16xf32> -> tensor<71x100x64xf32>
+
+ %1 = tensor.empty() : tensor<100x71x64xf32>
+ %transposed = linalg.transpose
+ ins(%pack : tensor<71x100x64xf32>)
+ outs(%1 : tensor<100x71x64xf32>)
+ permutation = [1, 0, 2]
+ return %transposed : tensor<100x71x64xf32>
+}
+// CHECK-LABEL: func.func @tensor_padded_unpack_linalg_transpose_fold(
+// CHECK-SAME: %[[ARG0:.+]]: tensor<71x7x4x16x16xf32>) -> tensor<100x71x64xf32> {
+// CHECK: %[[OUT:.+]] = tensor.empty() : tensor<100x71x64xf32>
+// CHECK: %[[UNPACK:.+]] = tensor.unpack %[[ARG0]]
+// CHECK-SAME: outer_dims_perm = [1, 0, 2]
+// CHECK-SAME: inner_dims_pos = [0, 2]
+// CHECK-SAME: inner_tiles = [16, 16]
+// CHECK-SAME: into %[[OUT:.+]] : tensor<71x7x4x16x16xf32> -> tensor<100x71x64xf32>
+// CHECK: return %[[UNPACK]] : tensor<100x71x64xf32>
+// CHECK: }
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