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Merged
merged 3 commits into from
Feb 21, 2024
Merged

[mlir][Linalg] Add folders for linalg.transpose #81709

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49af442
[mlir][Linalg] Add folders for `linalg.transpose`
dcaballe Feb 14, 2024
76047f4
Merge remote-tracking branch 'github/main' into fold-linalg-transpose
dcaballe Feb 20, 2024
5715b89
Fix tests
dcaballe Feb 21, 2024
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3 changes: 2 additions & 1 deletion mlir/include/mlir/Dialect/Linalg/IR/LinalgStructuredOps.td
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Original file line number Diff line number Diff line change
Expand Up @@ -245,7 +245,7 @@ def MapOp : LinalgStructuredBase_Op<"map", [
}
```

Shortened print form is available. Applies to simple maps with one
Shortened print form is available. Applies to simple maps with one
non-yield operation inside the body.

The example above will be printed as:
Expand Down Expand Up @@ -458,6 +458,7 @@ def TransposeOp : LinalgStructuredBase_Op<"transpose", [
::mlir::OperationState & odsState);
}];

let hasFolder = 1;
let hasCustomAssemblyFormat = 1;
let hasVerifier = 1;
}
Expand Down
16 changes: 16 additions & 0 deletions mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp
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Expand Up @@ -1786,6 +1786,22 @@ void TransposeOp::getEffects(
getDpsInits());
}

LogicalResult TransposeOp::fold(FoldAdaptor adaptor,
SmallVectorImpl<OpFoldResult> &result) {
// Single dimension transpose.
if (getPermutation().size() == 0) {
result.push_back(getInput());
return success();
}
// Identity permutation.
if (isIdentityPermutation(getPermutation())) {
result.push_back(getInput());
return success();
}

return failure();
}

//===----------------------------------------------------------------------===//
// BroadcastOp
//===----------------------------------------------------------------------===//
Expand Down
35 changes: 35 additions & 0 deletions mlir/test/Dialect/Linalg/canonicalize.mlir
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Expand Up @@ -1029,3 +1029,38 @@ func.func @broadcast_same_shape(%input: tensor<2x3xf32>, %init: tensor<2x3xf32>)
%0 = linalg.broadcast ins(%input: tensor<2x3xf32>) outs(%init: tensor<2x3xf32>) dimensions = []
return %0 : tensor<2x3xf32>
}

// ----

func.func @transpose_1d(%input: tensor<16xf32>,
%init: tensor<16xf32>) -> tensor<16xf32> {
%transpose = linalg.transpose
ins(%input:tensor<16xf32>)
outs(%init:tensor<16xf32>)
permutation = [0]
func.return %transpose : tensor<16xf32>
}

// CHECK-LABEL: func @transpose_1d(
// CHECK-SAME: %[[INPUT:[a-zA-Z0-9]+]]: tensor<16xf32>,
// CHECK-SAME: %[[INIT:[a-zA-Z0-9]+]]: tensor<16xf32>)
// CHECK-NOT: linalg.transpose
// CHECK: return %[[INPUT]] : tensor<16xf32>

// -----

func.func @transpose_identity_perm(%input: tensor<16x32x64xf32>,
%init: tensor<16x32x64xf32>) -> tensor<16x32x64xf32> {
%transpose = linalg.transpose
ins(%input:tensor<16x32x64xf32>)
outs(%init:tensor<16x32x64xf32>)
permutation = [0, 1, 2]
func.return %transpose : tensor<16x32x64xf32>
}

// CHECK-LABEL: func @transpose_identity_perm(
// CHECK-SAME: %[[INPUT:[a-zA-Z0-9]+]]: tensor<16x32x64xf32>,
// CHECK-SAME: %[[INIT:[a-zA-Z0-9]+]]: tensor<16x32x64xf32>)
// CHECK-NOT: linalg.transpose
// CHECK: return %[[INPUT]] : tensor<16x32x64xf32>

16 changes: 4 additions & 12 deletions mlir/test/Dialect/Linalg/generalize-tensor-pack-tile.mlir
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Expand Up @@ -48,12 +48,8 @@ func.func @pad_and_pack(%arg0: tensor<13x15xf32>, %arg1: tensor<2x8x8x2xf32>, %a
// CHECK: %[[PAD:.+]] = tensor.pad %[[SRC_SLICE]]
// CHECK: tensor.yield %[[PAD_VAL]]
// CHECK: } : tensor<?x?xf32> to tensor<8x2xf32>
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<8x2xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[PAD]] : tensor<8x2xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<8x2xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK: %{{.+}} = tensor.insert_slice %[[TRANSP]] into %{{.+}}
// CHECK-NOT: linalg.transpose
// CHECK: %{{.+}} = tensor.insert_slice %[[PAD]] into %{{.+}}

module attributes {transform.with_named_sequence} {
transform.named_sequence @__transform_main(%arg1: !transform.any_op {transform.readonly}) {
Expand Down Expand Up @@ -81,12 +77,8 @@ func.func @KC_to_CKkc(%arg0: tensor<128x256xf32>, %arg1: tensor<32x4x32x8xf32>)
// CHECK-DAG: %[[IN_C:.+]] = affine.apply #[[MAP2]](%[[C]])
// CHECK: %[[TILE:.+]] = tensor.extract_slice %[[SRC]]
// CHECK-SAME: [%[[IN_K]], %[[IN_C]]] [32, 8] [1, 1]
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<32x8xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[TILE]]
// CHECK-SAME: outs(%[[EMPTY]]
// CHECK-SAME: permutation = [0, 1]
// CHECK: %[[SUB_ITER:.+]] = tensor.insert_slice %[[TRANSP]] into %{{[a-zA-Z0-9]+}}
// CHECK-NOT: linalg.transpose
// CHECK: %[[SUB_ITER:.+]] = tensor.insert_slice %[[TILE]] into %{{[a-zA-Z0-9]+}}
// CHECK-SAME: [0, 0, 0, 0] [1, 1, 32, 8] [1, 1, 1, 1] : tensor<32x8xf32> into tensor<1x1x32x8xf32>
// CHECK: %{{.+}} = tensor.insert_slice %[[SUB_ITER]] into %{{[a-zA-Z0-9]+}}
// CHECK-SAME: [%[[C]], %[[K]], 0, 0] [1, 1, 32, 8] [1, 1, 1, 1] : tensor<1x1x32x8xf32> into tensor<32x4x32x8xf32>
Expand Down
16 changes: 4 additions & 12 deletions mlir/test/Dialect/Linalg/generalize-tensor-pack.mlir
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Expand Up @@ -29,12 +29,8 @@ func.func @simple_pad_and_pack(%input: tensor<5x1xf32>, %output: tensor<1x1x8x2x
// CHECK-SAME: %[[PAD_VAL:[a-zA-Z0-9]+]]
// CHECK: %[[PAD:.+]] = tensor.pad %[[SRC]] low[0, 0] high[3, 1]
// CHECK: tensor.yield %[[PAD_VAL]]
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<8x2xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[PAD]] : tensor<8x2xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<8x2xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[TRANSP]] into %[[DEST]]
// CHECK-NOT: linalg.transpose
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[PAD]] into %[[DEST]]
// CHECK-SAME: [0, 0, 0, 0] [1, 1, 8, 2] [1, 1, 1, 1]
// CHECK: return %[[INSERT]]

Expand All @@ -47,12 +43,8 @@ func.func @simple_NC_to_CNnc(%arg0: tensor<32x8xf32>, %arg1: tensor<1x1x32x8xf32
// CHECK-LABEL: func.func @simple_NC_to_CNnc
// CHECK-SAME: %[[SRC:[a-zA-Z0-9]+]]
// CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]]
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<32x8xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[SRC]] : tensor<32x8xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<32x8xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[TRANSP]] into %[[DEST]]
// CHECK-NOT: linalg.transpose
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[SRC]] into %[[DEST]]
// CHECK-SAME: [0, 0, 0, 0] [1, 1, 32, 8] [1, 1, 1, 1]
// CHECK: return %[[INSERT]]

Expand Down
16 changes: 4 additions & 12 deletions mlir/test/Dialect/Linalg/generalize-tensor-unpack-tile.mlir
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Expand Up @@ -57,12 +57,8 @@ func.func @unpack_and_extract_slice(%arg0: tensor<2x8x8x2xf32>, %arg1: tensor<13
// CHECK-SAME: [%[[I]], %[[J]]] [%[[OUT_I_SZ]], %[[OUT_J_SZ]]]
// CHECK: %[[TILE:.+]] = tensor.extract_slice %[[SRC_SLICE]]
// CHECK-SAME: [0, 0, 0, 0] [1, 1, 8, 2] [1, 1, 1, 1] : tensor<1x1x8x2xf32> to tensor<8x2xf32>
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<8x2xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[TILE]] : tensor<8x2xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<8x2xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK: %[[UNPACK_TILE:.+]] = tensor.extract_slice %[[TRANSP]]
// CHECK-NOT: linalg.transpose
// CHECK: %[[UNPACK_TILE:.+]] = tensor.extract_slice %[[TILE]]
// CHECK-SAME: [0, 0] [%[[OUT_I_SZ]], %[[OUT_J_SZ]]] [1, 1]
// CHECK: %[[INSERT1:.+]] = tensor.insert_slice %[[UNPACK_TILE]] into %[[ITER_SLICE]]
// CHECK-SAME: [0, 0] [%[[OUT_I_SZ]], %[[OUT_J_SZ]]] [1, 1]
Expand Down Expand Up @@ -96,12 +92,8 @@ func.func @CKkc_to_KC(%arg0: tensor<32x4x32x8xf32>, %arg1: tensor<128x256xf32>)
// CHECK-SAME: [%[[IN_C]], %[[IN_K]], 0, 0] [1, 1, 32, 8] [1, 1, 1, 1]
// CHECK: %[[TILE:.+]] = tensor.extract_slice %[[SRC_SLICE]]
// CHECK-SAME: [0, 0, 0, 0] [1, 1, 32, 8] [1, 1, 1, 1] : tensor<1x1x32x8xf32> to tensor<32x8xf32>
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<32x8xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[TILE]]
// CHECK-SAME: outs(%[[EMPTY]]
// CHECK-SAME: permutation = [0, 1]
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[TRANSP]] into %{{[a-zA-Z0-9]+}}
// CHECK-NOT: linalg.transpose
// CHECK: %[[INSERT:.+]] = tensor.insert_slice %[[TILE]] into %{{[a-zA-Z0-9]+}}
// CHECK-SAME: [%[[K]], %[[C]]] [32, 8] [1, 1]


Expand Down
17 changes: 4 additions & 13 deletions mlir/test/Dialect/Linalg/generalize-tensor-unpack.mlir
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Expand Up @@ -27,14 +27,10 @@ func.func @simple_unpack_and_extract_slice(%input: tensor<1x1x8x2xf32>, %output:
// CHECK-SAME: %[[SRC:[a-zA-Z0-9]+]]
// CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]]
// CHECK: %[[TILE:.+]] = tensor.extract_slice %[[SRC]][0, 0, 0, 0] [1, 1, 8, 2] [1, 1, 1, 1]
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<8x2xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[TILE]] : tensor<8x2xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<8x2xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK-NOT: linalg.transpose
// They have the same type, so the insert_slice op is folded
// away.
// CHECK: %[[SLICE:.+]] = tensor.extract_slice %[[TRANSP]][0, 0] [5, 1] [1, 1]
// CHECK: %[[SLICE:.+]] = tensor.extract_slice %[[TILE]][0, 0] [5, 1] [1, 1]
// CHECK: return %[[SLICE]]

// -----
Expand All @@ -47,14 +43,10 @@ func.func @simple_CNnc_to_NC(%arg0: tensor<1x1x32x8xf32>, %arg1: tensor<32x8xf32
// CHECK-SAME: %[[SRC:[a-zA-Z0-9]+]]
// CHECK-SAME: %[[DEST:[a-zA-Z0-9]+]]
// CHECK: %[[TILE:.+]] = tensor.extract_slice %[[SRC]][0, 0, 0, 0] [1, 1, 32, 8] [1, 1, 1, 1]
// CHECK: %[[EMPTY:.+]] = tensor.empty() : tensor<32x8xf32>
// CHECK: %[[TRANSP:.+]] = linalg.transpose
// CHECK-SAME: ins(%[[TILE]] : tensor<32x8xf32>)
// CHECK-SAME: outs(%[[EMPTY]] : tensor<32x8xf32>)
// CHECK-SAME: permutation = [0, 1]
// CHECK-NOT: linalg.transpose
// They have the same type, so the insert_slice op is folded
// away.
// CHECK: return %[[TRANSP]]
// CHECK: return %[[TILE]]

// -----

Expand All @@ -75,7 +67,6 @@ func.func @simple_NCHWc_to_NCHW(%arg0: tensor<2x1x16x8x32xf32>, %arg1: tensor<2x
// away.
// CHECK: return %[[TRANSP]]


// -----

func.func @simple_NHWC_to_NCHW(%arg0: tensor<1x16x8x32xf32>, %arg1: tensor<1x32x16x8xf32>) -> tensor<1x32x16x8xf32> {
Expand Down