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[AutoBump] Merge with fixes of 729f958c (Jan 22) (14) #552

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729f958
[TOSA] Add SameOperandsAndResultRank to TOSA Ops (#104501)
Tai78641 Jan 22, 2025
3e6b7bf
[AutoBump] Merge with fixes of 729f958c (Jan 22)
jorickert May 21, 2025
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3 changes: 2 additions & 1 deletion mlir/include/mlir/Dialect/Tosa/IR/TosaOpBase.td
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Original file line number Diff line number Diff line change
Expand Up @@ -231,7 +231,7 @@ def TosaResolvableShapeOperands : NativeOpTrait<"TosaResolvableShapeOperands"> {
//===----------------------------------------------------------------------===//

class Tosa_Op<string mnemonic, list<Trait> traits = []> :
Op<Tosa_Dialect, mnemonic, !listconcat(traits, [TosaOpInterface,
Op<Tosa_Dialect, mnemonic, !listconcat(traits, [TosaOpInterface,
TosaResolvableShapeOperands])> {
}

Expand All @@ -241,6 +241,7 @@ class Tosa_ElementwiseOp<string mnemonic, list<Trait> traits = []> :
["inferReturnTypeComponents"]>,
ResultsBroadcastableShape,
TosaElementwiseOperator,
SameOperandsAndResultRank,
Pure])> {
let assemblyFormat =
"operands attr-dict `:` functional-type(operands, results)";
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28 changes: 28 additions & 0 deletions mlir/lib/Dialect/Tosa/Transforms/TosaInferShapes.cpp
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Expand Up @@ -303,6 +303,32 @@ void propagateShapesInRegion(Region &region, TypeModificationState &state) {
}
}

/// Recursively validate tosa ops with SameOperandsAndResultRank trait in region
/// and all nested regions
void validateSameOperandsAndResultRankTrait(Region &region) {
int errs = 0;
for (auto &block : region) {
for (auto &op : block) {
if (!op.getDialect() ||
op.getDialect()->getNamespace() != TosaDialect::getDialectNamespace())
continue;
if (op.hasTrait<OpTrait::SameOperandsAndResultRank>()) {
if (OpTrait::impl::verifySameOperandsAndResultRank(&op).failed()) {
errs++;
}
}
WhileOp whileOp = dyn_cast<WhileOp>(op);
IfOp ifOp = dyn_cast<IfOp>(op);
if (whileOp || ifOp) {
// recurse into whileOp's regions
for (auto &next : op.getRegions()) {
validateSameOperandsAndResultRankTrait(next);
}
}
}
}
}

/// Pass that performs shape propagation across TOSA operations. This includes
/// migrating to within the regions of if/while operations.
struct TosaInferShapes
Expand All @@ -313,6 +339,8 @@ struct TosaInferShapes
TypeModificationState state;
propagateShapesInRegion(func.getBody(), state);
state.commit();

validateSameOperandsAndResultRankTrait(func.getBody());
}
};
} // namespace
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8 changes: 8 additions & 0 deletions mlir/test/Conversion/TosaToLinalg/tosa-to-linalg-invalid.mlir
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Expand Up @@ -45,3 +45,11 @@ func.func @rescale_unsupported_type(%arg0: tensor<13x21x3x!quant.uniform<u8:f32,
%0 = tosa.rescale %arg0 {double_round = false, input_zp = 127 : i32, multiplier = array<i32: 1073741824>, output_zp = -1 : i32, per_channel = false, scale32 = true, shift = array<i8: 30>} : (tensor<13x21x3x!quant.uniform<u8:f32, 0.015655439347028732:127>>) -> tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
return %0 : tensor<13x21x3x!quant.uniform<i8:f32, 0.015655439347028732:-1>>
}

// -----

func.func @test_add_2d_different_ranks(%arg0: tensor<3x4xf32>, %arg1: tensor<2x3x4xf32>) -> tensor<2x3x4xf32> {
// expected-error@+1 {{'tosa.add' op operands don't have matching ranks}}
%0 = "tosa.add"(%arg0, %arg1) : (tensor<3x4xf32>, tensor<2x3x4xf32>) -> tensor<2x3x4xf32>
return %0 : tensor<2x3x4xf32>
}
35 changes: 7 additions & 28 deletions mlir/test/Conversion/TosaToLinalg/tosa-to-linalg.mlir
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Expand Up @@ -94,6 +94,7 @@ func.func @test_add_0d(%arg0: tensor<f32>, %arg1: tensor<f32>) -> tensor<f32> {
// CHECK: } -> tensor<f32>
%0 = tosa.add %arg0, %arg1 : (tensor<f32>, tensor<f32>) -> tensor<f32>


// CHECK: return [[RESULT]] : tensor<f32>
return %0 : tensor<f32>
}
Expand Down Expand Up @@ -123,20 +124,20 @@ func.func @test_add_uint8(%arg0: tensor<ui8>, %arg1: tensor<ui8>) -> tensor<ui8>
// CHECK: #[[$MAP0:.+]] = affine_map<(d0, d1) -> (d0, d1)>
// CHECK: #[[$MAP1:.+]] = affine_map<(d0, d1) -> (0, d1)>

// CHECK-LABEL: func.func @test_add_0d_broadcast(
// CHECK-LABEL: func.func @test_add_2d_broadcast(
// CHECK-SAME: %[[ARG0:.*]]: tensor<2x1xf32>,
// CHECK-SAME: %[[ARG1:.*]]: tensor<f32>) -> tensor<2x1xf32> {
// CHECK: %[[EXPANDED:.*]] = tensor.expand_shape %[[ARG1]] [] output_shape [1, 1] : tensor<f32> into tensor<1x1xf32>
// CHECK-SAME: %[[ARG1:.*]]: tensor<1x1xf32>) -> tensor<2x1xf32> {
// CHECK: %[[EMPTY_TENSOR:.*]] = tensor.empty() : tensor<2x1xf32>
// CHECK: %[[RESULT:.*]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]], %[[EXPANDED]] : tensor<2x1xf32>, tensor<1x1xf32>) outs(%[[EMPTY_TENSOR]] : tensor<2x1xf32>) {
// CHECK: %[[RESULT:.*]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP0]]], iterator_types = ["parallel", "parallel"]} ins(%[[ARG0]], %[[ARG1]] : tensor<2x1xf32>, tensor<1x1xf32>) outs(%[[EMPTY_TENSOR]] : tensor<2x1xf32>) {
// CHECK: ^bb0(%[[IN0:.*]]: f32, %[[IN1:.*]]: f32, %[[OUT:.*]]: f32):
// CHECK: %[[ADD:.*]] = arith.addf %[[IN0]], %[[IN1]] : f32
// CHECK: linalg.yield %[[ADD]] : f32
// CHECK: } -> tensor<2x1xf32>
// CHECK: return %[[RESULT]] : tensor<2x1xf32>
// CHECK: }
func.func @test_add_0d_broadcast(%arg0: tensor<2x1xf32>, %arg1: tensor<f32>) -> tensor<2x1xf32> {
%0 = tosa.add %arg0, %arg1 : (tensor<2x1xf32>, tensor<f32>) -> tensor<2x1xf32>
func.func @test_add_2d_broadcast(%arg0: tensor<2x1xf32>, %arg1: tensor<1x1xf32>) -> tensor<2x1xf32> {
// tosa element-wise operators now require operands of equal ranks
%0 = tosa.add %arg0, %arg1 : (tensor<2x1xf32>, tensor<1x1xf32>) -> tensor<2x1xf32>
return %0 : tensor<2x1xf32>
}

Expand Down Expand Up @@ -403,28 +404,6 @@ func.func @test_add_2d_all_dynamic(%arg0: tensor<?x?xf32>, %arg1: tensor<?x?xf32

// -----

// CHECK: #[[$MAP0:.+]] = affine_map<(d0, d1, d2) -> (0, d1, d2)>
// CHECK: #[[$MAP1:.+]] = affine_map<(d0, d1, d2) -> (d0, d1, d2)>
// CHECK-LABEL: @test_add_2d_different_ranks
// CHECK-SAME: %[[ARG0:[0-9a-zA-Z_]*]]:
// CHECK-SAME: %[[ARG1:[0-9a-zA-Z_]*]]:
func.func @test_add_2d_different_ranks(%arg0: tensor<3x4xf32>, %arg1: tensor<2x3x4xf32>) -> tensor<2x3x4xf32> {

// CHECK: %[[ARG0_EXPANDED:.*]] = tensor.expand_shape %[[ARG0]] {{\[\[}}0, 1], [2]] output_shape [1, 3, 4] : tensor<3x4xf32> into tensor<1x3x4xf32>
// CHECK: %[[VAL_0:.*]] = tensor.empty() : tensor<2x3x4xf32>
// CHECK: %[[RESULT:.*]] = linalg.generic {indexing_maps = [#[[$MAP0]], #[[$MAP1]], #[[$MAP1]]], iterator_types = ["parallel", "parallel", "parallel"]} ins(%[[ARG0_EXPANDED]], %[[ARG1]] : tensor<1x3x4xf32>, tensor<2x3x4xf32>) outs(%[[VAL_0]] : tensor<2x3x4xf32>) {
// CHECK: ^bb0(%[[VAL_1:.*]]: f32, %[[VAL_2:.*]]: f32, %[[VAL_3:.*]]: f32):
// CHECK: %[[VAL_4:.*]] = arith.addf %[[VAL_1]], %[[VAL_2]] : f32
// CHECK: linalg.yield %[[VAL_4]] : f32
// CHECK: } -> tensor<2x3x4xf32>
%0 = tosa.add %arg0, %arg1 : (tensor<3x4xf32>, tensor<2x3x4xf32>) -> tensor<2x3x4xf32>

// CHECK: return %[[RESULT]] : tensor<2x3x4xf32>
return %0 : tensor<2x3x4xf32>
}

// -----

// CHECK: #[[$MAP0:.+]] = affine_map<(d0, d1) -> (d0, 0)>
// CHECK: #[[$MAP1:.+]] = affine_map<(d0, d1) -> (d0, d1)>
// CHECK-LABEL: @test_select_2d_one_dynamic
Expand Down
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