[TOSA] bug fix infer shape for slice #108306
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This fixes the infer output shape of TOSA slice op for start/size values that are out-of-bound or -1 added tests to check: - size = -1 - size is out of bound - start is out of bound Signed-off-by: Tai Ly <tai.ly@arm.com> Change-Id: I8b59502a93cb332fe5c9a9f87970b83742538126
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@llvm/pr-subscribers-mlir-tosa Author: Tai Ly (Tai78641) ChangesThis fixes the infer output shape of TOSA slice op for start/size values that are out-of-bound or -1 added tests to check:
Full diff: https://github.com/llvm/llvm-project/pull/108306.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index 0d0241fea5152c..4ca42cc99a507a 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -842,8 +842,40 @@ LogicalResult tosa::SliceOp::inferReturnTypeComponents(
MLIRContext *context, ::std::optional<Location> location,
SliceOp::Adaptor adaptor,
SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) {
- inferredReturnShapes.push_back(
- ShapedTypeComponents(convertToMlirShape(adaptor.getSize())));
+ auto start = adaptor.getStart();
+ auto size = adaptor.getSize();
+
+ // if size[i] is -1, all remaining elements in dimension i are included
+ // in the slice, similar to TF.
+ ShapeAdaptor inputShape(adaptor.getInput().getType());
+ // initialize outputShape to all unknown
+ SmallVector<int64_t> outputShape(size.size(), ShapedType::kDynamic);
+ if (inputShape.hasRank()) {
+ for (size_t i = 0; i < size.size(); i++) {
+ if (size[i] != 0 && size[i] >= -1 && start[i] >= 0 &&
+ (ShapedType::isDynamic(inputShape.getDimSize(i)) ||
+ start[i] < inputShape.getDimSize(i))) {
+ // size[i] is not 0 and not < -1, and start[i] is in valid range
+ if (ShapedType::isDynamic(inputShape.getDimSize(i))) {
+ // input shape has unknown dim[i] - only valid if size[i] > 0
+ if (size[i] > 0) {
+ outputShape[i] = size[i];
+ }
+ } else {
+ // input shape has known dim[i]
+ if (size[i] == -1) {
+ outputShape[i] = inputShape.getDimSize(i) - start[i];
+ } else if (start[i] + size[i] <= inputShape.getDimSize(i)) {
+ // start[i] + size[i] is within bound of input shape's dim[i]
+ outputShape[i] = size[i];
+ }
+ }
+ }
+ }
+ } else {
+ outputShape = convertToMlirShape(size);
+ }
+ inferredReturnShapes.push_back(ShapedTypeComponents(outputShape));
return success();
}
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index d46de740800e93..d2314698afa925 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -532,6 +532,48 @@ func.func @test_slice(%arg0 : tensor<?xi32>) -> () {
// -----
+// CHECK-LABEL: @test_slice_size_minus_one
+func.func @test_slice_size_minus_one(%arg0 : tensor<?x8x8x8xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: -1, -1, -1, -1>, start = array<i64: 0, 1, -1, 8>} : (tensor<?x8x8x8xi32>) -> tensor<?x7x?x?xi32>
+ // this checks following
+ // dim 0: size=-1, input dim=? => inferred output dim is ?
+ // dim 1: size=-1 => inferred output dim is input_dim - start
+ // dim 2: size=-1, start=-1 => inferred output dim is ?
+ // dim 3: size=-1, start=8 => inferred output dim is ? because start is out of bound
+ %2= tosa.slice %arg0 { start = array<i64: 0, 1, -1, 8>, size = array<i64: -1, -1, -1, -1> } : (tensor<?x8x8x8xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
+// CHECK-LABEL: @test_slice_size_out_of_bound
+func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: 0, -2, 9, 4>, start = array<i64: 0, 0, 0, 0>} : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x4xi32>
+ // this checks following
+ // dim 0: size=0 => inferred output dim is ?
+ // dim 1: size=-2 => inferred output dim is ?
+ // dim 3: start+size out of bound because size too big: inferred output dim is ?
+ // dim 4: size=4, input dim=? => inferred output dim is 4
+ %2= tosa.slice %arg0 { start = array<i64: 0, 0, 0, 0>, size = array<i64: 0, -2, 9, 4> } : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
+// CHECK-LABEL: @test_slice_start_out_of_bound
+func.func @test_slice_start_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: 1, 1, 3, 4>, start = array<i64: -1, 8, 6, 8000000>} : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x4xi32>
+ // this checks following
+ // dim 0: start=-1 => inferred output dim is ?
+ // dim 1: start=8 => inferred output dim is ?
+ // dim 2: start+size out of bound: inferred output dim is ?
+ // dim 3: start=8000000, size=4, input dim=? => inferred output dim is 4
+ %2= tosa.slice %arg0 { start = array<i64: -1, 8, 6, 8000000>, size = array<i64: 1, 1, 3, 4> } : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
// CHECK-LABEL: @test_slice_dynamic
func.func @test_slice_dynamic(%arg0 : tensor<10x?x2xf32>) -> () {
// CHECK: tosa.slice %arg0 {size = array<i64: 7, -1, 1>, start = array<i64: 1, 0, 0>} : (tensor<10x?x2xf32>) -> tensor<7x?x1xf32>
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@llvm/pr-subscribers-mlir Author: Tai Ly (Tai78641) ChangesThis fixes the infer output shape of TOSA slice op for start/size values that are out-of-bound or -1 added tests to check:
Full diff: https://github.com/llvm/llvm-project/pull/108306.diff 2 Files Affected:
diff --git a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
index 0d0241fea5152c..4ca42cc99a507a 100644
--- a/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
+++ b/mlir/lib/Dialect/Tosa/IR/TosaOps.cpp
@@ -842,8 +842,40 @@ LogicalResult tosa::SliceOp::inferReturnTypeComponents(
MLIRContext *context, ::std::optional<Location> location,
SliceOp::Adaptor adaptor,
SmallVectorImpl<ShapedTypeComponents> &inferredReturnShapes) {
- inferredReturnShapes.push_back(
- ShapedTypeComponents(convertToMlirShape(adaptor.getSize())));
+ auto start = adaptor.getStart();
+ auto size = adaptor.getSize();
+
+ // if size[i] is -1, all remaining elements in dimension i are included
+ // in the slice, similar to TF.
+ ShapeAdaptor inputShape(adaptor.getInput().getType());
+ // initialize outputShape to all unknown
+ SmallVector<int64_t> outputShape(size.size(), ShapedType::kDynamic);
+ if (inputShape.hasRank()) {
+ for (size_t i = 0; i < size.size(); i++) {
+ if (size[i] != 0 && size[i] >= -1 && start[i] >= 0 &&
+ (ShapedType::isDynamic(inputShape.getDimSize(i)) ||
+ start[i] < inputShape.getDimSize(i))) {
+ // size[i] is not 0 and not < -1, and start[i] is in valid range
+ if (ShapedType::isDynamic(inputShape.getDimSize(i))) {
+ // input shape has unknown dim[i] - only valid if size[i] > 0
+ if (size[i] > 0) {
+ outputShape[i] = size[i];
+ }
+ } else {
+ // input shape has known dim[i]
+ if (size[i] == -1) {
+ outputShape[i] = inputShape.getDimSize(i) - start[i];
+ } else if (start[i] + size[i] <= inputShape.getDimSize(i)) {
+ // start[i] + size[i] is within bound of input shape's dim[i]
+ outputShape[i] = size[i];
+ }
+ }
+ }
+ }
+ } else {
+ outputShape = convertToMlirShape(size);
+ }
+ inferredReturnShapes.push_back(ShapedTypeComponents(outputShape));
return success();
}
diff --git a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
index d46de740800e93..d2314698afa925 100644
--- a/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
+++ b/mlir/test/Dialect/Tosa/tosa-infer-shapes.mlir
@@ -532,6 +532,48 @@ func.func @test_slice(%arg0 : tensor<?xi32>) -> () {
// -----
+// CHECK-LABEL: @test_slice_size_minus_one
+func.func @test_slice_size_minus_one(%arg0 : tensor<?x8x8x8xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: -1, -1, -1, -1>, start = array<i64: 0, 1, -1, 8>} : (tensor<?x8x8x8xi32>) -> tensor<?x7x?x?xi32>
+ // this checks following
+ // dim 0: size=-1, input dim=? => inferred output dim is ?
+ // dim 1: size=-1 => inferred output dim is input_dim - start
+ // dim 2: size=-1, start=-1 => inferred output dim is ?
+ // dim 3: size=-1, start=8 => inferred output dim is ? because start is out of bound
+ %2= tosa.slice %arg0 { start = array<i64: 0, 1, -1, 8>, size = array<i64: -1, -1, -1, -1> } : (tensor<?x8x8x8xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
+// CHECK-LABEL: @test_slice_size_out_of_bound
+func.func @test_slice_size_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: 0, -2, 9, 4>, start = array<i64: 0, 0, 0, 0>} : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x4xi32>
+ // this checks following
+ // dim 0: size=0 => inferred output dim is ?
+ // dim 1: size=-2 => inferred output dim is ?
+ // dim 3: start+size out of bound because size too big: inferred output dim is ?
+ // dim 4: size=4, input dim=? => inferred output dim is 4
+ %2= tosa.slice %arg0 { start = array<i64: 0, 0, 0, 0>, size = array<i64: 0, -2, 9, 4> } : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
+// CHECK-LABEL: @test_slice_start_out_of_bound
+func.func @test_slice_start_out_of_bound(%arg0 : tensor<8x8x8x?xi32>) -> () {
+ // CHECK: tosa.slice %arg0 {size = array<i64: 1, 1, 3, 4>, start = array<i64: -1, 8, 6, 8000000>} : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x4xi32>
+ // this checks following
+ // dim 0: start=-1 => inferred output dim is ?
+ // dim 1: start=8 => inferred output dim is ?
+ // dim 2: start+size out of bound: inferred output dim is ?
+ // dim 3: start=8000000, size=4, input dim=? => inferred output dim is 4
+ %2= tosa.slice %arg0 { start = array<i64: -1, 8, 6, 8000000>, size = array<i64: 1, 1, 3, 4> } : (tensor<8x8x8x?xi32>) -> tensor<?x?x?x?xi32>
+ return
+}
+
+// -----
+
// CHECK-LABEL: @test_slice_dynamic
func.func @test_slice_dynamic(%arg0 : tensor<10x?x2xf32>) -> () {
// CHECK: tosa.slice %arg0 {size = array<i64: 7, -1, 1>, start = array<i64: 1, 0, 0>} : (tensor<10x?x2xf32>) -> tensor<7x?x1xf32>
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GeorgeARM
approved these changes
Sep 20, 2024
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This fixes the infer output shape of TOSA slice op for start/size values that are out-of-bound or -1
added tests to check: