[mlir][spirv] Fix serialization of multi-dimensional TensorArm constant #151158
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This fixes an issue where multi-dimensional TensorArm dense elements could not be serialized. Signed-off-by: Mohammadreza Ameri Mahabadian <[email protected]>
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@llvm/pr-subscribers-mlir Author: Mohammadreza Ameri Mahabadian (mahabadm) ChangesThis fixes an issue where multi-dimensional TensorArm dense elements could not be serialized. Full diff: https://github.com/llvm/llvm-project/pull/151158.diff 2 Files Affected:
diff --git a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
index a8a2b2e7cf38c..f31e6881cf994 100644
--- a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
+++ b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
@@ -938,6 +938,25 @@ Serializer::prepareDenseElementsConstant(Location loc, Type constType,
} else {
return 0;
}
+ } else if (isa<spirv::TensorArmType>(constType)) {
+ numberOfConstituents = shapedType.getNumElements();
+ operands.reserve(numberOfConstituents + 2);
+ for (int i = 0; i < numberOfConstituents; ++i) {
+ uint32_t elementID = 0;
+ if (auto attr = dyn_cast<DenseIntElementsAttr>(valueAttr)) {
+ elementID =
+ elementType.isInteger(1)
+ ? prepareConstantBool(loc, attr.getValues<BoolAttr>()[i])
+ : prepareConstantInt(loc, attr.getValues<IntegerAttr>()[i]);
+ }
+ if (auto attr = dyn_cast<DenseFPElementsAttr>(valueAttr)) {
+ elementID = prepareConstantFp(loc, attr.getValues<FloatAttr>()[i]);
+ }
+ if (!elementID) {
+ return 0;
+ }
+ operands.push_back(elementID);
+ }
} else {
operands.reserve(numberOfConstituents + 2);
for (int i = 0; i < numberOfConstituents; ++i) {
diff --git a/mlir/test/Target/SPIRV/constant.mlir b/mlir/test/Target/SPIRV/constant.mlir
index 6aca11ec5e6e6..1695d2a6a2eb4 100644
--- a/mlir/test/Target/SPIRV/constant.mlir
+++ b/mlir/test/Target/SPIRV/constant.mlir
@@ -307,6 +307,34 @@ spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader
spirv.ReturnValue %coop : !spirv.coopmatrix<16x16xi8, Subgroup, MatrixAcc>
}
+ // CHECK-LABEL: @arm_tensor_of_i32
+ spirv.func @arm_tensor_of_i32() -> (!spirv.arm.tensor<2x3xi32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<{{\[}}[1, 2, 3], [4, 5, 6]]> : !spirv.arm.tensor<2x3xi32>
+ %0 = spirv.Constant dense<[[1, 2, 3], [4, 5, 6]]> : !spirv.arm.tensor<2x3xi32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xi32>
+ }
+
+ // CHECK-LABEL: @splat_arm_tensor_of_i32
+ spirv.func @splat_arm_tensor_of_i32() -> (!spirv.arm.tensor<2x3xi32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<2> : !spirv.arm.tensor<2x3xi32>
+ %0 = spirv.Constant dense<2> : !spirv.arm.tensor<2x3xi32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xi32>
+ }
+
+ // CHECK-LABEL: @arm_tensor_of_f32
+ spirv.func @arm_tensor_of_f32() -> (!spirv.arm.tensor<2x3xf32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<{{\[}}[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : !spirv.arm.tensor<2x3xf32>
+ %0 = spirv.Constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]>: !spirv.arm.tensor<2x3xf32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xf32>
+ }
+
+ // CHECK-LABEL: @splat_arm_tensor_of_f32
+ spirv.func @splat_arm_tensor_of_f32() -> (!spirv.arm.tensor<2x3xf32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<2.000000e+00> : !spirv.arm.tensor<2x3xf32>
+ %0 = spirv.Constant dense<2.0> : !spirv.arm.tensor<2x3xf32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xf32>
+ }
+
spirv.EntryPoint "GLCompute" @bool_const
}
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Member
|
@llvm/pr-subscribers-mlir-spirv Author: Mohammadreza Ameri Mahabadian (mahabadm) ChangesThis fixes an issue where multi-dimensional TensorArm dense elements could not be serialized. Full diff: https://github.com/llvm/llvm-project/pull/151158.diff 2 Files Affected:
diff --git a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
index a8a2b2e7cf38c..f31e6881cf994 100644
--- a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
+++ b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
@@ -938,6 +938,25 @@ Serializer::prepareDenseElementsConstant(Location loc, Type constType,
} else {
return 0;
}
+ } else if (isa<spirv::TensorArmType>(constType)) {
+ numberOfConstituents = shapedType.getNumElements();
+ operands.reserve(numberOfConstituents + 2);
+ for (int i = 0; i < numberOfConstituents; ++i) {
+ uint32_t elementID = 0;
+ if (auto attr = dyn_cast<DenseIntElementsAttr>(valueAttr)) {
+ elementID =
+ elementType.isInteger(1)
+ ? prepareConstantBool(loc, attr.getValues<BoolAttr>()[i])
+ : prepareConstantInt(loc, attr.getValues<IntegerAttr>()[i]);
+ }
+ if (auto attr = dyn_cast<DenseFPElementsAttr>(valueAttr)) {
+ elementID = prepareConstantFp(loc, attr.getValues<FloatAttr>()[i]);
+ }
+ if (!elementID) {
+ return 0;
+ }
+ operands.push_back(elementID);
+ }
} else {
operands.reserve(numberOfConstituents + 2);
for (int i = 0; i < numberOfConstituents; ++i) {
diff --git a/mlir/test/Target/SPIRV/constant.mlir b/mlir/test/Target/SPIRV/constant.mlir
index 6aca11ec5e6e6..1695d2a6a2eb4 100644
--- a/mlir/test/Target/SPIRV/constant.mlir
+++ b/mlir/test/Target/SPIRV/constant.mlir
@@ -307,6 +307,34 @@ spirv.module Logical Vulkan requires #spirv.vce<v1.3, [VulkanMemoryModel, Shader
spirv.ReturnValue %coop : !spirv.coopmatrix<16x16xi8, Subgroup, MatrixAcc>
}
+ // CHECK-LABEL: @arm_tensor_of_i32
+ spirv.func @arm_tensor_of_i32() -> (!spirv.arm.tensor<2x3xi32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<{{\[}}[1, 2, 3], [4, 5, 6]]> : !spirv.arm.tensor<2x3xi32>
+ %0 = spirv.Constant dense<[[1, 2, 3], [4, 5, 6]]> : !spirv.arm.tensor<2x3xi32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xi32>
+ }
+
+ // CHECK-LABEL: @splat_arm_tensor_of_i32
+ spirv.func @splat_arm_tensor_of_i32() -> (!spirv.arm.tensor<2x3xi32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<2> : !spirv.arm.tensor<2x3xi32>
+ %0 = spirv.Constant dense<2> : !spirv.arm.tensor<2x3xi32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xi32>
+ }
+
+ // CHECK-LABEL: @arm_tensor_of_f32
+ spirv.func @arm_tensor_of_f32() -> (!spirv.arm.tensor<2x3xf32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<{{\[}}[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : !spirv.arm.tensor<2x3xf32>
+ %0 = spirv.Constant dense<[[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]]>: !spirv.arm.tensor<2x3xf32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xf32>
+ }
+
+ // CHECK-LABEL: @splat_arm_tensor_of_f32
+ spirv.func @splat_arm_tensor_of_f32() -> (!spirv.arm.tensor<2x3xf32>) "None" {
+ // CHECK: {{%.*}} = spirv.Constant dense<2.000000e+00> : !spirv.arm.tensor<2x3xf32>
+ %0 = spirv.Constant dense<2.0> : !spirv.arm.tensor<2x3xf32>
+ spirv.ReturnValue %0 : !spirv.arm.tensor<2x3xf32>
+ }
+
spirv.EntryPoint "GLCompute" @bool_const
}
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kuhar
approved these changes
Jul 29, 2025
Contributor
Author
|
@kuhar Many thanks for your approval. Can this be merged please? Thanks. |
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This fixes an issue where multi-dimensional TensorArm dense elements could not be serialized.