[mlir][spirv] Fix serialization of multi-dimensional TensorArm constant (#151158)

This fixes an issue where multi-dimensional TensorArm dense elements
could not be serialized.

Signed-off-by: Mohammadreza Ameri Mahabadian <mohammadreza.amerimahabadian@arm.com>

2 files changed, 47 insertions, 0 deletions

diff --git a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
index 63d3423..737f296 100644
--- a/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
+++ b/mlir/lib/Target/SPIRV/Serialization/Serializer.cpp
@@ -958,6 +958,25 @@ 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 6aca11e..1695d2a 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
 }