Summary: Minor cleanup post quantized_add op

Test Plan: examples/arm/run.sh --et_build_root=arm_test/test_run --target=ethos-u55-128 --model_name=qadd2 --no_delegate

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Author: Github Executorch

backends/cortex_m/ops/cortex_m_ops_common.h

@@ -17,11 +17,6 @@
 #include <executorch/runtime/kernel/kernel_includes.h>
 #include <executorch/runtime/platform/assert.h>
 
-// Include CMSIS-NN headers with C linkage
-extern "C" {
-#include "arm_nnfunctions.h"
-}
-
 using Tensor = torch::executor::Tensor;
 using ScalarType = executorch::aten::ScalarType;
 using Scalar = torch::executor::Scalar;
@@ -139,3 +134,19 @@ inline Error resize_to_broadcast_target_size(
   return executorch::runtime::resize_tensor(
       output, {expected_output_size, expected_output_dim});
 }
+
+/**
+ * Convert Scalar to CMSIS-NN int32 format
+ * For multipliers, zero_points, etc. from quantize_multiplier_aot
+ */
+inline int32_t extractScalarToInt32(const Scalar& scalar_value) {
+  return static_cast<int32_t>(scalar_value.to<int64_t>());
+}
+
+/**
+ * Convert Scalar to CMSIS-NN int format
+ * For shift values from quantize_multiplier_aot
+ */
+inline int extractScalarToInt(const Scalar& scalar_value) {
+  return static_cast<int>(scalar_value.to<int64_t>());
+}

backends/cortex_m/ops/op_quantized_add.cpp

@@ -8,6 +8,11 @@
 
 #include "cortex_m_ops_common.h"
 
+// Include CMSIS-NN headers with C linkage
+extern "C" {
+#include "arm_nnfunctions.h"
+}
+
 namespace cortex_m {
 namespace native {
 using KernelRuntimeContext = torch::executor::KernelRuntimeContext;
@@ -54,19 +59,15 @@ Tensor& quantized_add_out(
       "quantized_add_out: input1_int8.sizes() = %zu",
       input1_int8.sizes().size());
 
-  // FIX: Use template types that ExecutorTorch definitely provides
-  // Use to<int64_t>() and to<double>() which are commonly instantiated
-  int32_t zp1 = static_cast<int32_t>(input1_zero_point.to<int64_t>());
-  int32_t input1_mult = static_cast<int32_t>(input1_multiplier.to<int64_t>());
-  int input1_shift_val = static_cast<int>(input1_shift.to<int64_t>());
-
-  int32_t zp2 = static_cast<int32_t>(input2_zero_point.to<int64_t>());
-  int32_t input2_mult = static_cast<int32_t>(input2_multiplier.to<int64_t>());
-  int input2_shift_val = static_cast<int>(input2_shift.to<int64_t>());
-
-  int32_t out_zp = static_cast<int32_t>(output_zero_point.to<int64_t>());
-  int32_t output_mult = static_cast<int32_t>(output_multiplier.to<int64_t>());
-  int output_shift_val = static_cast<int>(output_shift.to<int64_t>());
+  int32_t zp1 = extractScalarToInt32(input1_zero_point);
+  int32_t input1_mult = extractScalarToInt32(input1_multiplier);
+  int input1_shift_val = extractScalarToInt(input1_shift);
+  int32_t zp2 = extractScalarToInt32(input2_zero_point);
+  int32_t input2_mult = extractScalarToInt32(input2_multiplier);
+  int input2_shift_val = extractScalarToInt(input2_shift);
+  int32_t out_zp = extractScalarToInt32(output_zero_point);
+  int32_t output_mult = extractScalarToInt32(output_multiplier);
+  int output_shift_val = extractScalarToInt(output_shift);
 
   // Left shift to maximize precision (tune as needed)
   const int32_t left_shift = 20;