[Executorch] Refactor op_add to support op_sub broadcasting

Summary:
Refactor op_add to conslidate commong broadcasting related improvements

Test Plan:
Previously added tests

Reviewers:

Subscribers:

Tasks:

Tags:

ghstack-source-id: b97d3c9
Pull Request resolved: pytorch/executorch#8255

Author: kimishpatel

kernels/optimized/cpu/op_add.cpp

@@ -14,59 +14,11 @@
 #include <executorch/runtime/kernel/kernel_includes.h>
 #include <executorch/runtime/platform/assert.h>
 
+#include <executorch/kernels/optimized/cpu/op_add_sub_impl.h>
+
 namespace torch {
 namespace executor {
 namespace native {
-namespace {
-
-template <
-    bool can_cast,
-    typename CTYPE_A,
-    typename CTYPE_B,
-    typename CTYPE_IN,
-    typename CTYPE_OUT>
-struct AddInner;
-
-template <
-    typename CTYPE_A,
-    typename CTYPE_B,
-    typename CTYPE_IN,
-    typename CTYPE_OUT>
-struct AddInner<true, CTYPE_A, CTYPE_B, CTYPE_IN, CTYPE_OUT> {
-  static void
-  run(const Tensor& a, const Tensor& b, CTYPE_IN alpha_val, Tensor& out) {
-    apply_binary_elementwise_fn<CTYPE_A, CTYPE_B, CTYPE_OUT>(
-        // NOLINTNEXTLINE(facebook-hte-ConstantArgumentPassByValue)
-        [alpha_val](const CTYPE_A val_a, const CTYPE_B val_b) {
-          CTYPE_IN a_casted = static_cast<CTYPE_IN>(val_a);
-          CTYPE_IN b_casted = static_cast<CTYPE_IN>(val_b);
-          CTYPE_IN value = a_casted + alpha_val * b_casted;
-
-          return static_cast<CTYPE_OUT>(value);
-        },
-        a,
-        b,
-        out);
-  }
-};
-
-template <typename CTYPE_IN>
-struct ReportCanCastBug {
-  static void run(const Tensor&, const Tensor&, CTYPE_IN, Tensor&) {
-    ET_DCHECK_MSG(false, "BUG: canCast should have been checked above");
-  }
-};
-
-template <
-    typename CTYPE_A,
-    typename CTYPE_B,
-    typename CTYPE_IN,
-    typename CTYPE_OUT>
-struct AddInner<false, CTYPE_A, CTYPE_B, CTYPE_IN, CTYPE_OUT>
-    : public ReportCanCastBug<CTYPE_IN> {};
-
-} // namespace
-
 using Tensor = executorch::aten::Tensor;
 using ScalarType = executorch::aten::ScalarType;
 
@@ -76,8 +28,6 @@ Tensor& opt_add_out(
     const Tensor& b,
     const Scalar& alpha,
     Tensor& out) {
-  (void)ctx;
-
   ScalarType a_type = a.scalar_type();
   ScalarType b_type = b.scalar_type();
   ScalarType out_type = out.scalar_type();
@@ -95,7 +45,9 @@ Tensor& opt_add_out(
         ET_SWITCH_REALB_TYPES(b_type, ctx, "add.out", CTYPE_B, [&]() {
           CTYPE alpha_val;
           ET_KERNEL_CHECK(
-              ctx, utils::extract_scalar(alpha, &alpha_val), InvalidArgument, );
+              ctx,
+              torch::executor::native::utils::extract_scalar(alpha, &alpha_val),
+              InvalidArgument, );
           CTYPE_B b_val = *b.const_data_ptr<CTYPE_B>();
           CTYPE b_casted = static_cast<CTYPE>(b_val);
 
@@ -115,100 +67,9 @@ Tensor& opt_add_out(
     return opt_add_out(ctx, b, a, alpha, out);
   }
 
-  auto selected_optimized_path = select_optimized_path(a, b, out);
-  if (selected_optimized_path == ElementwiseOptimizedPath::kTreatAs1d) {
-    // Resize for dynamic shape
-    auto error = resize_tensor(out, a.sizes());
-    ET_KERNEL_CHECK_MSG(
-        ctx,
-        error == Error::Ok,
-        InvalidArgument,
-        out,
-        "Failed to resize output tensor.");
-
-    ET_SWITCH_REALB_TYPES(a_type, ctx, "add.out", CTYPE, [&]() {
-      CTYPE alpha_val;
-      ET_KERNEL_CHECK(
-          ctx, utils::extract_scalar(alpha, &alpha_val), InvalidArgument, );
-
-      using Vec = executorch::vec::Vectorized<CTYPE>;
-      executorch::vec::map2<CTYPE>(
-          [alpha_val](Vec x, Vec y) { return x + Vec(alpha_val) * y; },
-          out.mutable_data_ptr<CTYPE>(),
-          a.const_data_ptr<CTYPE>(),
-          b.const_data_ptr<CTYPE>(),
-          out.numel());
-    });
-  } else if (selected_optimized_path != ElementwiseOptimizedPath::kNone) {
-    ET_SWITCH_REALB_TYPES(out_type, ctx, "add.out", CTYPE, [&]() {
-      CTYPE alpha_val;
-      ET_KERNEL_CHECK_MSG(
-          ctx,
-          utils::extract_scalar(alpha, &alpha_val),
-          InvalidArgument,
-          out,
-          "Failed to extract scalar alpha.");
-      using Vec = executorch::vec::Vectorized<CTYPE>;
-      Vec alpha_val_vec(alpha_val);
-      if (selected_optimized_path ==
-              ElementwiseOptimizedPath::kBroadcast2dBy1dReverseArguments ||
-          selected_optimized_path ==
-              ElementwiseOptimizedPath::kBroadcastLastDimReverseArguments ||
-          selected_optimized_path ==
-              ElementwiseOptimizedPath::kBroadcastNdByNdReverseArguments) {
-        // Reason we swap out args here is because handle_broadcast_elementwise
-        // handles this selected_optimized_path option a bit differently.
-        // This should really be resolved in handle_broadcast_elementwise.
-        // However, the current blocker is that handle_broadcast_elementwise
-        // tries to be agnostic of op. This should be fixed, likely by moving
-        // lambda creation to handle_broadcast_elementwise and it be aware of
-        // which op is being executed.
-        auto add_lambda = [&alpha_val_vec](auto x, auto y) {
-          return y + alpha_val_vec * x;
-        };
-        return torch::executor::handle_broadcast_elementwise<CTYPE>(
-            ctx, add_lambda, a, b, out, selected_optimized_path, alpha);
-      } else {
-        auto add_lambda = [&alpha_val_vec](auto x, auto y) {
-          return x + alpha_val_vec * y;
-        };
-        return torch::executor::handle_broadcast_elementwise<CTYPE>(
-            ctx, add_lambda, a, b, out, selected_optimized_path, alpha);
-      }
-    });
-  } else {
-    ScalarType common_type =
-        promoteTypes(a_type, b_type, /*half_to_float*/ true);
-    ET_KERNEL_CHECK(ctx, canCast(common_type, out_type), InvalidArgument, out);
-
-    ET_KERNEL_CHECK(
-        ctx,
-        resize_to_broadcast_target_size(a, b, out) == Error::Ok,
-        InvalidArgument,
-        out);
-
-    ET_SWITCH_REALHBBF16_TYPES(a_type, ctx, "add.out", CTYPE_A, [&]() {
-      ET_SWITCH_REALHBBF16_TYPES(b_type, ctx, "add.out", CTYPE_B, [&]() {
-        using CTYPE_IN = typename torch::executor::
-            promote_types<CTYPE_A, CTYPE_B, /*half_to_float*/ true>::type;
-        ET_DCHECK(CppTypeToScalarType<CTYPE_IN>::value == common_type);
-        ET_SWITCH_REALHBBF16_TYPES(out_type, ctx, "add.out", CTYPE_OUT, [&]() {
-          CTYPE_IN alpha_val;
-          ET_KERNEL_CHECK(
-              ctx, utils::extract_scalar(alpha, &alpha_val), InvalidArgument, );
-
-          AddInner<
-              can_cast<CTYPE_IN, CTYPE_OUT>::value,
-              CTYPE_A,
-              CTYPE_B,
-              CTYPE_IN,
-              CTYPE_OUT>::run(a, b, alpha_val, out);
-        });
-      });
-    });
-  }
-
-  return out;
+  static constexpr const char op_name[] = "add.out";
+  return torch::executor::kernels::impl::opt_add_sub_out_impl<false, op_name>(
+      ctx, a, b, alpha, out);
 }
 
 Tensor& opt_add_scalar_out(