Remove ExecuTorch copy of Vectorized

extension/llm/custom_ops/op_sdpa.cpp

@@ -8,9 +8,10 @@
 
 #include <executorch/extension/llm/custom_ops/op_sdpa.h>
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/blas/CPUBlas.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/runtime/core/exec_aten/util/dim_order_util.h>
 // @lint-ignore CLANGTIDY facebook-unused-include-check
 #include <executorch/runtime/core/exec_aten/util/scalar_type_util.h>
@@ -34,18 +35,10 @@ namespace util {
 constexpr size_t kKVDim = 4;
 
 template <typename T>
-inline void _store(T* dst, ::executorch::vec::Vectorized<T> src) {
+inline void _store(T* dst, ::at::vec::Vectorized<T> src) {
   src.store(dst);
 }
 
-/*
-inline void _store(::Half* dst, at::vec::Vectorized<float> src) {
-  //fp16_ieee_to_fp32_value
-  auto res = at::vec::convert_float_half(src, src);
-  res.store(dst, at::vec::Vectorized<float>::size());
-}
-*/
-
 template <typename T>
 inline T data_index_init(T offset) {
   return offset;
@@ -78,7 +71,7 @@ inline double calculate_scale(const Tensor& query, optional<double> scale) {
 }
 
 } // namespace util
-namespace vec = ::executorch::vec;
+namespace vec = ::at::vec;
 using Tensor = exec_aten::Tensor;
 
 namespace {

kernels/optimized/cpu/moments_utils.h

@@ -12,7 +12,7 @@
 // for use in optimized ExecuTorch ops. Template specializations of BFloat16
 // are excluded.
 
-#include <executorch/kernels/optimized/vec/vec.h>
+#include <ATen/cpu/vec/vec.h>
 
 #include <executorch/kernels/optimized/utils/math_utils.h>
 #include <executorch/runtime/platform/compiler.h>
@@ -47,12 +47,12 @@ void AddMoments(
 template <typename T>
 ET_INLINE void AddMomentsVec(
     int64_t m0_add,
-    const executorch::vec::Vectorized<T>& m1_add,
-    const executorch::vec::Vectorized<T>& m2_add,
+    const at::vec::Vectorized<T>& m1_add,
+    const at::vec::Vectorized<T>& m2_add,
     int64_t& m0,
-    executorch::vec::Vectorized<T>& m1,
-    executorch::vec::Vectorized<T>& m2) {
-  using Vec = executorch::vec::Vectorized<T>;
+    at::vec::Vectorized<T>& m1,
+    at::vec::Vectorized<T>& m2) {
+  using Vec = at::vec::Vectorized<T>;
   const int64_t n = m0 + m0_add;
   const T c =
       n == 0 ? static_cast<T>(0) : static_cast<T>(m0_add) / static_cast<T>(n);
@@ -67,11 +67,11 @@ template <typename T>
 inline void UpdateMomentsVec(
     int64_t m0,
     const T* X_ptr,
-    const std::array<executorch::vec::Vectorized<acc_t<T>>, kChunkSize>& c_vecs,
+    const std::array<at::vec::Vectorized<acc_t<T>>, kChunkSize>& c_vecs,
     int64_t& m0_stk0,
-    executorch::vec::Vectorized<acc_t<T>>& m1_stk0,
-    executorch::vec::Vectorized<acc_t<T>>& m2_stk0) {
-  using Vec = executorch::vec::Vectorized<acc_t<T>>;
+    at::vec::Vectorized<acc_t<T>>& m1_stk0,
+    at::vec::Vectorized<acc_t<T>>& m2_stk0) {
+  using Vec = at::vec::Vectorized<acc_t<T>>;
   Vec m1_vec(0);
   Vec m2_vec(0);
   for (int64_t j = 0; j < m0; ++j) {
@@ -92,13 +92,13 @@ std::pair<acc_t<T>, acc_t<T>>
 RowwiseMomentsImpl(const T* X, int64_t N, int64_t ddof = 0) {
   using T_ACC = acc_t<T>;
 
-  constexpr int64_t kVecSize = executorch::vec::Vectorized<T>::size();
-  constexpr int64_t kAccVecSize = executorch::vec::Vectorized<T_ACC>::size();
+  constexpr int64_t kVecSize = at::vec::Vectorized<T>::size();
+  constexpr int64_t kAccVecSize = at::vec::Vectorized<T_ACC>::size();
   const int64_t n = N / kVecSize;
   const int64_t m = executorch::utils::divup(n, kChunkSize);
   const int64_t depth = executorch::utils::CeilLog2(m);
 
-  using Vec = executorch::vec::Vectorized<T_ACC>;
+  using Vec = at::vec::Vectorized<T_ACC>;
   const Vec kZeroVec(T_ACC(0));
   std::array<int64_t, kMaxDepth> m0_stk;
   std::array<Vec, kMaxDepth> m1_stk;
@@ -168,7 +168,7 @@ RowwiseMomentsImpl(const T* X, int64_t N, int64_t ddof = 0) {
 template <typename T>
 std::pair<acc_t<T>, acc_t<T>>
 RowwiseMoments(const T* X, int64_t N, int64_t ddof = 0) {
-  using Vec = executorch::vec::Vectorized<T>;
+  using Vec = at::vec::Vectorized<T>;
   constexpr int64_t kVecSize = Vec::size();
   const int64_t n = N / kVecSize;
   const int64_t m = executorch::utils::divup(n, kChunkSize);

kernels/optimized/cpu/op_add.cpp

@@ -6,9 +6,10 @@
  * LICENSE file in the root directory of this source tree.
  */
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/cpu/binary_ops.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/kernels/portable/cpu/scalar_utils.h>
 #include <executorch/kernels/portable/cpu/util/broadcast_util.h>
 #include <executorch/runtime/kernel/kernel_includes.h>
@@ -99,8 +100,8 @@ Tensor& opt_add_out(
           CTYPE_B b_val = *b.const_data_ptr<CTYPE_B>();
           CTYPE b_casted = static_cast<CTYPE>(b_val);
 
-          using Vec = executorch::vec::Vectorized<CTYPE>;
-          executorch::vec::map<CTYPE>(
+          using Vec = at::vec::Vectorized<CTYPE>;
+          at::vec::map<CTYPE>(
               [alpha_val, b_casted](Vec x) {
                 return x + Vec(alpha_val * b_casted);
               },
@@ -131,8 +132,8 @@ Tensor& opt_add_out(
       ET_KERNEL_CHECK(
           ctx, utils::extract_scalar(alpha, &alpha_val), InvalidArgument, );
 
-      using Vec = executorch::vec::Vectorized<CTYPE>;
-      executorch::vec::map2<CTYPE>(
+      using Vec = at::vec::Vectorized<CTYPE>;
+      at::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>(),
@@ -166,7 +167,7 @@ Tensor& opt_add_out(
       ET_KERNEL_CHECK(
           ctx, utils::extract_scalar(alpha, &alpha_val), InvalidArgument, );
 
-      using Vec = executorch::vec::Vectorized<CTYPE>;
+      using Vec = at::vec::Vectorized<CTYPE>;
       executorch::vec::broadcasting_map_2d_by_1d<CTYPE>(
           [alpha_val](Vec x, Vec y) { return x + Vec(alpha_val) * y; },
           out.mutable_data_ptr<CTYPE>(),
@@ -244,8 +245,8 @@ Tensor& opt_add_scalar_out(
         CTYPE alpha_val;
         ET_EXTRACT_SCALAR(alpha, alpha_val);
 
-        using Vec = executorch::vec::Vectorized<CTYPE>;
-        executorch::vec::map<CTYPE>(
+        using Vec = at::vec::Vectorized<CTYPE>;
+        at::vec::map<CTYPE>(
             [alpha_val, b_casted](Vec x) {
               return x + Vec(alpha_val * b_casted);
             },

kernels/optimized/cpu/op_div.cpp

@@ -6,9 +6,10 @@
  * LICENSE file in the root directory of this source tree.
  */
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/cpu/binary_ops.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/kernels/portable/cpu/scalar_utils.h>
 #include <executorch/kernels/portable/cpu/util/broadcast_util.h>
 #include <executorch/runtime/kernel/kernel_includes.h>
@@ -76,16 +77,16 @@ Tensor& opt_div_out(
           CTYPE_SCALAR scalar_val = *scalar->const_data_ptr<CTYPE_SCALAR>();
           CTYPE scalar_casted = static_cast<CTYPE>(scalar_val);
 
-          using Vec = executorch::vec::Vectorized<CTYPE>;
+          using Vec = at::vec::Vectorized<CTYPE>;
           if (a.numel() == 1) {
-            executorch::vec::map<CTYPE>(
+            at::vec::map<CTYPE>(
                 [scalar_casted](Vec x) { return Vec(scalar_casted) / x; },
                 out.mutable_data_ptr<CTYPE>(),
                 tensor->const_data_ptr<CTYPE>(),
                 out.numel());
           } else {
             Vec inv_scalar_casted_vec(CTYPE(1) / scalar_casted);
-            executorch::vec::map<CTYPE>(
+            at::vec::map<CTYPE>(
                 [inv_scalar_casted_vec](Vec x) {
                   return x * inv_scalar_casted_vec;
                 },
@@ -111,8 +112,8 @@ Tensor& opt_div_out(
         "Failed to resize output tensor.");
 
     ET_SWITCH_REAL_TYPES_AND(Bool, out_type, ctx, "div.out", CTYPE, [&]() {
-      using Vec = executorch::vec::Vectorized<CTYPE>;
-      executorch::vec::map2<CTYPE>(
+      using Vec = at::vec::Vectorized<CTYPE>;
+      at::vec::map2<CTYPE>(
           [](Vec x, Vec y) { return x / y; },
           out.mutable_data_ptr<CTYPE>(),
           a.const_data_ptr<CTYPE>(),
@@ -142,7 +143,7 @@ Tensor& opt_div_out(
         out,
         "Failed to resize output tensor.");
     ET_SWITCH_REALB_TYPES(out_type, ctx, "sub.out", CTYPE, [&]() {
-      using Vec = executorch::vec::Vectorized<CTYPE>;
+      using Vec = at::vec::Vectorized<CTYPE>;
       if (selected_optimized_path ==
           ElementwiseOptimizedPath::kBroadcast2dBy1dReverseArguments) {
         executorch::vec::broadcasting_map_2d_by_1d<CTYPE>(
@@ -222,9 +223,9 @@ Tensor& opt_div_scalar_out(
             ET_EXTRACT_SCALAR(b, b_val);
             CTYPE b_casted = static_cast<CTYPE>(b_val);
 
-            using Vec = executorch::vec::Vectorized<CTYPE>;
+            using Vec = at::vec::Vectorized<CTYPE>;
             Vec inv_b_casted_vec(CTYPE(1) / b_casted);
-            executorch::vec::map<CTYPE>(
+            at::vec::map<CTYPE>(
                 [inv_b_casted_vec](Vec x) { return x * inv_b_casted_vec; },
                 out.mutable_data_ptr<CTYPE>(),
                 a.const_data_ptr<CTYPE>(),

kernels/optimized/cpu/op_exp.cpp

@@ -8,8 +8,9 @@
 
 #include <cmath>
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/runtime/kernel/kernel_includes.h>
 
 namespace torch {
@@ -34,8 +35,8 @@ void exp_data(
     const CTYPE_IN* in_data,
     const size_t numel,
     CTYPE_OUT* out_data) {
-  using Vec = executorch::vec::Vectorized<CTYPE_IN>;
-  executorch::vec::map<CTYPE_IN>(
+  using Vec = at::vec::Vectorized<CTYPE_IN>;
+  at::vec::map<CTYPE_IN>(
       [](Vec x) { return x.exp(); }, out_data, in_data, numel);
 }
 

kernels/optimized/cpu/op_le.cpp

@@ -6,8 +6,9 @@
  * LICENSE file in the root directory of this source tree.
  */
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/kernels/portable/cpu/scalar_utils.h>
 #include <executorch/runtime/kernel/kernel_includes.h>
 #include <executorch/runtime/platform/assert.h>
@@ -44,8 +45,8 @@ Tensor& opt_le_tensor_out(
   if (a_type == b_type && a_type == out_type) {
     ET_SWITCH_REAL_TYPES_AND(
         Bool, out_type, ctx, "le.Tensor_out", CTYPE, [&]() {
-          using Vec = executorch::vec::Vectorized<CTYPE>;
-          executorch::vec::map2<CTYPE>(
+          using Vec = at::vec::Vectorized<CTYPE>;
+          at::vec::map2<CTYPE>(
               [](Vec x, Vec y) { return x.le(y); },
               out.mutable_data_ptr<CTYPE>(),
               a.const_data_ptr<CTYPE>(),
@@ -109,8 +110,8 @@ Tensor& opt_le_scalar_out(
             CTYPE_B b_val = 0;
             ET_EXTRACT_SCALAR(b, b_val);
             CTYPE b_casted = static_cast<CTYPE>(b_val);
-            using Vec = executorch::vec::Vectorized<CTYPE>;
-            executorch::vec::map<CTYPE>(
+            using Vec = at::vec::Vectorized<CTYPE>;
+            at::vec::map<CTYPE>(
                 [b_casted](Vec x) { return x.le(Vec(b_casted)); },
                 out.mutable_data_ptr<CTYPE>(),
                 a.const_data_ptr<CTYPE>(),

kernels/optimized/cpu/op_mul.cpp

@@ -6,9 +6,10 @@
  * LICENSE file in the root directory of this source tree.
  */
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/cpu/binary_ops.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/kernels/portable/cpu/scalar_utils.h>
 #include <executorch/kernels/portable/cpu/util/broadcast_util.h>
 #include <executorch/runtime/core/exec_aten/util/tensor_util.h> // IWYU pragma: export
@@ -95,7 +96,7 @@ Tensor& handle_last_dim_broadcast(
   const size_t outer_size = getLeadingDims(out, out.dim() - 1);
   const auto broadcast_size = out.size(out.dim() - 1);
   ET_SWITCH_REALB_TYPES(out_type, ctx, "mul.out", CTYPE, [&]() {
-    using Vec = executorch::vec::Vectorized<CTYPE>;
+    using Vec = at::vec::Vectorized<CTYPE>;
     executorch::vec::broadcasting_map_broadcast_last_dim<CTYPE>(
         [](Vec x, Vec y) { return x * y; },
         out.mutable_data_ptr<CTYPE>(),
@@ -164,7 +165,7 @@ Tensor& handle_broadcast_mul(
     inner_size = lhs->sizes()[lhs->dim() - 1];
   }
   ET_SWITCH_REALB_TYPES(out_type, ctx, "mul.out", CTYPE, [&]() {
-    using Vec = executorch::vec::Vectorized<CTYPE>;
+    using Vec = at::vec::Vectorized<CTYPE>;
     executorch::vec::broadcasting_map_3d_and_unsqueezed_3d<CTYPE>(
         [](Vec x, Vec y) { return x * y; },
         out.mutable_data_ptr<CTYPE>(),
@@ -203,8 +204,8 @@ Tensor& opt_mul_out(
           CTYPE_B b_val = *b.const_data_ptr<CTYPE_B>();
           CTYPE b_casted = static_cast<CTYPE>(b_val);
 
-          using Vec = executorch::vec::Vectorized<CTYPE>;
-          executorch::vec::map<CTYPE>(
+          using Vec = at::vec::Vectorized<CTYPE>;
+          at::vec::map<CTYPE>(
               [b_casted](Vec x) { return x * Vec(b_casted); },
               out.mutable_data_ptr<CTYPE>(),
               a.const_data_ptr<CTYPE>(),
@@ -229,8 +230,8 @@ Tensor& opt_mul_out(
         "Failed to resize output tensor.");
 
     ET_SWITCH_REALB_TYPES(out_type, ctx, "mul.out", CTYPE, [&]() {
-      using Vec = executorch::vec::Vectorized<CTYPE>;
-      executorch::vec::map2<CTYPE>(
+      using Vec = at::vec::Vectorized<CTYPE>;
+      at::vec::map2<CTYPE>(
           [](Vec x, Vec y) { return x * y; },
           out.mutable_data_ptr<CTYPE>(),
           a.const_data_ptr<CTYPE>(),
@@ -306,8 +307,8 @@ Tensor& opt_mul_scalar_out(
         ET_EXTRACT_SCALAR(b, b_val);
         CTYPE b_casted = static_cast<CTYPE>(b_val);
 
-        using Vec = executorch::vec::Vectorized<CTYPE>;
-        executorch::vec::map<CTYPE>(
+        using Vec = at::vec::Vectorized<CTYPE>;
+        at::vec::map<CTYPE>(
             [b_casted](Vec x) { return x * Vec(b_casted); },
             out.mutable_data_ptr<CTYPE>(),
             a.const_data_ptr<CTYPE>(),

kernels/optimized/cpu/op_native_layer_norm.cpp

@@ -10,9 +10,10 @@
 #include <cmath>
 #include <tuple>
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/cpu/moments_utils.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/kernels/portable/cpu/util/normalization_ops_util.h>
 
 namespace torch {
@@ -33,7 +34,7 @@ void layer_norm(
     Tensor& out,
     Tensor& mean,
     Tensor& rstd) {
-  using Vec = executorch::vec::Vectorized<CTYPE>;
+  using Vec = at::vec::Vectorized<CTYPE>;
 
   const size_t dim = input.dim() - normalized_shape.size();
   const size_t dim_size = input.size(dim);
@@ -93,7 +94,7 @@ void layer_norm(
         dst_ptr[j] = (src_ptr[j] * scale + offset) * gamma_v + beta_v;
       }
     } else {
-      executorch::vec::map3<CTYPE>(
+      at::vec::map3<CTYPE>(
           [scale, offset](Vec x, Vec gamma, Vec beta) {
             return (x * Vec(scale) + Vec(offset)) * gamma + beta;
           },

kernels/optimized/cpu/op_neg.cpp

@@ -6,8 +6,9 @@
  * LICENSE file in the root directory of this source tree.
  */
 
+#include <ATen/cpu/vec/functional.h>
+#include <ATen/cpu/vec/vec.h>
 #include <executorch/kernels/optimized/vec/functional.h>
-#include <executorch/kernels/optimized/vec/vec.h>
 #include <executorch/runtime/kernel/kernel_includes.h>
 
 namespace torch {
@@ -27,8 +28,8 @@ Tensor& opt_neg_out(KernelRuntimeContext& ctx, const Tensor& in, Tensor& out) {
       "Failed to resize output tensor.");
 
   ET_SWITCH_REAL_TYPES(in.scalar_type(), ctx, "neg.out", CTYPE, [&] {
-    using Vec = executorch::vec::Vectorized<CTYPE>;
-    executorch::vec::map<CTYPE>(
+    using Vec = at::vec::Vectorized<CTYPE>;
+    at::vec::map<CTYPE>(
         [](Vec x) { return x.neg(); },
         out.mutable_data_ptr<CTYPE>(),
         in.const_data_ptr<CTYPE>(),