Remove ExecuTorch copy of Vectorized#11613

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Merged
swolchok merged 1 commit into from
Jun 12, 2025
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Remove ExecuTorch copy of Vectorized #11613

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2 changes: 1 addition & 1 deletion .ci/scripts/test_llava.sh
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Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

# verify result.txt
RESULT=$(cat result.txt)
EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down
4 changes: 3 additions & 1 deletion .ci/scripts/unittest-buck2.sh
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Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down
4 changes: 3 additions & 1 deletion extension/llm/custom_ops/CMakeLists.txt
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Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
)
target_include_directories(
custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
${TORCH_INCLUDE_DIRS}
)
# TODO: This only works if we install portable_lib.so to
# <site-packages>/executorch/extension/pybindings/.
Expand Down
4 changes: 2 additions & 2 deletions extension/llm/custom_ops/op_sdpa.cpp
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Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down
40 changes: 28 additions & 12 deletions extension/llm/custom_ops/op_sdpa_impl.h
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Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
auto vec_size = vec::Vectorized<T1>::size();
auto vec_max = vec::Vectorized<T1>(val);
// NOTE: we observed numerics issues with this function when
// deleting the old executorch::vec and replacing with at::vec
// here. The major known difference is that executorch::vec was 256
// bits wide vs 128 bits for at::vec (and the hardware). Preserving
// this function's execution width at 256 bits and avoiding
// vec_reduce_all below removed the issues.
constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
auto vec_max = vec::VectorizedN<T1, 2>(val);
T1 tmp_sum = 0;
auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
auto tmp1 = tmp0 - vec_max;
// Replace with exp_u20 later
// auto tmp2 = tmp1.exp_u20();
auto tmp2 = tmp1.exp();
vec_tmp_sum += tmp2;
_store(out + i, tmp2);
vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
}
tmp_sum = vec::vec_reduce_all<T1>(
[](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
vec_tmp_sum);

__at_align__ T1 vec_tmp_sum_array[vec_size];
vec_tmp_sum.store(vec_tmp_sum_array);
for (const auto i : c10::irange(vec_size)) {
tmp_sum += vec_tmp_sum_array[i];
}
// See NOTE above; we should replace the scalar reduction above with
// this reduction (which uses vaddvq_f32 internally), but it changes
// numerics.
// tmp_sum = vec::vec_reduce_all<T1>(
// [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
// vec_tmp_sum);
for (int i = vec_size * (size / vec_size); i < size; i++) {
auto tmp0 = a[i];
auto tmp1 = tmp0 - val;
Expand Down
28 changes: 14 additions & 14 deletions kernels/optimized/cpu/moments_utils.h
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Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down
12 changes: 6 additions & 6 deletions kernels/optimized/cpu/op_add.cpp
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Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
},
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
},
Expand Down
10 changes: 5 additions & 5 deletions kernels/optimized/cpu/op_add_sub_impl.h
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Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
if constexpr (is_sub) {
alpha_val = -alpha_val;
}
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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
InvalidArgument,
out,
"Failed to extract scalar alpha.");
using Vec = executorch::vec::Vectorized<CTYPE>;
using Vec = at::vec::Vectorized<CTYPE>;
Vec alpha_val_vec(alpha_val);
if constexpr (is_sub) {
if (selected_optimized_path ==
Expand Down
18 changes: 9 additions & 9 deletions kernels/optimized/cpu/op_div.cpp
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Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
},
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down
8 changes: 4 additions & 4 deletions kernels/optimized/cpu/op_exp.cpp
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Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down
18 changes: 9 additions & 9 deletions kernels/optimized/cpu/op_le.cpp
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Expand Up@@ -6,8 +6,8 @@
* LICENSE file in the root directory of this source tree.
*/

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
out.mutable_data_ptr<CTYPE>(),
tensor->const_data_ptr<CTYPE>(),
out.numel());
} else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
[scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
out.mutable_data_ptr<CTYPE>(),
tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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Remove ExecuTorch copy of Vectorized#11613

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 Merged

swolchok
merged 1 commit into

from

Jun 12, 2025
 Merged


Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
 Merged


Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
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Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
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Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
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Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
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} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
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Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
Loading

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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 Merged

swolchok
merged 1 commit into

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Jun 12, 2025
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Remove ExecuTorch copy of Vectorized
#11613
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2 changes: 1 addition & 1 deletion
.ci/scripts/test_llava.sh

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -147,7 +147,7 @@ run_and_verify() {

 # verify result.txt
 RESULT=$(cat result.txt)
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with several players on the court. "
 EXPECTED_PREFIX="ASSISTANT: image captures a basketball game in progress, with"

 if [[ "${RESULT}" == *"${EXPECTED_PREFIX}"* ]]; then
 echo "Expected result prefix: ${EXPECTED_PREFIX}"
Expand Down

4 changes: 3 additions & 1 deletion
.ci/scripts/unittest-buck2.sh

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Original file line numberDiff line numberDiff line change
Expand Up@@ -15,8 +15,10 @@ buck2 query "//backends/apple/... + //backends/example/... + \
//kernels/optimized/... + //kernels/portable/... + //kernels/quantized/... + \
//kernels/test/... + //runtime/... + //schema/... + //test/... + //util/..."

# TODO: optimized ops are unbuildable because they now use ATen; put
# them back after we can use PyTorch in OSS buck.
UNBUILDABLE_OPTIMIZED_OPS_REGEX="_elu|gelu|fft|log_softmax"
BUILDABLE_OPTIMIZED_OPS=$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)
BUILDABLE_OPTIMIZED_OPS= #$(buck2 query //kernels/optimized/cpu/... | grep -E -v $UNBUILDABLE_OPTIMIZED_OPS_REGEX)

# TODO: build prim_ops_test_cpp again once supported_features works in
# OSS buck.
Expand Down

4 changes: 3 additions & 1 deletion
extension/llm/custom_ops/CMakeLists.txt

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Original file line numberDiff line numberDiff line change
Expand Up@@ -70,10 +70,11 @@ else()
endif()

add_library(custom_ops ${_custom_ops__srcs})

find_package_torch_headers()
target_include_directories(custom_ops PUBLIC "${_common_include_directories}")
target_include_directories(
 custom_ops PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
)
target_link_libraries(custom_ops PUBLIC ${custom_ops_libs} executorch_core)

Expand All@@ -99,6 +100,7 @@ if(EXECUTORCH_BUILD_KERNELS_CUSTOM_AOT)
 )
 target_include_directories(
 custom_ops_aot_lib PRIVATE "${CMAKE_CURRENT_BINARY_DIR}/../../../include"
 ${TORCH_INCLUDE_DIRS}
 )
 # TODO: This only works if we install portable_lib.so to
 # <site-packages>/executorch/extension/pybindings/.
Expand Down

4 changes: 2 additions & 2 deletions
extension/llm/custom_ops/op_sdpa.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -9,9 +9,9 @@
#include <executorch/extension/llm/custom_ops/op_sdpa.h>
#include <executorch/extension/llm/custom_ops/op_sdpa_impl.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>
Expand Down

40 changes: 28 additions & 12 deletions
extension/llm/custom_ops/op_sdpa_impl.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -8,9 +8,10 @@

#pragma once

#include <ATen/cpu/vec/vec.h>
#include <ATen/cpu/vec/vec_n.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>
Expand DownExpand Up@@ -319,7 +320,7 @@ void _qk_at_v_gemm(
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);
}

Expand DownExpand Up@@ -356,30 +357,45 @@ inline double calculate_scale(
 return softmax_scale;
}

namespace vec = ::executorch::vec;
namespace vec = ::at::vec;
using Tensor = ::executorch::aten::Tensor;

// 1) out = exp(a - val)
// 2) val = sum(out)
template <typename T1, typename T2>
inline void
_exp_reduce_sum_fusion_kernel(T1* a, const int& size, T2* out, T1& val) {
 auto vec_size = vec::Vectorized<T1>::size();
 auto vec_max = vec::Vectorized<T1>(val);
 // NOTE: we observed numerics issues with this function when
 // deleting the old executorch::vec and replacing with at::vec
 // here. The major known difference is that executorch::vec was 256
 // bits wide vs 128 bits for at::vec (and the hardware). Preserving
 // this function's execution width at 256 bits and avoiding
 // vec_reduce_all below removed the issues.
 constexpr auto vec_size = vec::Vectorized<T1>::size() * 2;
 auto vec_max = vec::VectorizedN<T1, 2>(val);
 T1 tmp_sum = 0;
 auto vec_tmp_sum = vec::Vectorized<T1>(tmp_sum);
 auto vec_tmp_sum = vec::VectorizedN<T1, 2>(tmp_sum);
 for (int i = 0; i < vec_size * (size / vec_size); i += vec_size) {
 auto tmp0 = vec::Vectorized<T1>::loadu(a + i);
 auto tmp0 = vec::VectorizedN<T1, 2>::loadu(a + i);
 auto tmp1 = tmp0 - vec_max;
 // Replace with exp_u20 later
 // auto tmp2 = tmp1.exp_u20();
 auto tmp2 = tmp1.exp();
 vec_tmp_sum += tmp2;
_store(out + i, tmp2);
 vec_tmp_sum = vec_tmp_sum + tmp2;
tmp2.store(out + i);
 }
 tmp_sum = vec::vec_reduce_all<T1>(
 [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 vec_tmp_sum);

 __at_align__ T1 vec_tmp_sum_array[vec_size];
 vec_tmp_sum.store(vec_tmp_sum_array);
 for (const auto i : c10::irange(vec_size)) {
 tmp_sum += vec_tmp_sum_array[i];
 }
 // See NOTE above; we should replace the scalar reduction above with
 // this reduction (which uses vaddvq_f32 internally), but it changes
 // numerics.
 // tmp_sum = vec::vec_reduce_all<T1>(
 // [](vec::Vectorized<T1>& x, vec::Vectorized<T1>& y) { return x + y; },
 // vec_tmp_sum);
 for (int i = vec_size * (size / vec_size); i < size; i++) {
 auto tmp0 = a[i];
 auto tmp1 = tmp0 - val;
Expand Down

28 changes: 14 additions & 14 deletions
kernels/optimized/cpu/moments_utils.h

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Original file line numberDiff line numberDiff line change
Expand Up@@ -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>
Expand DownExpand Up@@ -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);
Expand All@@ -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) {
Expand All@@ -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;
Expand DownExpand Up@@ -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);
Expand Down

12 changes: 6 additions & 6 deletions
kernels/optimized/cpu/op_add.cpp

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -51,8 +51,8 @@ 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);
 },
Expand DownExpand Up@@ -106,8 +106,8 @@ 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);
 },
Expand Down

10 changes: 5 additions & 5 deletions
kernels/optimized/cpu/op_add_sub_impl.h

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -104,8 +104,8 @@ Tensor& opt_add_sub_out_impl(
 if constexpr (is_sub) {
 alpha_val = -alpha_val;
 }
 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>(),
Expand All@@ -123,7 +123,7 @@ Tensor& opt_add_sub_out_impl(
 InvalidArgument,
 out,
 "Failed to extract scalar alpha.");
 using Vec = executorch::vec::Vectorized<CTYPE>;
 using Vec = at::vec::Vectorized<CTYPE>;
 Vec alpha_val_vec(alpha_val);
 if constexpr (is_sub) {
 if (selected_optimized_path ==
Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_div.cpp

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +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/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>
Expand DownExpand Up@@ -76,16 +76,16 @@ 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;
 },
Expand All@@ -111,8 +111,8 @@ 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>(),
Expand DownExpand Up@@ -198,9 +198,9 @@ 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>(),
Expand Down

8 changes: 4 additions & 4 deletions
kernels/optimized/cpu/op_exp.cpp

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -8,8 +8,8 @@

#include <cmath>

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/vec/vec.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
Expand All@@ -34,8 +34,8 @@ 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);
}

Expand Down

18 changes: 9 additions & 9 deletions
kernels/optimized/cpu/op_le.cpp

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,8 +6,8 @@
 * LICENSE file in the root directory of this source tree.
 */

#include <executorch/kernels/optimized/vec/functional.h>
#include <executorch/kernels/optimized/vec/vec.h>
#include <ATen/cpu/vec/functional.h>
#include <ATen/cpu/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>
Expand DownExpand Up@@ -60,15 +60,15 @@ Tensor& opt_le_tensor_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).le(x); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
 out.numel());
 } else {
executorch::vec::map<CTYPE>(
at::vec::map<CTYPE>(
 [scalar_casted](Vec x) { return x.le(Vec(scalar_casted)); },
 out.mutable_data_ptr<CTYPE>(),
 tensor->const_data_ptr<CTYPE>(),
Expand All@@ -93,8 +93,8 @@ 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>(),
Expand DownExpand Up@@ -158,8 +158,8 @@ 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>(),
Expand Down
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