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Revert exposed_as_util functionality and refactor stack utils #13822

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Merged
merged 1 commit into from
Sep 4, 2025
Merged

Revert exposed_as_util functionality and refactor stack utils #13822

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72 changes: 0 additions & 72 deletions kernels/portable/cpu/op_add.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,6 @@
namespace torch {
namespace executor {
namespace native {
namespace impl {

Tensor& add_out(
KernelRuntimeContext& ctx,
Expand Down Expand Up @@ -152,77 +151,6 @@ Tensor& add_scalar_out(
return out;
}

} // namespace impl

Tensor& add_out(
KernelRuntimeContext& ctx,
const Tensor& a,
const Tensor& b,
const Scalar& alpha,
Tensor& out) {
return impl::add_out(ctx, a, b, alpha, out);
}

Tensor& add_scalar_out(
KernelRuntimeContext& ctx,
const Tensor& a,
const Scalar& b,
const Scalar& alpha,
Tensor& out) {
return impl::add_scalar_out(ctx, a, b, alpha, out);
}

namespace utils {

Tensor& add_out(
KernelRuntimeContext& ctx,
const Tensor& a,
const Tensor& b,
const Scalar& alpha,
Tensor& out) {
return impl::add_out(ctx, a, b, alpha, out);
}

Tensor& add_scalar_out(
KernelRuntimeContext& ctx,
const Tensor& a,
const Scalar& b,
const Scalar& alpha,
Tensor& out) {
return impl::add_scalar_out(ctx, a, b, alpha, out);
}

std::tuple<
Error,
std::array<executorch::aten::SizesType, kTensorDimensionLimit>,
size_t>
add_out_shape(const Tensor& a, const Tensor& b, ET_UNUSED const Scalar& alpha) {
std::array<executorch::aten::SizesType, kTensorDimensionLimit> out_sizes{};
size_t out_dim = 0;

Error err = get_broadcast_target_size(
a, b, out_sizes.data(), kTensorDimensionLimit, &out_dim);

return std::make_tuple(err, out_sizes, out_dim);
}

std::tuple<
Error,
std::array<executorch::aten::SizesType, kTensorDimensionLimit>,
size_t>
add_scalar_out_shape(
const Tensor& a,
ET_UNUSED const Scalar& b,
ET_UNUSED const Scalar& alpha) {
std::array<executorch::aten::SizesType, kTensorDimensionLimit> out_sizes{};
size_t out_dim = a.dim();

std::copy(a.sizes().begin(), a.sizes().end(), out_sizes.begin());

return std::make_tuple(Error::Ok, out_sizes, out_dim);
}

} // namespace utils
} // namespace native
} // namespace executor
} // namespace torch
65 changes: 0 additions & 65 deletions kernels/portable/cpu/op_add.h
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125 changes: 2 additions & 123 deletions kernels/portable/cpu/op_stack.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -6,142 +6,21 @@
* LICENSE file in the root directory of this source tree.
*/

#include <cstring>

#include <c10/util/irange.h>
#include <executorch/kernels/portable/cpu/util/copy_ops_util.h>
#include <executorch/kernels/portable/cpu/util/stack_util.h>
#include <executorch/runtime/kernel/kernel_includes.h>

namespace torch {
namespace executor {
namespace native {
namespace impl {

using Tensor = executorch::aten::Tensor;

Tensor& stack_out(
KernelRuntimeContext& ctx,
executorch::aten::ArrayRef<Tensor> tensors,
int64_t dim,
Tensor& out) {
(void)ctx;

if (dim < 0) {
dim += out.dim();
}

ET_KERNEL_CHECK(
ctx, check_stack_args(tensors, dim, out), InvalidArgument, out);

for (size_t i = 0; i < tensors.size(); ++i) {
ET_KERNEL_CHECK(
ctx,
tensors_have_same_dim_order(tensors[i], out),
InvalidArgument,
out);
}

ET_KERNEL_CHECK(ctx, tensor_is_default_dim_order(out), InvalidArgument, out);

Tensor::SizesType expected_out_size[kTensorDimensionLimit];
size_t expected_out_dim = 0;
get_stack_out_target_size(tensors, dim, expected_out_size, &expected_out_dim);
ET_KERNEL_CHECK(
ctx,
resize_tensor(out, {expected_out_size, expected_out_dim}) == Error::Ok,
InvalidArgument,
out);

const size_t outer = getLeadingDims(out, dim);
const size_t inner = getTrailingDims(out, dim);
const size_t ninputs = tensors.size();

const auto out_type = out.scalar_type();
ET_SWITCH_REALHBBF16_TYPES(out_type, ctx, "stack.out", CTYPE_OUT, [&] {
CTYPE_OUT* out_ptr = out.mutable_data_ptr<CTYPE_OUT>();
for (size_t i = 0; i < outer; ++i) {
for (size_t j = 0; j < ninputs; ++j) {
const auto in_type = tensors[j].scalar_type();
ET_SWITCH_REALHBBF16_TYPES(in_type, ctx, "stack.out", CTYPE_IN, [&] {
const CTYPE_IN* const in_ptr =
tensors[j].const_data_ptr<CTYPE_IN>() + i * inner;

for (size_t k = 0; k < inner; ++k) {
out_ptr[k] = static_cast<CTYPE_OUT>(in_ptr[k]);
}
out_ptr += inner;
});
}
}
});

return out;
}

} // namespace impl

Tensor& stack_out(
KernelRuntimeContext& ctx,
executorch::aten::ArrayRef<Tensor> tensors,
int64_t dim,
Tensor& out) {
return impl::stack_out(ctx, tensors, dim, out);
}

namespace utils {

Tensor& stack_out(
KernelRuntimeContext& ctx,
executorch::aten::ArrayRef<Tensor> tensors,
int64_t dim,
Tensor& out) {
return impl::stack_out(ctx, tensors, dim, out);
}

std::tuple<
Error,
std::array<executorch::aten::SizesType, kTensorDimensionLimit>,
size_t>
stack_out_shape(executorch::aten::ArrayRef<Tensor> tensors, int64_t dim) {
std::array<executorch::aten::SizesType, kTensorDimensionLimit> out_sizes{};
size_t out_dim = 0;

// Check if tensors array is empty
if (tensors.size() == 0) {
return std::make_tuple(Error::InvalidArgument, out_sizes, out_dim);
}

// Normalize negative dimension
int64_t normalized_dim = dim;
if (normalized_dim < 0) {
normalized_dim += tensors[0].dim() + 1;
}

// Check if dimension is valid
if (normalized_dim < 0 || normalized_dim > tensors[0].dim()) {
return std::make_tuple(Error::InvalidArgument, out_sizes, out_dim);
}

// Check that all tensors have the same shape
for (size_t i = 1; i < tensors.size(); ++i) {
if (tensors[i].dim() != tensors[0].dim()) {
return std::make_tuple(Error::InvalidArgument, out_sizes, out_dim);
}
for (const auto d : c10::irange(tensors[0].dim())) {
if (tensors[i].size(d) != tensors[0].size(d)) {
return std::make_tuple(Error::InvalidArgument, out_sizes, out_dim);
}
}
}

// Compute output shape using the existing utility
::torch::executor::get_stack_out_target_size(
tensors, normalized_dim, out_sizes.data(), &out_dim);

return std::make_tuple(Error::Ok, out_sizes, out_dim);
return utils::stack_out_impl(ctx, tensors, dim, out);
}

} // namespace utils
} // namespace native
} // namespace executor
} // namespace torch
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