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/*
* Copyright (c) 2022-2023 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to
* deal in the Software without restriction, including without limitation the
* rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
* sell copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all
* copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
* SOFTWARE.
*/
#ifndef ACL_SRC_CPU_KERNELS_SELECT_GENERIC_NEON_IMPL_H
#define ACL_SRC_CPU_KERNELS_SELECT_GENERIC_NEON_IMPL_H
#include "arm_compute/core/TensorInfo.h"
#include "src/core/NEON/NEAsymm.h"
#include "src/cpu/kernels/select/generic/neon/impl.h"
#include <arm_neon.h>
#include <map>
#include <string>
namespace arm_compute
{
namespace cpu
{
template <typename ScalarType, typename VectorType>
void select_op(const ITensor *cond,
const ITensor *in1,
const ITensor *in2,
ITensor *out,
const Window &window,
const int window_step_x,
const int window_start_x,
const int window_end_x,
const int limit,
VectorType (*condition_conversion)(const uint8_t *))
{
Window win = window;
win.set(Window::DimX, Window::Dimension(0, 1, 1));
Iterator condition(cond, win);
Iterator input1(in1, win);
Iterator input2(in2, win);
Iterator output(out, win);
execute_window_loop(
win,
[&](const Coordinates &)
{
auto output_ptr = reinterpret_cast<ScalarType *>(output.ptr());
const auto condition_ptr = reinterpret_cast<const uint8_t *>(condition.ptr());
const auto input1_ptr = reinterpret_cast<const ScalarType *>(input1.ptr());
const auto input2_ptr = reinterpret_cast<const ScalarType *>(input2.ptr());
int x = window_start_x;
for (; x <= limit; x += window_step_x)
{
const auto c = (*condition_conversion)(condition_ptr + x);
const auto a = wrapper::vloadq(input1_ptr + x);
const auto b = wrapper::vloadq(input2_ptr + x);
wrapper::vstore(output_ptr + x, wrapper::vbsl(c, a, b));
}
for (; x < window_end_x; ++x)
{
const auto c = *(condition_ptr + x);
const auto a = *(input1_ptr + x);
const auto b = *(input2_ptr + x);
*(output_ptr + x) = static_cast<bool>(c) ? a : b;
}
},
condition, input1, input2, output);
}
template <typename ScalarType, typename VectorType>
void select_op_8(const ITensor *cond, const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
{
const auto window_step_x = 16 / sizeof(ScalarType);
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
select_op<ScalarType, VectorType>(
cond, in1, in2, out, window, window_step_x, window_start_x, window_end_x, window_end_x - window_step_x,
[](const uint8_t *condition_ptr) -> VectorType
{
static const auto zero =
wrapper::vdup_n(static_cast<uint8_t>(0), arm_compute::wrapper::traits::vector_128_tag());
return wrapper::vcgt(wrapper::vloadq(condition_ptr), zero);
});
}
template <typename ScalarType, typename VectorType>
void select_op_16(const ITensor *cond, const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
{
const auto window_step_x = 16 / sizeof(ScalarType);
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
select_op<ScalarType, VectorType>(
cond, in1, in2, out, window, window_step_x, window_start_x, window_end_x, window_end_x - window_step_x,
[](const uint8_t *condition_ptr) -> VectorType
{
static const auto zero =
wrapper::vdup_n(static_cast<uint16_t>(0), arm_compute::wrapper::traits::vector_128_tag());
return wrapper::vcgt(wrapper::vmovl(wrapper::vload(condition_ptr)), zero);
});
}
template <typename ScalarType, typename VectorType>
void select_op_32(const ITensor *cond, const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
{
const auto window_step_x = 16 / sizeof(ScalarType);
const auto window_start_x = static_cast<int>(window.x().start());
const auto window_end_x = static_cast<int>(window.x().end());
select_op<ScalarType, VectorType>(
cond, in1, in2, out, window, window_step_x, window_start_x, window_end_x, window_end_x - window_step_x,
[](const uint8_t *condition_ptr) -> VectorType
{
static const auto zero =
wrapper::vdup_n(static_cast<uint32_t>(0), arm_compute::wrapper::traits::vector_128_tag());
return wrapper::vcgt(wrapper::vmovl(wrapper::vgetlow(wrapper::vmovl(wrapper::vload(condition_ptr)))), zero);
});
}
template <typename ScalarType>
void select_op_not_same_rank(
const ITensor *cond, const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window)
{
ARM_COMPUTE_UNUSED(window);
auto output_ptr = reinterpret_cast<ScalarType *>(out->buffer());
const auto condition_ptr = reinterpret_cast<const uint8_t *>(cond->buffer());
const auto input1_ptr = reinterpret_cast<const ScalarType *>(in1->buffer());
const auto input2_ptr = reinterpret_cast<const ScalarType *>(in2->buffer());
const int outer_size = cond->info()->total_size() / cond->info()->element_size();
const int inner_size = (in1->info()->total_size() / in1->info()->element_size()) / outer_size;
int offset = 0;
const int step = 16 / in1->info()->element_size();
for (int i = 0; i < outer_size; ++i)
{
int x = offset;
const auto input_ptr = static_cast<bool>(*(condition_ptr + i)) ? input1_ptr : input2_ptr;
for (; x <= offset + inner_size - step; x += step)
{
wrapper::vstore(output_ptr + x, wrapper::vloadq(input_ptr + x));
}
if (x <= offset + inner_size - (step / 2))
{
wrapper::vstore(output_ptr + x, wrapper::vload(input_ptr + x));
x += step / 2;
}
for (; x < offset + inner_size; ++x)
{
*(output_ptr + x) = *(input_ptr + x);
}
offset += inner_size;
}
}
} // namespace cpu
} // namespace arm_compute
#endif // ACL_SRC_CPU_KERNELS_SELECT_GENERIC_NEON_IMPL_H
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