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Diffstat (limited to 'src/cpu/kernels/select/generic/neon/impl.h')
| -rw-r--r-- | src/cpu/kernels/select/generic/neon/impl.h | 177 |
1 files changed, 177 insertions, 0 deletions
diff --git a/src/cpu/kernels/select/generic/neon/impl.h b/src/cpu/kernels/select/generic/neon/impl.h new file mode 100644 index 0000000000..7ce640b6ff --- /dev/null +++ b/src/cpu/kernels/select/generic/neon/impl.h @@ -0,0 +1,177 @@ +/* + * 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 |