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Diffstat (limited to 'src/cpu/kernels/elementwise_binary/generic/neon/impl.h')
| -rw-r--r-- | src/cpu/kernels/elementwise_binary/generic/neon/impl.h | 1316 |
1 files changed, 1316 insertions, 0 deletions
diff --git a/src/cpu/kernels/elementwise_binary/generic/neon/impl.h b/src/cpu/kernels/elementwise_binary/generic/neon/impl.h new file mode 100644 index 0000000000..78e3baf74b --- /dev/null +++ b/src/cpu/kernels/elementwise_binary/generic/neon/impl.h @@ -0,0 +1,1316 @@ +/* + * Copyright (c) 2021-2022, 2024 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_ELEMENTWISE_BINARY_GENERIC_NEON_IMPL_H +#define ACL_SRC_CPU_KERNELS_ELEMENTWISE_BINARY_GENERIC_NEON_IMPL_H + +#include "src/core/NEON/NEAsymm.h" + +namespace arm_compute +{ +namespace cpu +{ +template <ArithmeticOperation op, typename VectorType> +typename VectorType::type elementwise_arithm_op(const typename VectorType::type &a, const typename VectorType::type &b) +{ + using vec_type = typename VectorType::type; + using scalar_type = typename VectorType::scalar_type; + using tag_type = typename VectorType::tag_type; + + vec_type res = wrapper::vdup_n(static_cast<scalar_type>(0), tag_type{}); + + switch (op) + { + case ArithmeticOperation::MAX: + res = wrapper::vmax(a, b); + break; + case ArithmeticOperation::MIN: + res = wrapper::vmin(a, b); + break; + case ArithmeticOperation::SQUARED_DIFF: + { + const vec_type tmp = wrapper::vsub(a, b); + res = wrapper::vmul(tmp, tmp); + break; + } + case ArithmeticOperation::PRELU: + { + const vec_type zero = wrapper::vdup_n(static_cast<scalar_type>(0), tag_type{}); + const vec_type tmp = wrapper::vmul(a, b); + const auto gt = wrapper::vcgt(a, zero); + + res = wrapper::vbsl(gt, a, tmp); + break; + } + + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); + } + + return res; +} + +template <ArithmeticOperation op, typename ScalarType, typename VectorType> +typename VectorType::type elementwise_arithm_op_broadcast(const typename VectorType::type &a, + const ScalarType &broadcast_value, + const bool reorder) +{ + using tag_type = typename VectorType::tag_type; + using vec_type = typename VectorType::type; + + vec_type broadcast_vector = wrapper::vdup_n(broadcast_value, tag_type{}); + return elementwise_arithm_op<op, VectorType>(reorder ? broadcast_vector : a, reorder ? a : broadcast_vector); +} + +template <typename InputScalarType, typename OutputScalarType, typename InputVectorType> +void elementwise_op( + const ITensor *in1, + const ITensor *in2, + ITensor *out, + const Window &window, + OutputScalarType (*scalar_func)(const InputScalarType &, const InputScalarType &), + int (*broadcast_func)( + int, int, int, const InputScalarType *, const InputScalarType &, OutputScalarType *, const bool), + int (*neon_func)(int, int, int, const InputScalarType *, const InputScalarType *, OutputScalarType *)) +{ + // Create input windows + Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); + Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); + + // Clear X Dimension on execution window as we handle manually + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int window_step_x = std::min(16 / static_cast<int>(sizeof(OutputScalarType)), 8); + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); + + if (is_broadcast_across_x) + { + const bool is_broadcast_input_2 = input2_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; + Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; + const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; + const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; + + // Clear X Dimension on execution window as we handle manually + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_input(broadcast_tensor, broadcast_win); + Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); + const auto non_broadcast_input_ptr = + reinterpret_cast<const InputScalarType *>(non_broadcast_input.ptr()); + const InputScalarType broadcast_value = + *reinterpret_cast<const InputScalarType *>(broadcast_input.ptr()); + + int x = (*broadcast_func)(window_start_x, window_end_x, window_step_x, non_broadcast_input_ptr, + broadcast_value, output_ptr, !is_broadcast_input_2); + for (; x < window_end_x; ++x) + { + const auto a = *(non_broadcast_input_ptr + x); + *(output_ptr + x) = (*scalar_func)(!is_broadcast_input_2 ? broadcast_value : a, + !is_broadcast_input_2 ? a : broadcast_value); + } + }, + broadcast_input, non_broadcast_input, output); + } + else + { + // Clear X Dimension on execution window as we handle manually + input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input1(in1, input1_win); + Iterator input2(in2, input2_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + auto output_ptr = reinterpret_cast<OutputScalarType *>(output.ptr()); + const auto input1_ptr = reinterpret_cast<const InputScalarType *>(input1.ptr()); + const auto input2_ptr = reinterpret_cast<const InputScalarType *>(input2.ptr()); + + int x = (*neon_func)(window_start_x, window_end_x, window_step_x, input1_ptr, input2_ptr, output_ptr); + for (; x < window_end_x; ++x) + { + const auto a = *(input1_ptr + x); + const auto b = *(input2_ptr + x); + *(output_ptr + x) = (*scalar_func)(a, b); + } + }, + input1, input2, output); + } +} + +template <ArithmeticOperation op, typename ScalarType> +inline ScalarType elementwise_arithm_op_scalar(const ScalarType &a, const ScalarType &b) +{ + auto res = ScalarType(0); + + switch (op) + { + case ArithmeticOperation::MAX: + res = std::max(a, b); + break; + case ArithmeticOperation::MIN: + res = std::min(a, b); + break; + case ArithmeticOperation::SQUARED_DIFF: + { + res = (a - b) * (a - b); + break; + } + case ArithmeticOperation::PRELU: + { + res = (a > 0 ? a : a * b); + break; + } + case ArithmeticOperation::DIV: + { + res = a / b; + break; + } + case ArithmeticOperation::POWER: + { + res = std::pow(a, b); + break; + } + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); + } + return res; +} + +template <> +inline int32x4_t +elementwise_arithm_op<ArithmeticOperation::DIV, typename wrapper::traits::neon_vector<int32_t, 4>>(const int32x4_t &a, + const int32x4_t &b) +{ + int32x4_t result; + + // Neon(TM) does not have vector integer division + result[0] = a[0] / b[0]; + result[1] = a[1] / b[1]; + result[2] = a[2] / b[2]; + result[3] = a[3] / b[3]; + + return result; +} + +template <> +inline float32x4_t +elementwise_arithm_op<ArithmeticOperation::DIV, typename wrapper::traits::neon_vector<float, 4>>(const float32x4_t &a, + const float32x4_t &b) +{ + return wrapper::vdiv(a, b); +} + +template <> +inline float32x4_t +elementwise_arithm_op<ArithmeticOperation::POWER, typename wrapper::traits::neon_vector<float, 4>>(const float32x4_t &a, + const float32x4_t &b) +{ + return wrapper::vpow(a, b); +} + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +template <> +inline float16x8_t elementwise_arithm_op<ArithmeticOperation::DIV, typename wrapper::traits::neon_vector<float16_t, 8>>( + const float16x8_t &a, const float16x8_t &b) +{ + return wrapper::vdiv(a, b); +} + +template <> +inline float16x8_t +elementwise_arithm_op<ArithmeticOperation::POWER, typename wrapper::traits::neon_vector<float16_t, 8>>( + const float16x8_t &a, const float16x8_t &b) +{ + return wrapper::vpow(a, b); +} +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + +template <ArithmeticOperation op, typename ScalarType, typename VectorType> +inline int elementwise_arithm_op_loop(int window_start_x, + int window_end_x, + int window_step_x, + const ScalarType *input1_ptr, + const ScalarType *input2_ptr, + ScalarType *output_ptr) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = wrapper::vloadq(input1_ptr + x); + const auto b = wrapper::vloadq(input2_ptr + x); + wrapper::vstore(output_ptr + x, elementwise_arithm_op<op, VectorType>(a, b)); + } + return x; +} + +template <ArithmeticOperation op, typename ScalarType, typename VectorType> +inline int elementwise_arithm_op_broadcast_loop(int window_start_x, + int window_end_x, + int window_step_x, + const ScalarType *non_broadcast_input_ptr, + const ScalarType &broadcast_value, + ScalarType *output_ptr, + const bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = wrapper::vloadq((non_broadcast_input_ptr + x)); + wrapper::vstore(output_ptr + x, + elementwise_arithm_op_broadcast<op, ScalarType, VectorType>(a, broadcast_value, reorder)); + } + return x; +} + +template <ArithmeticOperation op, typename VectorType> +void elementwise_arithm_op(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + using scalar_type = typename VectorType::scalar_type; + + elementwise_op<scalar_type, scalar_type, VectorType>( + in1, in2, out, window, &elementwise_arithm_op_scalar<op, scalar_type>, + &elementwise_arithm_op_broadcast_loop<op, scalar_type, VectorType>, + &elementwise_arithm_op_loop<op, scalar_type, VectorType>); +} + +template <ComparisonOperation op, typename InputScalarType> +inline uint8_t elementwise_comp_op_scalar(const InputScalarType &a, const InputScalarType &b) +{ + bool res = false; + + switch (op) + { + case ComparisonOperation::Equal: + res = (a == b); + break; + case ComparisonOperation::NotEqual: + res = (a != b); + break; + case ComparisonOperation::Greater: + res = (a > b); + break; + case ComparisonOperation::GreaterEqual: + res = (a >= b); + break; + case ComparisonOperation::Less: + res = (a < b); + break; + case ComparisonOperation::LessEqual: + res = (a <= b); + break; + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); + } + return res ? ~static_cast<uint8_t>(0) : static_cast<uint8_t>(0); +} + +template <ComparisonOperation op, typename InputVectorType, typename OutputVectorType> +inline OutputVectorType elementwise_comp_op(const InputVectorType &a, const InputVectorType &b) +{ + OutputVectorType res = {0, 0, 0, 0}; + + switch (op) + { + case ComparisonOperation::Equal: + res = wrapper::vceq(a, b); + break; + case ComparisonOperation::NotEqual: + res = wrapper::vnot(wrapper::vceq(a, b)); + break; + case ComparisonOperation::Greater: + res = wrapper::vcgt(a, b); + break; + case ComparisonOperation::GreaterEqual: + res = wrapper::vcge(a, b); + break; + case ComparisonOperation::Less: + res = wrapper::vcgt(b, a); + break; + case ComparisonOperation::LessEqual: + res = wrapper::vcge(b, a); + break; + default: + ARM_COMPUTE_ERROR("NOT_SUPPORTED!"); + } + + return res; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType, typename OutputVectorType> +inline OutputVectorType +elementwise_comp_op_broadcast(const InputVectorType &a, const InputScalarType &broadcast_value, const bool reorder) +{ + InputVectorType broadcast_vector = wrapper::vdup_n(broadcast_value, wrapper::traits::vector_128_tag()); + return elementwise_comp_op<op, InputVectorType, OutputVectorType>(reorder ? broadcast_vector : a, + reorder ? a : broadcast_vector); +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_broadcast_8_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *non_broadcast_input_ptr, + const InputScalarType &broadcast_value, + uint8_t *output_ptr, + const bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = elementwise_comp_op_broadcast<op, InputScalarType, InputVectorType, uint8x16_t>( + wrapper::vloadq((non_broadcast_input_ptr + x)), broadcast_value, reorder); + wrapper::vstore(output_ptr + x, a); + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_broadcast_16_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *non_broadcast_input_ptr, + const InputScalarType &broadcast_value, + uint8_t *output_ptr, + const bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = elementwise_comp_op_broadcast<op, InputScalarType, InputVectorType, uint16x8_t>( + wrapper::vloadq((non_broadcast_input_ptr + x)), broadcast_value, reorder); + wrapper::vstore(output_ptr + x, wrapper::vmovn(a)); + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_broadcast_32_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *non_broadcast_input_ptr, + const InputScalarType &broadcast_value, + uint8_t *output_ptr, + const bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = elementwise_comp_op_broadcast<op, InputScalarType, InputVectorType, uint32x4_t>( + wrapper::vloadq(non_broadcast_input_ptr + x), broadcast_value, reorder); + const auto b = elementwise_comp_op_broadcast<op, InputScalarType, InputVectorType, uint32x4_t>( + wrapper::vloadq(non_broadcast_input_ptr + x + 4), broadcast_value, reorder); + wrapper::vstore(output_ptr + x, wrapper::vmovn(wrapper::vcombine(wrapper::vmovn(a), wrapper::vmovn(b)))); + } + if (x <= window_end_x - 4) + { + const auto a = elementwise_comp_op_broadcast<op, InputScalarType, InputVectorType, uint32x4_t>( + wrapper::vloadq((non_broadcast_input_ptr + x)), broadcast_value, reorder); + for (int i = 0; i < 4; i++) + { + *(output_ptr + x + i) = wrapper::vgetlane(a, i); + } + x = +4; + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_8_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *input1_ptr, + const InputScalarType *input2_ptr, + uint8_t *output_ptr) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = wrapper::vloadq(input1_ptr + x); + const auto b = wrapper::vloadq(input2_ptr + x); + const auto res = elementwise_comp_op<op, InputVectorType, uint8x16_t>(a, b); + wrapper::vstore(output_ptr + x, res); + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_16_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *input1_ptr, + const InputScalarType *input2_ptr, + uint8_t *output_ptr) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const auto a = wrapper::vloadq(input1_ptr + x); + const auto b = wrapper::vloadq(input2_ptr + x); + const auto res = elementwise_comp_op<op, InputVectorType, uint16x8_t>(a, b); + wrapper::vstore(output_ptr + x, wrapper::vmovn(res)); + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +inline int elementwise_comp_op_32_loop(int window_start_x, + int window_end_x, + int window_step_x, + const InputScalarType *input1_ptr, + const InputScalarType *input2_ptr, + uint8_t *output_ptr) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + auto a = wrapper::vloadq(input1_ptr + x); + auto b = wrapper::vloadq(input2_ptr + x); + const auto res = elementwise_comp_op<op, InputVectorType, uint32x4_t>(a, b); + a = wrapper::vloadq(input1_ptr + x + 4); + b = wrapper::vloadq(input2_ptr + x + 4); + const auto res2 = elementwise_comp_op<op, InputVectorType, uint32x4_t>(a, b); + wrapper::vstore(output_ptr + x, wrapper::vmovn(wrapper::vcombine(wrapper::vmovn(res), wrapper::vmovn(res2)))); + } + if (x <= window_end_x - 4) + { + const auto a = wrapper::vloadq(input1_ptr + x); + const auto b = wrapper::vloadq(input2_ptr + x); + const auto res = elementwise_comp_op<op, InputVectorType, uint32x4_t>(a, b); + for (int i = 0; i < 4; i++) + { + *(output_ptr + x + i) = wrapper::vgetlane(res, i); + } + x = +4; + } + return x; +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +void elementwise_comp_op_8(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op<InputScalarType, uint8_t, InputVectorType>( + in1, in2, out, window, &elementwise_comp_op_scalar<op, InputScalarType>, + &elementwise_comp_op_broadcast_8_loop<op, InputScalarType, InputVectorType>, + &elementwise_comp_op_8_loop<op, InputScalarType, InputVectorType>); +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +void elementwise_comp_op_16(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op<InputScalarType, uint8_t, InputVectorType>( + in1, in2, out, window, &elementwise_comp_op_scalar<op, InputScalarType>, + &elementwise_comp_op_broadcast_16_loop<op, InputScalarType, InputVectorType>, + &elementwise_comp_op_16_loop<op, InputScalarType, InputVectorType>); +} + +template <ComparisonOperation op, typename InputScalarType, typename InputVectorType> +void elementwise_comp_op_32(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op<InputScalarType, uint8_t, InputVectorType>( + in1, in2, out, window, &elementwise_comp_op_scalar<op, InputScalarType>, + &elementwise_comp_op_broadcast_32_loop<op, InputScalarType, InputVectorType>, + &elementwise_comp_op_32_loop<op, InputScalarType, InputVectorType>); +} + +inline float32x4x4_t load_quantized(const uint8_t *input1_ptr, const int32x4_t &offset, const float32x4_t &scale) +{ + qasymm8x16_t x = vld1q_u8(input1_ptr); + const float32x4x4_t out = {{ + vmulq_f32( + vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(x))))), offset)), + scale), + vmulq_f32( + vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(x))))), offset)), + scale), + vmulq_f32( + vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(x))))), offset)), + scale), + vmulq_f32(vcvtq_f32_s32( + vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(x))))), offset)), + scale), + }}; + return out; +} + +inline float32x4x4_t load_quantized_signed(const int8_t *input1_ptr, const int32x4_t &offset, const float32x4_t &scale) +{ + qasymm8x16_signed_t x = vld1q_s8(input1_ptr); + const float32x4x4_t out = {{ + vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_low_s8(x)))), offset)), scale), + vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_low_s8(x)))), offset)), scale), + vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_low_s16(vmovl_s8(vget_high_s8(x)))), offset)), scale), + vmulq_f32(vcvtq_f32_s32(vsubq_s32(vmovl_s16(vget_high_s16(vmovl_s8(vget_high_s8(x)))), offset)), scale), + }}; + return out; +} + +inline void store_quantized(uint8_t *output_ptr, const uint32x4x4_t &out) +{ + const uint8x8_t pa = vqmovn_u16(vcombine_u16(vqmovn_u32(out.val[0]), vqmovn_u32(out.val[1]))); + const uint8x8_t pb = vqmovn_u16(vcombine_u16(vqmovn_u32(out.val[2]), vqmovn_u32(out.val[3]))); + vst1q_u8(output_ptr, vcombine_u8(pa, pb)); +} + +inline void store_quantized(uint8_t *output_ptr, const int32x4x4_t &out) +{ + const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(out.val[0]), vqmovn_s32(out.val[1]))); + const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(out.val[2]), vqmovn_s32(out.val[3]))); + vst1q_u8(output_ptr, vcombine_u8(pa, pb)); +} + +inline void +store_quantized(uint8_t *output_ptr, const float32x4x4_t &rf, const float32x4_t &offset, const float32x4_t &invscale) +{ + int32x4x4_t out = {{ + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[0], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[1], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[2], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[3], invscale)), + }}; + store_quantized(output_ptr, out); +} + +inline void store_quantized_signed(int8_t *output_ptr, const int32x4x4_t &out) +{ + const int8x8_t pa = vqmovn_s16(vcombine_s16(vqmovn_s32(out.val[0]), vqmovn_s32(out.val[1]))); + const int8x8_t pb = vqmovn_s16(vcombine_s16(vqmovn_s32(out.val[2]), vqmovn_s32(out.val[3]))); + vst1q_s8(output_ptr, vcombine_s8(pa, pb)); +} + +inline void store_quantized_signed(int8_t *output_ptr, + const float32x4x4_t &rf, + const float32x4_t &offset, + const float32x4_t &invscale) +{ + int32x4x4_t out = {{ + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[0], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[1], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[2], invscale)), + vcvtq_s32_f32(vmlaq_f32(offset, rf.val[3], invscale)), + }}; + store_quantized_signed(output_ptr, out); +} + +template <ArithmeticOperation op> +inline uint8_t elementwise_arithm_op_quantized_scalar(const float &a, const float &b, UniformQuantizationInfo qinfo) +{ + return quantize_qasymm8(elementwise_arithm_op_scalar<op>(a, b), qinfo); +} + +template <ArithmeticOperation op> +inline int8_t +elementwise_arithm_op_quantized_signed_scalar(const float &a, const float &b, UniformQuantizationInfo qinfo) +{ + return quantize_qasymm8_signed(elementwise_arithm_op_scalar<op>(a, b), qinfo); +} + +template <ArithmeticOperation op> +float32x4x4_t elementwise_arithm_op(const float32x4x4_t &a, const float32x4x4_t &b) +{ + using neon_vector_float = wrapper::traits::neon_vector<float, 4>; + float32x4x4_t out = {{ + elementwise_arithm_op<op, neon_vector_float>(a.val[0], b.val[0]), + elementwise_arithm_op<op, neon_vector_float>(a.val[1], b.val[1]), + elementwise_arithm_op<op, neon_vector_float>(a.val[2], b.val[2]), + elementwise_arithm_op<op, neon_vector_float>(a.val[3], b.val[3]), + }}; + return out; +} + +template <ComparisonOperation op> +inline uint8_t elementwise_comp_op_quantized_scalar(const float &a, const float &b, UniformQuantizationInfo qinfo) +{ + ARM_COMPUTE_UNUSED(qinfo); + return elementwise_comp_op_scalar<op>(a, b); +} + +template <ComparisonOperation op> +inline uint32x4x4_t elementwise_comp_op(const float32x4x4_t &a, const float32x4x4_t &b) +{ + uint32x4x4_t out = {{elementwise_comp_op<op, float32x4_t, uint32x4_t>(a.val[0], b.val[0]), + elementwise_comp_op<op, float32x4_t, uint32x4_t>(a.val[1], b.val[1]), + elementwise_comp_op<op, float32x4_t, uint32x4_t>(a.val[2], b.val[2]), + elementwise_comp_op<op, float32x4_t, uint32x4_t>(a.val[3], b.val[3])}}; + return out; +} + +template <ArithmeticOperation op> +inline int elementwise_arithm_op_quantized_loop(int window_start_x, + int window_end_x, + int window_step_x, + const uint8_t *input1_ptr, + const uint8_t *input2_ptr, + uint8_t *output_ptr, + int32x4_t voffset1, + int32x4_t voffset2, + float32x4_t vscale1, + float32x4_t vscale2, + float32x4_t voffseto, + float32x4_t invvscaleo) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Get inputs and compute output + const float32x4x4_t af = load_quantized(input1_ptr + x, voffset1, vscale1); + const float32x4x4_t bf = load_quantized(input2_ptr + x, voffset2, vscale2); + const float32x4x4_t rf = elementwise_arithm_op<op>(af, bf); + store_quantized(output_ptr + x, rf, voffseto, invvscaleo); + } + return x; +} + +template <ArithmeticOperation op> +inline int elementwise_arithm_op_quantized_singed_loop(int window_start_x, + int window_end_x, + int window_step_x, + const int8_t *input1_ptr, + const int8_t *input2_ptr, + int8_t *output_ptr, + int32x4_t voffset1, + int32x4_t voffset2, + float32x4_t vscale1, + float32x4_t vscale2, + float32x4_t voffseto, + float32x4_t invvscaleo) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + // Get inputs and compute output + const float32x4x4_t af = load_quantized_signed(input1_ptr + x, voffset1, vscale1); + const float32x4x4_t bf = load_quantized_signed(input2_ptr + x, voffset2, vscale2); + const float32x4x4_t rf = elementwise_arithm_op<op>(af, bf); + store_quantized_signed(output_ptr + x, rf, voffseto, invvscaleo); + } + return x; +} + +template <ArithmeticOperation op> +inline int elementwise_arithm_op_quantized_broadcast_loop(int window_start_x, + int window_end_x, + int window_step_x, + const uint8_t *non_broadcast_input_ptr, + float32x4x4_t broadcast_vector, + uint8_t *output_ptr, + int32x4_t voffset_non_broadcast, + float32x4_t vscale_non_broadcast, + float32x4_t voffseto, + float32x4_t invvscaleo, + bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = + load_quantized(non_broadcast_input_ptr + x, voffset_non_broadcast, vscale_non_broadcast); + const float32x4x4_t rf = + elementwise_arithm_op<op>(reorder ? broadcast_vector : af, reorder ? af : broadcast_vector); + store_quantized(output_ptr + x, rf, voffseto, invvscaleo); + } + return x; +} +template <ArithmeticOperation op> +inline int elementwise_arithm_op_quantized_signed_broadcast_loop(int window_start_x, + int window_end_x, + int window_step_x, + const int8_t *non_broadcast_input_ptr, + float32x4x4_t broadcast_vector, + int8_t *output_ptr, + int32x4_t voffset_non_broadcast, + float32x4_t vscale_non_broadcast, + float32x4_t voffseto, + float32x4_t invvscaleo, + bool reorder) +{ + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = + load_quantized_signed(non_broadcast_input_ptr + x, voffset_non_broadcast, vscale_non_broadcast); + const float32x4x4_t rf = + elementwise_arithm_op<op>(reorder ? broadcast_vector : af, reorder ? af : broadcast_vector); + store_quantized_signed(output_ptr + x, rf, voffseto, invvscaleo); + } + return x; +} + +template <ComparisonOperation op> +inline int elementwise_comp_op_quantized_loop(int window_start_x, + int window_end_x, + int window_step_x, + const uint8_t *input1_ptr, + const uint8_t *input2_ptr, + uint8_t *output_ptr, + int32x4_t voffset1, + int32x4_t voffset2, + float32x4_t vscale1, + float32x4_t vscale2, + float32x4_t voffseto, + float32x4_t invvscaleo) +{ + ARM_COMPUTE_UNUSED(voffseto, invvscaleo); + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = load_quantized(input1_ptr + x, voffset1, vscale1); + const float32x4x4_t bf = load_quantized(input2_ptr + x, voffset2, vscale2); + const uint32x4x4_t rf = elementwise_comp_op<op>(af, bf); + store_quantized(output_ptr + x, rf); + } + return x; +} + +template <ComparisonOperation op> +inline int elementwise_comp_op_quantized_signed_loop(int window_start_x, + int window_end_x, + int window_step_x, + const int8_t *input1_ptr, + const int8_t *input2_ptr, + uint8_t *output_ptr, + int32x4_t voffset1, + int32x4_t voffset2, + float32x4_t vscale1, + float32x4_t vscale2, + float32x4_t voffseto, + float32x4_t invvscaleo) +{ + ARM_COMPUTE_UNUSED(voffseto, invvscaleo); + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = load_quantized_signed(input1_ptr + x, voffset1, vscale1); + const float32x4x4_t bf = load_quantized_signed(input2_ptr + x, voffset2, vscale2); + const uint32x4x4_t rf = elementwise_comp_op<op>(af, bf); + store_quantized(output_ptr + x, rf); + } + return x; +} + +template <ComparisonOperation op> +inline int elementwise_comp_op_quantized_broadcast_loop(int window_start_x, + int window_end_x, + int window_step_x, + const uint8_t *non_broadcast_input_ptr, + float32x4x4_t broadcast_vector, + uint8_t *output_ptr, + int32x4_t voffset_non_broadcast, + float32x4_t vscale_non_broadcast, + float32x4_t voffseto, + float32x4_t invvscaleo, + bool reorder) +{ + ARM_COMPUTE_UNUSED(voffseto, invvscaleo); + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = + load_quantized(non_broadcast_input_ptr + x, voffset_non_broadcast, vscale_non_broadcast); + const uint32x4x4_t rf = + elementwise_comp_op<op>(reorder ? broadcast_vector : af, reorder ? af : broadcast_vector); + store_quantized(output_ptr + x, rf); + } + return x; +} + +template <ComparisonOperation op> +inline int elementwise_comp_op_quantized_signed_broadcast_loop(int window_start_x, + int window_end_x, + int window_step_x, + const int8_t *non_broadcast_input_ptr, + float32x4x4_t broadcast_vector, + uint8_t *output_ptr, + int32x4_t voffset_non_broadcast, + float32x4_t vscale_non_broadcast, + float32x4_t voffseto, + float32x4_t invvscaleo, + bool reorder) +{ + ARM_COMPUTE_UNUSED(voffseto, invvscaleo); + int x = window_start_x; + for (; x <= (window_end_x - window_step_x); x += window_step_x) + { + const float32x4x4_t af = + load_quantized_signed(non_broadcast_input_ptr + x, voffset_non_broadcast, vscale_non_broadcast); + const uint32x4x4_t rf = + elementwise_comp_op<op>(reorder ? broadcast_vector : af, reorder ? af : broadcast_vector); + store_quantized(output_ptr + x, rf); + } + return x; +} + +inline void elementwise_op_quantized(const ITensor *in1, + const ITensor *in2, + ITensor *out, + const Window &window, + uint8_t (*scalar_func)(const float &, const float &, UniformQuantizationInfo), + int (*broadcast_func)(int, + int, + int, + const uint8_t *, + float32x4x4_t, + uint8_t *, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + const bool), + int (*neon_func)(int, + int, + int, + const uint8_t *, + const uint8_t *, + uint8_t *, + int32x4_t, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + float32x4_t)) +{ + // Create input windows + Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); + Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); + + // Clear X Dimension on execution window as we handle manually + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int window_step_x = 16; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); + + const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform(); + + // Output quantization info (add 0.5 to round toward the nearest integer - 0.5 rounds away from zero) + const float32x4_t voffseto = vdupq_n_f32(output_qinfo.offset + 0.5f); + const float32x4_t invvscaleo = vdupq_n_f32(1.f / output_qinfo.scale); + + if (is_broadcast_across_x) + { + // Select the broadcast input on the X axis + const bool is_broadcast_input_2 = input2_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; + Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; + const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; + const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; + + const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform(); + const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform(); + + const int32x4_t voffset_non_broadcast = vdupq_n_s32(non_broadcast_qinfo.offset); + const float32x4_t vscale_non_broadcast = vdupq_n_f32(non_broadcast_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_input(broadcast_tensor, broadcast_win); + Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto non_broadcast_input_ptr = reinterpret_cast<const uint8_t *>(non_broadcast_input.ptr()); + const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr()); + + const uint8_t broadcast_value = *reinterpret_cast<const uint8_t *>(broadcast_input.ptr()); + const float32x4x4_t broadcast_vector = vdequantize(vdupq_n_u8(broadcast_value), broadcast_qinfo); + + int x = (*broadcast_func)(window_start_x, window_end_x, window_step_x, non_broadcast_input_ptr, + broadcast_vector, output_ptr, voffset_non_broadcast, vscale_non_broadcast, + voffseto, invvscaleo, !is_broadcast_input_2); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8(*(non_broadcast_input_ptr + x), non_broadcast_qinfo); + const float bfs = dequantize_qasymm8(broadcast_value, broadcast_qinfo); + *(output_ptr + x) = (*scalar_func)(!is_broadcast_input_2 ? bfs : afs, + !is_broadcast_input_2 ? afs : bfs, output_qinfo); + } + }, + broadcast_input, non_broadcast_input, output); + } + else + { + const UniformQuantizationInfo input1_qinfo = in1->info()->quantization_info().uniform(); + const UniformQuantizationInfo input2_qinfo = in2->info()->quantization_info().uniform(); + + // Input1 quantization info + const int32x4_t voffset1 = vdupq_n_s32(input1_qinfo.offset); + const float32x4_t vscale1 = vdupq_n_f32(input1_qinfo.scale); + + // Input2 quantization info + const int32x4_t voffset2 = vdupq_n_s32(input2_qinfo.offset); + const float32x4_t vscale2 = vdupq_n_f32(input2_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input1(in1, input1_win); + Iterator input2(in2, input2_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto input1_ptr = reinterpret_cast<const uint8_t *>(input1.ptr()); + const auto input2_ptr = reinterpret_cast<const uint8_t *>(input2.ptr()); + const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr()); + + int x = (*neon_func)(window_start_x, window_end_x, window_step_x, input1_ptr, input2_ptr, output_ptr, + voffset1, voffset2, vscale1, vscale2, voffseto, invvscaleo); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8(*(input1_ptr + x), input1_qinfo); + const float bfs = dequantize_qasymm8(*(input2_ptr + x), input2_qinfo); + *(output_ptr + x) = (*scalar_func)(afs, bfs, output_qinfo); + } + }, + input1, input2, output); + } +} + +inline void +elementwise_comp_quantized_signed(const ITensor *in1, + const ITensor *in2, + ITensor *out, + const Window &window, + uint8_t (*scalar_func)(const float &, const float &, UniformQuantizationInfo), + int (*broadcast_func)(int, + int, + int, + const int8_t *, + float32x4x4_t, + uint8_t *, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + const bool), + int (*neon_func)(int, + int, + int, + const int8_t *, + const int8_t *, + uint8_t *, + int32x4_t, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + float32x4_t)) +{ + // Create input windows + Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); + Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); + + // Clear X Dimension on execution window as we handle manually + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int window_step_x = 16; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); + + const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform(); + + const float32x4_t voffseto = vdupq_n_f32(output_qinfo.offset); + const float32x4_t invvscaleo = vdupq_n_f32(1.f / output_qinfo.scale); + + if (is_broadcast_across_x) + { + // Select the broadcast input on the X axis + const bool is_broadcast_input_2 = input2_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; + Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; + const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; + const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; + + const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform(); + const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform(); + + const int32x4_t voffset_non_broadcast = vdupq_n_s32(non_broadcast_qinfo.offset); + const float32x4_t vscale_non_broadcast = vdupq_n_f32(non_broadcast_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_input(broadcast_tensor, broadcast_win); + Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto non_broadcast_input_ptr = reinterpret_cast<const int8_t *>(non_broadcast_input.ptr()); + const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr()); + + const int8_t broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr()); + const float32x4x4_t broadcast_vector = vdequantize(vdupq_n_s8(broadcast_value), broadcast_qinfo); + + int x = (*broadcast_func)(window_start_x, window_end_x, window_step_x, non_broadcast_input_ptr, + broadcast_vector, output_ptr, voffset_non_broadcast, vscale_non_broadcast, + voffseto, invvscaleo, !is_broadcast_input_2); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8_signed(*(non_broadcast_input_ptr + x), non_broadcast_qinfo); + const float bfs = dequantize_qasymm8_signed(broadcast_value, broadcast_qinfo); + *(output_ptr + x) = (*scalar_func)(!is_broadcast_input_2 ? bfs : afs, + !is_broadcast_input_2 ? afs : bfs, output_qinfo); + } + }, + broadcast_input, non_broadcast_input, output); + } + else + { + const UniformQuantizationInfo input1_qinfo = in1->info()->quantization_info().uniform(); + const UniformQuantizationInfo input2_qinfo = in2->info()->quantization_info().uniform(); + + // Input1 quantization info + const int32x4_t voffset1 = vdupq_n_s32(input1_qinfo.offset); + const float32x4_t vscale1 = vdupq_n_f32(input1_qinfo.scale); + + // Input2 quantization info + const int32x4_t voffset2 = vdupq_n_s32(input2_qinfo.offset); + const float32x4_t vscale2 = vdupq_n_f32(input2_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input1(in1, input1_win); + Iterator input2(in2, input2_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto input1_ptr = reinterpret_cast<const int8_t *>(input1.ptr()); + const auto input2_ptr = reinterpret_cast<const int8_t *>(input2.ptr()); + const auto output_ptr = reinterpret_cast<uint8_t *>(output.ptr()); + + int x = (*neon_func)(window_start_x, window_end_x, window_step_x, input1_ptr, input2_ptr, output_ptr, + voffset1, voffset2, vscale1, vscale2, voffseto, invvscaleo); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8_signed(*(input1_ptr + x), input1_qinfo); + const float bfs = dequantize_qasymm8_signed(*(input2_ptr + x), input2_qinfo); + *(output_ptr + x) = (*scalar_func)(afs, bfs, output_qinfo); + } + }, + input1, input2, output); + } +} + +inline void +elementwise_op_quantized_signed(const ITensor *in1, + const ITensor *in2, + ITensor *out, + const Window &window, + int8_t (*scalar_func)(const float &, const float &, UniformQuantizationInfo), + int (*broadcast_func)(int, + int, + int, + const int8_t *, + float32x4x4_t, + int8_t *, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + const bool), + int (*neon_func)(int, + int, + int, + const int8_t *, + const int8_t *, + int8_t *, + int32x4_t, + int32x4_t, + float32x4_t, + float32x4_t, + float32x4_t, + float32x4_t)) +{ + // Create input windows + Window input1_win = window.broadcast_if_dimension_le_one(in1->info()->tensor_shape()); + Window input2_win = window.broadcast_if_dimension_le_one(in2->info()->tensor_shape()); + + // Clear X Dimension on execution window as we handle manually + Window win = window; + win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + const int window_step_x = 16; + const auto window_start_x = static_cast<int>(window.x().start()); + const auto window_end_x = static_cast<int>(window.x().end()); + const bool is_broadcast_across_x = in1->info()->tensor_shape().x() != in2->info()->tensor_shape().x(); + + const UniformQuantizationInfo output_qinfo = out->info()->quantization_info().uniform(); + + const float32x4_t voffseto = vdupq_n_f32(output_qinfo.offset); + const float32x4_t invvscaleo = vdupq_n_f32(1.f / output_qinfo.scale); + + if (is_broadcast_across_x) + { + // Select the broadcast input on the X axis + const bool is_broadcast_input_2 = input2_win.x().step() == 0; + Window broadcast_win = is_broadcast_input_2 ? input2_win : input1_win; + Window non_broadcast_win = !is_broadcast_input_2 ? input2_win : input1_win; + const ITensor *broadcast_tensor = is_broadcast_input_2 ? in2 : in1; + const ITensor *non_broadcast_tensor = !is_broadcast_input_2 ? in2 : in1; + + const UniformQuantizationInfo broadcast_qinfo = broadcast_tensor->info()->quantization_info().uniform(); + const UniformQuantizationInfo non_broadcast_qinfo = non_broadcast_tensor->info()->quantization_info().uniform(); + + const int32x4_t voffset_non_broadcast = vdupq_n_s32(non_broadcast_qinfo.offset); + const float32x4_t vscale_non_broadcast = vdupq_n_f32(non_broadcast_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + non_broadcast_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator broadcast_input(broadcast_tensor, broadcast_win); + Iterator non_broadcast_input(non_broadcast_tensor, non_broadcast_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto non_broadcast_input_ptr = reinterpret_cast<const int8_t *>(non_broadcast_input.ptr()); + const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr()); + + const int8_t broadcast_value = *reinterpret_cast<const int8_t *>(broadcast_input.ptr()); + const float32x4x4_t broadcast_vector = vdequantize(vdupq_n_s8(broadcast_value), broadcast_qinfo); + + int x = (*broadcast_func)(window_start_x, window_end_x, window_step_x, non_broadcast_input_ptr, + broadcast_vector, output_ptr, voffset_non_broadcast, vscale_non_broadcast, + voffseto, invvscaleo, !is_broadcast_input_2); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8_signed(*(non_broadcast_input_ptr + x), non_broadcast_qinfo); + const float bfs = dequantize_qasymm8_signed(broadcast_value, broadcast_qinfo); + *(output_ptr + x) = (*scalar_func)(!is_broadcast_input_2 ? bfs : afs, + !is_broadcast_input_2 ? afs : bfs, output_qinfo); + } + }, + broadcast_input, non_broadcast_input, output); + } + else + { + const UniformQuantizationInfo input1_qinfo = in1->info()->quantization_info().uniform(); + const UniformQuantizationInfo input2_qinfo = in2->info()->quantization_info().uniform(); + + // Input1 quantization info + const int32x4_t voffset1 = vdupq_n_s32(input1_qinfo.offset); + const float32x4_t vscale1 = vdupq_n_f32(input1_qinfo.scale); + + // Input2 quantization info + const int32x4_t voffset2 = vdupq_n_s32(input2_qinfo.offset); + const float32x4_t vscale2 = vdupq_n_f32(input2_qinfo.scale); + + // Clear X Dimension on execution window as we handle manually + input1_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + input2_win.set(Window::DimX, Window::Dimension(0, 1, 1)); + + Iterator input1(in1, input1_win); + Iterator input2(in2, input2_win); + Iterator output(out, win); + + execute_window_loop( + win, + [&](const Coordinates &) + { + const auto input1_ptr = reinterpret_cast<const int8_t *>(input1.ptr()); + const auto input2_ptr = reinterpret_cast<const int8_t *>(input2.ptr()); + const auto output_ptr = reinterpret_cast<int8_t *>(output.ptr()); + + int x = (*neon_func)(window_start_x, window_end_x, window_step_x, input1_ptr, input2_ptr, output_ptr, + voffset1, voffset2, vscale1, vscale2, voffseto, invvscaleo); + for (; x < window_end_x; ++x) + { + const float afs = dequantize_qasymm8_signed(*(input1_ptr + x), input1_qinfo); + const float bfs = dequantize_qasymm8_signed(*(input2_ptr + x), input2_qinfo); + *(output_ptr + x) = (*scalar_func)(afs, bfs, output_qinfo); + } + }, + input1, input2, output); + } +} + +template <ArithmeticOperation op> +void elementwise_arithm_op_quantized(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op_quantized(in1, in2, out, window, &elementwise_arithm_op_quantized_scalar<op>, + &elementwise_arithm_op_quantized_broadcast_loop<op>, + &elementwise_arithm_op_quantized_loop<op>); +} + +template <ArithmeticOperation op> +void elementwise_arithm_op_quantized_signed(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op_quantized_signed(in1, in2, out, window, &elementwise_arithm_op_quantized_signed_scalar<op>, + &elementwise_arithm_op_quantized_signed_broadcast_loop<op>, + &elementwise_arithm_op_quantized_singed_loop<op>); +} + +template <ComparisonOperation op> +void elementwise_comp_op_quantized(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_op_quantized(in1, in2, out, window, &elementwise_comp_op_quantized_scalar<op>, + &elementwise_comp_op_quantized_broadcast_loop<op>, + &elementwise_comp_op_quantized_loop<op>); +} + +template <ComparisonOperation op> +void elementwise_comp_op_quantized_signed(const ITensor *in1, const ITensor *in2, ITensor *out, const Window &window) +{ + elementwise_comp_quantized_signed(in1, in2, out, window, &elementwise_comp_op_quantized_scalar<op>, + &elementwise_comp_op_quantized_signed_broadcast_loop<op>, + &elementwise_comp_op_quantized_signed_loop<op>); +} +} // namespace cpu +} // namespace arm_compute + +#endif // ACL_SRC_CPU_KERNELS_ELEMENTWISE_BINARY_GENERIC_NEON_IMPL_H |