diff options
Diffstat (limited to 'src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp | 1027 |
1 files changed, 0 insertions, 1027 deletions
diff --git a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp b/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp deleted file mode 100644 index ca59e66293..0000000000 --- a/src/core/NEON/kernels/NEPixelWiseMultiplicationKernel.cpp +++ /dev/null @@ -1,1027 +0,0 @@ -/* - * Copyright (c) 2016-2020 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. - */ -#include "arm_compute/core/NEON/kernels/NEPixelWiseMultiplicationKernel.h" - -#include "arm_compute/core/CPP/Validate.h" -#include "arm_compute/core/NEON/NEAsymm.h" -#include "arm_compute/core/NEON/NESymm.h" -#include "arm_compute/core/NEON/wrapper/wrapper.h" -#include "arm_compute/core/TensorInfo.h" - -#include <arm_neon.h> - -#if __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -#include <arm_fp16.h> // needed for float16_t -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - -namespace arm_compute -{ -namespace -{ -const float scale255_constant = 1.f / 255.f; -const float32x4_t scale255_constant_f32q = vdupq_n_f32(scale255_constant); -const float32x4_t positive_round_f32q = vdupq_n_f32(0.5f); - -constexpr unsigned int num_elems_processed_per_iteration = 16; - -inline Status validate_arguments(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy) -{ - ARM_COMPUTE_UNUSED(overflow_policy); - ARM_COMPUTE_UNUSED(rounding_policy); - - ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(input1); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::S16, DataType::QSYMM16, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8, DataType::QASYMM8, DataType::QASYMM8_SIGNED, - DataType::S16, DataType::QSYMM16, - DataType::S32, DataType::F16, DataType::F32); - if(is_data_type_quantized(input1->data_type()) || is_data_type_quantized(input2->data_type())) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(overflow_policy == ConvertPolicy::WRAP, "ConvertPolicy cannot be WRAP if datatype is quantized"); - } - - if(output->total_size() > 0) - { - if(is_data_type_quantized(output->data_type())) - { - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input1, input2, output); - } - - const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape()); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::U8 && (input1->data_type() != DataType::U8 || input2->data_type() != DataType::U8), - "Output can only be U8 if both inputs are U8"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::S32 && (input1->data_type() != DataType::QSYMM16 || input2->data_type() != DataType::QSYMM16), - "Output can only be S32 if both inputs are QSYMM16"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(output->data_type() == DataType::S32 && scale != 1.f, "Unsupported scale for QSYMM16 inputs and S32 output"); - } - - if(std::abs(scale - scale255_constant) < 0.00001f) - { - ARM_COMPUTE_RETURN_ERROR_ON(rounding_policy != RoundingPolicy::TO_NEAREST_UP && rounding_policy != RoundingPolicy::TO_NEAREST_EVEN); - } - else - { - ARM_COMPUTE_RETURN_ERROR_ON(rounding_policy != RoundingPolicy::TO_ZERO); - - int exponent = 0; - const float normalized_mantissa = std::frexp(scale, &exponent); - - // Use int scaling if factor is equal to 1/2^n for 0 <= n <= 15 - // frexp returns 0.5 as mantissa which means that the exponent will be in the range of -1 <= e <= 14 - // Moreover, it will be negative as we deal with 1/2^n - ARM_COMPUTE_RETURN_ERROR_ON_MSG(!((normalized_mantissa == 0.5f) && (-14 <= exponent) && (exponent <= 1)), "Scale value not supported (Should be 1/(2^n) or 1/255"); - } - - return Status{}; -} - -inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2); - const ValidRegion &valid_region = broadcast_pair.second; - - // Auto initialize output if not initialized - { - ARM_COMPUTE_UNUSED(set_shape_if_empty(*output, input1->tensor_shape())); - - if(input1->data_type() == DataType::S16 || input2->data_type() == DataType::S16) - { - set_format_if_unknown(*output, Format::S16); - } - else if(input1->data_type() == DataType::F32 || input2->data_type() == DataType::F32) - { - set_format_if_unknown(*output, Format::F32); - } - else if(input1->data_type() == DataType::F16 || input2->data_type() == DataType::F16) - { - set_format_if_unknown(*output, Format::F16); - } - else if(input1->data_type() == DataType::QASYMM8 || input2->data_type() == DataType::QASYMM8) - { - set_data_type_if_unknown(*output, DataType::QASYMM8); - } - else if(input1->data_type() == DataType::QASYMM8_SIGNED || input2->data_type() == DataType::QASYMM8_SIGNED) - { - set_data_type_if_unknown(*output, DataType::QASYMM8_SIGNED); - } - else if(input1->data_type() == DataType::QSYMM16 || input2->data_type() == DataType::QSYMM16) - { - set_data_type_if_unknown(*output, DataType::QSYMM16); - } - } - - // Configure kernel window - Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration)); - Window win_input1 = win.broadcast_if_dimension_le_one(*input1); - Window win_input2 = win.broadcast_if_dimension_le_one(*input2); - - AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration); - - bool window_changed = update_window_and_padding(win_input1, input1_access) - || update_window_and_padding(win_input2, input2_access) - || update_window_and_padding(win, output_access); - - output_access.set_valid_region(win, valid_region); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} - -/* Scales a given vector by 1/255. - * - * @note This does not work for all cases. e.g. for float of 0.49999999999999994 and large floats. - * - * @param in Input vector to scale. - * @return Scaled output rounded to nearest (round half up). - */ -inline int32x4_t scale255_S32_S32(int32x4_t in) -{ - // Scale - const float32x4_t tmp = vmulq_f32(vcvtq_f32_s32(in), scale255_constant_f32q); - // Round to nearest (round half up) - // Add +0.5 for all values - // Afterwards vcvt rounds toward zero - return vcvtq_s32_f32(vaddq_f32(tmp, positive_round_f32q)); -} - -inline uint16x8_t scale255_U16_U16(uint16x8_t in) -{ - const int32x4_t tmp_s1 = scale255_S32_S32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(in)))); - const int32x4_t tmp_s2 = scale255_S32_S32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(in)))); - return vreinterpretq_u16_s16(vcombine_s16(vmovn_s32(tmp_s2), vmovn_s32(tmp_s1))); -} - -inline void mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, - float32x4_t input1_vscale, int32x4_t input1_voffset, float32x4_t input2_vscale, int32x4_t input2_voffset, float32x4_t output_voffset, float32x4_t vinvscale) -{ - const auto input1 = static_cast<const qasymm8_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const qasymm8_t *__restrict>(input2_ptr); - const auto output = static_cast<qasymm8_t *__restrict>(output_ptr); - - const qasymm8x16_t input1_q = vld1q_u8(input1); - const qasymm8x16_t input2_q = vld1q_u8(input2); - - // Dequantitize inputs - float32x4x4_t in1_f32x4x4; - float32x4x4_t in2_f32x4x4; - in1_f32x4x4.val[0] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(input1_q))))), input1_voffset)), input1_vscale); - in1_f32x4x4.val[1] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(input1_q))))), input1_voffset)), input1_vscale); - in1_f32x4x4.val[2] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(input1_q))))), input1_voffset)), input1_vscale); - in1_f32x4x4.val[3] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(input1_q))))), input1_voffset)), input1_vscale); - - in2_f32x4x4.val[0] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_low_u8(input2_q))))), input2_voffset)), input2_vscale); - in2_f32x4x4.val[1] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_low_u8(input2_q))))), input2_voffset)), input2_vscale); - in2_f32x4x4.val[2] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(vmovl_u8(vget_high_u8(input2_q))))), input2_voffset)), input2_vscale); - in2_f32x4x4.val[3] = vmulq_f32(vcvtq_f32_s32(vsubq_s32(vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(vmovl_u8(vget_high_u8(input2_q))))), input2_voffset)), input2_vscale); - - float32x4x4_t out_f32x4x4; - out_f32x4x4.val[0] = vmulq_f32(in1_f32x4x4.val[0], in2_f32x4x4.val[0]); - out_f32x4x4.val[1] = vmulq_f32(in1_f32x4x4.val[1], in2_f32x4x4.val[1]); - out_f32x4x4.val[2] = vmulq_f32(in1_f32x4x4.val[2], in2_f32x4x4.val[2]); - out_f32x4x4.val[3] = vmulq_f32(in1_f32x4x4.val[3], in2_f32x4x4.val[3]); - - int32x4x4_t rf; -#ifdef __aarch64__ - rf.val[0] = vcvtnq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[0], vinvscale)); - rf.val[1] = vcvtnq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[1], vinvscale)); - rf.val[2] = vcvtnq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[2], vinvscale)); - rf.val[3] = vcvtnq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[3], vinvscale)); -#else //__aarch64__ - rf.val[0] = vcvtq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[0], vinvscale)); - rf.val[1] = vcvtq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[1], vinvscale)); - rf.val[2] = vcvtq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[2], vinvscale)); - rf.val[3] = vcvtq_s32_f32(vmlaq_f32(output_voffset, out_f32x4x4.val[3], vinvscale)); -#endif //__aarch64__ - const uint8x8_t pa = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[0]), vqmovn_s32(rf.val[1]))); - const uint8x8_t pb = vqmovun_s16(vcombine_s16(vqmovn_s32(rf.val[2]), vqmovn_s32(rf.val[3]))); - - vst1q_u8(output, vcombine_u8(pa, pb)); -} - -inline void mul_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED_n( - const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, - float scale, const UniformQuantizationInfo &input1_qua_info, const UniformQuantizationInfo &input2_qua_info, - const UniformQuantizationInfo &output_qua_info) - -{ - const auto input1 = static_cast<const qasymm8_signed_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const qasymm8_signed_t *__restrict>(input2_ptr); - const auto output = static_cast<qasymm8_signed_t *__restrict>(output_ptr); - const qasymm8x16_signed_t input1_q = vld1q_s8(input1); - const qasymm8x16_signed_t input2_q = vld1q_s8(input2); - // Dequantitize inputs - const float32x4x4_t in1_f32x4x4 = vdequantize(input1_q, input1_qua_info); - const float32x4x4_t in2_f32x4x4 = vdequantize(input2_q, input2_qua_info); - const UniformQuantizationInfo tmp_qua_info = { output_qua_info.scale / scale, output_qua_info.offset }; - const float32x4x4_t out_f32x4x4 = - { - vmulq_f32(in1_f32x4x4.val[0], in2_f32x4x4.val[0]), - vmulq_f32(in1_f32x4x4.val[1], in2_f32x4x4.val[1]), - vmulq_f32(in1_f32x4x4.val[2], in2_f32x4x4.val[2]), - vmulq_f32(in1_f32x4x4.val[3], in2_f32x4x4.val[3]), - }; - const int8x16_t result = vquantize_signed(out_f32x4x4, tmp_qua_info); - vst1q_s8(output, result); -} - -void mul_saturate_QSYMM16_QSYMM16_QSYMM16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, float scale, - const UniformQuantizationInfo &input1_qua_info, const UniformQuantizationInfo &input2_qua_info, const UniformQuantizationInfo &output_qua_info) -{ - const auto input1 = static_cast<const qsymm16_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const qsymm16_t *__restrict>(input2_ptr); - const auto output = static_cast<qsymm16_t *__restrict>(output_ptr); - - const qsymm16x8x2_t input1_q = - { - { - vld1q_s16(input1), - vld1q_s16(input1 + 8), - } - }; - const qsymm16x8x2_t input2_q = - { - { - vld1q_s16(input2), - vld1q_s16(input2 + 8), - } - }; - - // Dequantitize inputs - const float32x4x4_t in1_f32x4x4 = vdequantize(input1_q, input1_qua_info); - const float32x4x4_t in2_f32x4x4 = vdequantize(input2_q, input2_qua_info); - - const UniformQuantizationInfo tmp_qua_info = { output_qua_info.scale / scale, output_qua_info.offset }; - - const float32x4x4_t out_f32x4x4 = - { - vmulq_f32(in1_f32x4x4.val[0], in2_f32x4x4.val[0]), - vmulq_f32(in1_f32x4x4.val[1], in2_f32x4x4.val[1]), - vmulq_f32(in1_f32x4x4.val[2], in2_f32x4x4.val[2]), - vmulq_f32(in1_f32x4x4.val[3], in2_f32x4x4.val[3]), - }; - - const qsymm16x8x2_t result = vquantize_qsymm16(out_f32x4x4, tmp_qua_info); - vst1q_s16(output, result.val[0]); - vst1q_s16(output + 8, result.val[1]); -} - -void mul_QSYMM16_QSYMM16_S32_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int scale) -{ - ARM_COMPUTE_UNUSED(scale); - const auto input1 = static_cast<const qsymm16_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const qsymm16_t *__restrict>(input2_ptr); - const auto output = static_cast<int32_t *__restrict>(output_ptr); - - const qsymm16x8x2_t input1_q = - { - { - vld1q_s16(input1), - vld1q_s16(input1 + 8), - } - }; - const qsymm16x8x2_t input2_q = - { - { - vld1q_s16(input2), - vld1q_s16(input2 + 8), - } - }; - - const int32x4x4_t in1_s32 = - { - { - vmovl_s16(vget_low_s16(input1_q.val[0])), - vmovl_s16(vget_high_s16(input1_q.val[0])), - vmovl_s16(vget_low_s16(input1_q.val[1])), - vmovl_s16(vget_high_s16(input1_q.val[1])), - } - }; - const int32x4x4_t in2_s32 = - { - { - vmovl_s16(vget_low_s16(input2_q.val[0])), - vmovl_s16(vget_high_s16(input2_q.val[0])), - vmovl_s16(vget_low_s16(input2_q.val[1])), - vmovl_s16(vget_high_s16(input2_q.val[1])), - } - }; - - const int32x4x4_t result = - { - { - vmulq_s32(in1_s32.val[0], in2_s32.val[0]), - vmulq_s32(in1_s32.val[1], in2_s32.val[1]), - vmulq_s32(in1_s32.val[2], in2_s32.val[2]), - vmulq_s32(in1_s32.val[3], in2_s32.val[3]), - } - }; - - vst1q_s32(output, result.val[0]); - vst1q_s32(output + 4, result.val[1]); - vst1q_s32(output + 8, result.val[2]); - vst1q_s32(output + 12, result.val[3]); -} - -template <bool is_scale255, bool is_sat> -void mul_U8_U8_U8_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int n) -{ - const auto input1 = static_cast<const uint8_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const uint8_t *__restrict>(input2_ptr); - const auto output = static_cast<uint8_t *__restrict>(output_ptr); - - const uint8x16_t ta1 = vld1q_u8(input1); - const uint8x16_t ta2 = vld1q_u8(input2); - - uint16x8_t tmp1_high = vmovl_u8(vget_high_u8(ta1)); - const uint16x8_t tmp2_high = vmovl_u8(vget_high_u8(ta2)); - uint16x8_t tmp1_low = vmovl_u8(vget_low_u8(ta1)); - const uint16x8_t tmp2_low = vmovl_u8(vget_low_u8(ta2)); - - tmp1_high = vmulq_u16(tmp1_high, tmp2_high); - tmp1_low = vmulq_u16(tmp1_low, tmp2_low); - - if(is_scale255) - { - tmp1_high = scale255_U16_U16(tmp1_high); - tmp1_low = scale255_U16_U16(tmp1_low); - } - else - { - const int16x8_t vn = vdupq_n_s16(-n); - - if(is_sat) - { - tmp1_high = vqshlq_u16(tmp1_high, vn); - tmp1_low = vqshlq_u16(tmp1_low, vn); - } - else - { - tmp1_high = vshlq_u16(tmp1_high, vn); - tmp1_low = vshlq_u16(tmp1_low, vn); - } - } - - if(is_sat) - { - vst1q_u8(output, vcombine_u8(vqmovn_u16(tmp1_low), vqmovn_u16(tmp1_high))); - } - else - { - vst1q_u8(output, vcombine_u8(vmovn_u16(tmp1_low), vmovn_u16(tmp1_high))); - } -} - -template <bool is_scale255, bool is_sat> -inline int16x8_t mul_S16_S16_S16_n_loop(const int16x8_t &input1, const int16x8_t &input2, int n) -{ - int32x4_t tmp1_high = vmovl_s16(vget_high_s16(input1)); - const int32x4_t tmp2_high = vmovl_s16(vget_high_s16(input2)); - int32x4_t tmp1_low = vmovl_s16(vget_low_s16(input1)); - const int32x4_t tmp2_low = vmovl_s16(vget_low_s16(input2)); - - tmp1_high = vmulq_s32(tmp1_high, tmp2_high); - tmp1_low = vmulq_s32(tmp1_low, tmp2_low); - - if(is_scale255) - { - tmp1_high = scale255_S32_S32(tmp1_high); - tmp1_low = scale255_S32_S32(tmp1_low); - } - else - { - // Right shift amount - const int32x4_t vn = vdupq_n_s32(-n); - // Left shift amount - const int32x4_t vnl = vdupq_n_s32(n); - // Calculate conversion bit - const uint32x4_t tmp1_high_u = vreinterpretq_u32_s32(tmp1_high); - const uint32x4_t tmp1_low_u = vreinterpretq_u32_s32(tmp1_low); - const uint32x4_t sign_high = vshrq_n_u32(tmp1_high_u, 31); - const uint32x4_t sign_low = vshrq_n_u32(tmp1_low_u, 31); - const int32x4_t sign_high_s = vreinterpretq_s32_u32(sign_high); - const int32x4_t sign_low_s = vreinterpretq_s32_u32(sign_low); - const int32x4_t convert_high = vsubq_s32(vshlq_s32(sign_high_s, vnl), sign_high_s); - const int32x4_t convert_low = vsubq_s32(vshlq_s32(sign_low_s, vnl), sign_low_s); - if(is_sat) - { - tmp1_high = vqshlq_s32(vaddq_s32(tmp1_high, convert_high), vn); - tmp1_low = vqshlq_s32(vaddq_s32(tmp1_low, convert_low), vn); - } - else - { - tmp1_high = vshlq_s32(vaddq_s32(tmp1_high, convert_high), vn); - tmp1_low = vshlq_s32(vaddq_s32(tmp1_low, convert_low), vn); - } - } - - if(is_sat) - { - return vcombine_s16(vqmovn_s32(tmp1_low), vqmovn_s32(tmp1_high)); - } - else - { - return vcombine_s16(vmovn_s32(tmp1_low), vmovn_s32(tmp1_high)); - } -} - -template <bool is_scale255, bool is_sat> -inline int16x8x2_t mul_S16_S16_S16_n_k(const int16x8x2_t &input1, const int16x8x2_t &input2, int n) -{ - const int16x8x2_t result = - { - { - // First 8 elements - mul_S16_S16_S16_n_loop<is_scale255, is_sat>(input1.val[0], input2.val[0], n), - // Second 8 elements - mul_S16_S16_S16_n_loop<is_scale255, is_sat>(input1.val[1], input2.val[1], n) - } - }; - - return result; -} - -template <bool is_scale255, bool is_sat> -void mul_S16_S16_S16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int n) -{ - const auto input1 = static_cast<const int16_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const int16_t *__restrict>(input2_ptr); - const auto output = static_cast<int16_t *__restrict>(output_ptr); - - const int16x8x2_t ta1 = - { - { - vld1q_s16(input1), - vld1q_s16(input1 + 8), - } - }; - const int16x8x2_t ta2 = - { - { - vld1q_s16(input2), - vld1q_s16(input2 + 8), - } - }; - const int16x8x2_t result = mul_S16_S16_S16_n_k<is_scale255, is_sat>(ta1, ta2, n); - - vst1q_s16(output, result.val[0]); - vst1q_s16(output + 8, result.val[1]); -} - -void mul_F32_F32_F32_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, float scale) -{ - const auto input1 = static_cast<const float *__restrict>(input1_ptr); - const auto input2 = static_cast<const float *__restrict>(input2_ptr); - const auto output = static_cast<float *__restrict>(output_ptr); - - const float32x4x4_t ta1 = vld4q_f32(input1); - const float32x4x4_t ta2 = vld4q_f32(input2); - const float32x4_t scale_vec = vdupq_n_f32(scale); - const float32x4x4_t result = - { - { - vmulq_f32(vmulq_f32(ta1.val[0], ta2.val[0]), scale_vec), - vmulq_f32(vmulq_f32(ta1.val[1], ta2.val[1]), scale_vec), - vmulq_f32(vmulq_f32(ta1.val[2], ta2.val[2]), scale_vec), - vmulq_f32(vmulq_f32(ta1.val[3], ta2.val[3]), scale_vec) - } - }; - vst4q_f32(output, result); -} - -void c_mul_F32_F32_F32_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr) -{ - const auto input1 = static_cast<const float *__restrict>(input1_ptr); - const auto input2 = static_cast<const float *__restrict>(input2_ptr); - const auto output = static_cast<float *__restrict>(output_ptr); - - const float32x4_t a = wrapper::vloadq(input1); - float32x4_t b = wrapper::vloadq(input2); - - using ExactTagType = typename wrapper::traits::neon_vector<float, 2>::tag_type; - - const float32x4_t mask = { -1.0f, 1.0f, -1.0f, 1.0f }; - const float32x2_t tmp00 = wrapper::vdup_n(wrapper::vgetlane(a, 0), ExactTagType{}); - const float32x2_t tmp01 = wrapper::vdup_n(wrapper::vgetlane(a, 1), ExactTagType{}); - const float32x2_t tmp10 = wrapper::vdup_n(wrapper::vgetlane(a, 2), ExactTagType{}); - const float32x2_t tmp11 = wrapper::vdup_n(wrapper::vgetlane(a, 3), ExactTagType{}); - - const float32x4_t tmp0 = wrapper::vcombine(tmp00, tmp10); - const float32x4_t tmp1 = wrapper::vcombine(tmp01, tmp11); - - float32x4_t res = wrapper::vmul(tmp0, b); - - b = wrapper::vrev64(b); - b = wrapper::vmul(b, mask); - - res = wrapper::vmla(res, tmp1, b); - wrapper::vstore(output, res); -} - -void mul_F16_F16_F16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, float scale) -{ -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - const auto input1 = static_cast<const float16_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const float16_t *__restrict>(input2_ptr); - const auto output = static_cast<float16_t *__restrict>(output_ptr); - const float16x8x2_t ta1 = - { - { - vld1q_f16(input1), - vld1q_f16(input1 + 8), - } - }; - const float16x8x2_t ta2 = - { - { - vld1q_f16(input2), - vld1q_f16(input2 + 8), - } - }; - const float16x8_t scale_vec = vdupq_n_f16(scale); - const float16x8x2_t result = - { - { - vmulq_f16(vmulq_f16(ta1.val[0], ta2.val[0]), scale_vec), - vmulq_f16(vmulq_f16(ta1.val[1], ta2.val[1]), scale_vec), - } - }; - vst1q_f16(output, result.val[0]); - vst1q_f16(output + 8, result.val[1]); -#else /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - ARM_COMPUTE_UNUSED(input1_ptr); - ARM_COMPUTE_UNUSED(input2_ptr); - ARM_COMPUTE_UNUSED(output_ptr); - ARM_COMPUTE_UNUSED(scale); - ARM_COMPUTE_ERROR("Not supported. Recompile the library with arch=arm64-v8.2-a."); -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ -} - -template <bool is_scale255, bool is_sat> -void mul_U8_U8_S16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int n) -{ - const auto input1 = static_cast<const uint8_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const uint8_t *__restrict>(input2_ptr); - const auto output = static_cast<int16_t *__restrict>(output_ptr); - - const uint8x16_t bv = vld1q_u8(input2); - const uint8x16_t av = vld1q_u8(input1); - - uint16x8_t tmp_low = vmovl_u8(vget_low_u8(av)); - uint16x8_t tmp_high = vmovl_u8(vget_high_u8(av)); - tmp_low = vmulq_u16(tmp_low, vmovl_u8(vget_low_u8(bv))); - tmp_high = vmulq_u16(tmp_high, vmovl_u8(vget_high_u8(bv))); - - if(is_scale255) - { - tmp_low = scale255_U16_U16(tmp_low); - tmp_high = scale255_U16_U16(tmp_high); - } - else - { - const int16x8_t vn = vdupq_n_s16(-n); - - if(is_sat) - { - tmp_low = vqshlq_u16(tmp_low, vn); - tmp_high = vqshlq_u16(tmp_high, vn); - } - else - { - tmp_low = vshlq_u16(tmp_low, vn); - tmp_high = vshlq_u16(tmp_high, vn); - } - } - - if(is_sat) - { - static const uint16x8_t max = vdupq_n_u16(SHRT_MAX); - - tmp_low = vminq_u16(tmp_low, max); - tmp_high = vminq_u16(tmp_high, max); - } - - vst1q_s16(output, vreinterpretq_s16_u16(tmp_low)); - vst1q_s16(output + 8, vreinterpretq_s16_u16(tmp_high)); -} - -template <bool is_scale255, bool is_sat> -void mul_S16_U8_S16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int n) -{ - const auto input1 = static_cast<const int16_t *__restrict>(input1_ptr); - const auto input2 = static_cast<const uint8_t *__restrict>(input2_ptr); - const auto output = static_cast<int16_t *__restrict>(output_ptr); - - const int16x8x2_t ta1 = - { - { - vld1q_s16(input1), - vld1q_s16(input1 + 8), - } - }; - const uint8x8x2_t ta2u = - { - { - vld1_u8(input2), - vld1_u8(input2 + 8), - } - }; - const int16x8x2_t ta2 = - { - { - vreinterpretq_s16_u16(vmovl_u8(ta2u.val[0])), - vreinterpretq_s16_u16(vmovl_u8(ta2u.val[1])) - } - }; - - const int16x8x2_t result = mul_S16_S16_S16_n_k<is_scale255, is_sat>(ta1, ta2, n); - - vst1q_s16(output, result.val[0]); - vst1q_s16(output + 8, result.val[1]); -} - -template <bool is_scale255, bool is_sat> -void mul_U8_S16_S16_n(const void *__restrict input1_ptr, const void *__restrict input2_ptr, void *__restrict output_ptr, int n) -{ - // Simply swap the two input buffers - mul_S16_U8_S16_n<is_scale255, is_sat>(input2_ptr, input1_ptr, output_ptr, n); -} -} // namespace - -NEPixelWiseMultiplicationKernel::NEPixelWiseMultiplicationKernel() - : _func_float(nullptr), _func_int(nullptr), _func_quantized(nullptr), _input1(nullptr), _input2(nullptr), _output(nullptr), _scale{ 0 }, _scale_exponent{ 0 }, _run_optimized_qasymm8(false) -{ -} - -void NEPixelWiseMultiplicationKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output, float scale, ConvertPolicy overflow_policy, RoundingPolicy rounding_policy) -{ - ARM_COMPUTE_UNUSED(rounding_policy); - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input1->info(), input2->info(), output->info(), scale, overflow_policy, rounding_policy)); - - // Configure kernel window - auto win_config = validate_and_configure_window(input1->info(), input2->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - _input1 = input1; - _input2 = input2; - _output = output; - _scale = scale; - _scale_exponent = 0; - _func_quantized = nullptr; - _func_int = nullptr; - _func_float = nullptr; - _run_optimized_qasymm8 = false; - - bool is_scale_255 = false; - // Check and validate scaling factor - if(std::abs(scale - scale255_constant) < 0.00001f) - { - is_scale_255 = true; - } - else - { - int exponent = 0; - - std::frexp(scale, &exponent); - - // Store the positive exponent. We know that we compute 1/2^n - // Additionally we need to subtract 1 to compensate that frexp used a mantissa of 0.5 - _scale_exponent = std::abs(exponent - 1); - } - - const DataType dt_input1 = input1->info()->data_type(); - const DataType dt_input2 = input2->info()->data_type(); - const DataType dt_output = output->info()->data_type(); - const bool is_sat = (overflow_policy == ConvertPolicy::SATURATE); - - if(dt_input1 == DataType::QASYMM8 && dt_input2 == DataType::QASYMM8) - { - _run_optimized_qasymm8 = true; - } - else if(dt_input1 == DataType::QASYMM8_SIGNED && dt_input2 == DataType::QASYMM8_SIGNED) - { - _func_quantized = &mul_saturate_QASYMM8_SIGNED_QASYMM8_SIGNED_QASYMM8_SIGNED_n; - } - else if(dt_input1 == DataType::QSYMM16 && dt_input2 == DataType::QSYMM16 && dt_output == DataType::QSYMM16) - { - _func_quantized = &mul_saturate_QSYMM16_QSYMM16_QSYMM16_n; - } - else if(dt_input1 == DataType::QSYMM16 && dt_input2 == DataType::QSYMM16 && dt_output == DataType::S32) - { - _func_int = &mul_QSYMM16_QSYMM16_S32_n; - } - else if(DataType::U8 == dt_input1 && DataType::U8 == dt_input2 && DataType::U8 == dt_output) - { - if(is_scale_255) - { - _func_int = is_sat ? &mul_U8_U8_U8_n<true, true> : &mul_U8_U8_U8_n<true, false>; - } - else - { - _func_int = is_sat ? &mul_U8_U8_U8_n<false, true> : &mul_U8_U8_U8_n<false, false>; - } - } - else if(DataType::S16 == dt_input1 && DataType::S16 == dt_input2 && DataType::S16 == dt_output) - { - if(is_scale_255) - { - _func_int = is_sat ? &mul_S16_S16_S16_n<true, true> : &mul_S16_S16_S16_n<true, false>; - } - else - { - _func_int = is_sat ? &mul_S16_S16_S16_n<false, true> : &mul_S16_S16_S16_n<false, false>; - } - } - else if(DataType::S16 == dt_input1 && DataType::U8 == dt_input2 && DataType::S16 == dt_output) - { - if(is_scale_255) - { - _func_int = is_sat ? &mul_S16_U8_S16_n<true, true> : &mul_S16_U8_S16_n<true, false>; - } - else - { - _func_int = is_sat ? &mul_S16_U8_S16_n<false, true> : &mul_S16_U8_S16_n<false, false>; - } - } - else if(DataType::U8 == dt_input1 && DataType::S16 == dt_input2 && DataType::S16 == dt_output) - { - if(is_scale_255) - { - _func_int = is_sat ? &mul_U8_S16_S16_n<true, true> : &mul_U8_S16_S16_n<true, false>; - } - else - { - _func_int = is_sat ? &mul_U8_S16_S16_n<false, true> : &mul_U8_S16_S16_n<false, false>; - } - } - else if(DataType::U8 == dt_input1 && DataType::U8 == dt_input2 && DataType::S16 == dt_output) - { - if(is_scale_255) - { - _func_int = is_sat ? &mul_U8_U8_S16_n<true, true> : &mul_U8_U8_S16_n<true, false>; - } - else - { - _func_int = is_sat ? &mul_U8_U8_S16_n<false, true> : &mul_U8_U8_S16_n<false, false>; - } - } - else if(DataType::F16 == dt_input1 && DataType::F16 == dt_input2 && DataType::F16 == dt_output) - { - _func_float = &mul_F16_F16_F16_n; - _func_int = nullptr; - } - else if(DataType::F32 == dt_input1 && DataType::F32 == dt_input2 && DataType::F32 == dt_output) - { - _func_float = &mul_F32_F32_F32_n; - _func_int = nullptr; - } - else - { - ARM_COMPUTE_ERROR("You called with the wrong img formats"); - } - - INEKernel::configure(win_config.second); -} - -Status NEPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output, float scale, ConvertPolicy overflow_policy, - RoundingPolicy rounding_policy) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input1, input2, output, scale, overflow_policy, rounding_policy)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input1->clone().get(), input2->clone().get(), output->clone().get()).first); - - return Status{}; -} - -void NEPixelWiseMultiplicationKernel::run(const Window &window, const ThreadInfo &info) -{ - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - - const TensorShape &in_shape1 = _input1->info()->tensor_shape(); - const TensorShape &in_shape2 = _input2->info()->tensor_shape(); - const TensorShape &out_shape = _output->info()->tensor_shape(); - - bool can_collapse = true; - if(std::min(in_shape1.total_size(), in_shape2.total_size()) > 1) - { - can_collapse = (std::min(in_shape1.num_dimensions(), in_shape2.num_dimensions()) > Window::DimZ); - for(size_t d = Window::DimZ; can_collapse && (d < out_shape.num_dimensions()); ++d) - { - can_collapse = (in_shape1[d] == in_shape2[d]); - } - } - - bool has_collapsed = false; - Window collapsed = can_collapse ? window.collapse_if_possible(INEKernel::window(), Window::DimZ, &has_collapsed) : window; - - const TensorShape &in_shape1_collapsed = has_collapsed ? in_shape1.collapsed_from(Window::DimZ) : in_shape1; - const TensorShape &in_shape2_collapsed = has_collapsed ? in_shape2.collapsed_from(Window::DimZ) : in_shape2; - - Window slice = collapsed.first_slice_window_3D(); - Window slice_input1 = slice.broadcast_if_dimension_le_one(in_shape1_collapsed); - Window slice_input2 = slice.broadcast_if_dimension_le_one(in_shape2_collapsed); - - Iterator input1(_input1, slice_input1); - Iterator input2(_input2, slice_input2); - Iterator output(_output, slice); - - if((_run_optimized_qasymm8) || (_func_quantized != nullptr)) - { - if(_run_optimized_qasymm8) - { - const int32x4_t input1_voffset = vdupq_n_s32(_input1->info()->quantization_info().uniform().offset); - const float32x4_t input1_vscale = vdupq_n_f32(_input1->info()->quantization_info().uniform().scale); - const int32x4_t input2_voffset = vdupq_n_s32(_input2->info()->quantization_info().uniform().offset); - const float32x4_t input2_vscale = vdupq_n_f32(_input2->info()->quantization_info().uniform().scale); - const float32x4_t output_voffset = vdupq_n_f32(static_cast<float>(_output->info()->quantization_info().uniform().offset)); - const float output_scale = _output->info()->quantization_info().uniform().scale; - const float32x4_t vinvscale = vdupq_n_f32(1.f / (output_scale / _scale)); - - execute_window_loop(collapsed, [&](const Coordinates &) - { - mul_saturate_QASYMM8_QASYMM8_QASYMM8_n_opt(input1.ptr(), input2.ptr(), output.ptr(), - input1_vscale, input1_voffset, input2_vscale, input2_voffset, output_voffset, vinvscale); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - }, - input1, input2, output); - } - else - { - execute_window_loop(collapsed, [&](const Coordinates &) - { - (*_func_quantized)(input1.ptr(), input2.ptr(), output.ptr(), _scale, - _input1->info()->quantization_info().uniform(), _input2->info()->quantization_info().uniform(), _output->info()->quantization_info().uniform()); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - }, - input1, input2, output); - } - } - else if(_func_int != nullptr) - { - execute_window_loop(collapsed, [&](const Coordinates &) - { - (*_func_int)(input1.ptr(), input2.ptr(), output.ptr(), _scale_exponent); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - }, - input1, input2, output); - } - else - { - ARM_COMPUTE_ERROR_ON(_func_float == nullptr); - execute_window_loop(collapsed, [&](const Coordinates &) - { - (*_func_float)(input1.ptr(), input2.ptr(), output.ptr(), _scale); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input1)); - ARM_COMPUTE_UNUSED(collapsed.slide_window_slice_3D(slice_input2)); - }, - input1, input2, output); - } -} - -BorderSize NEPixelWiseMultiplicationKernel::border_size() const -{ - const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0)); - const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration - 1U, replicateSize); - return BorderSize{ 0, border, 0, 0 }; -} - -namespace -{ -constexpr unsigned int num_elems_processed_per_iteration_complex = 2; - -Status validate_arguments_complex(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) -{ - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input1, 2, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input2, 2, DataType::F32); - - const TensorShape &out_shape = TensorShape::broadcast_shape(input1->tensor_shape(), input2->tensor_shape()); - - ARM_COMPUTE_RETURN_ERROR_ON_MSG(out_shape.total_size() == 0, "Inputs are not broadcast compatible"); - - // Validate in case of configured output - if(output->total_size() > 0) - { - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 2, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(detail::have_different_dimensions(out_shape, output->tensor_shape(), 0), "Wrong shape for output"); - } - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window_complex(ITensorInfo *input1, ITensorInfo *input2, ITensorInfo *output) -{ - const std::pair<TensorShape, ValidRegion> broadcast_pair = ITensorInfo::broadcast_shape_and_valid_region(*input1, *input2); - const TensorShape &out_shape = broadcast_pair.first; - const ValidRegion &valid_region = broadcast_pair.second; - - // Auto initialize output if not initialized - const TensorInfo out_info(out_shape, input1->num_channels(), input1->data_type()); - auto_init_if_empty(*output, out_info); - - Window win = calculate_max_window(valid_region, Steps(num_elems_processed_per_iteration_complex)); - Window win_input1 = win.broadcast_if_dimension_le_one(*input1); - Window win_input2 = win.broadcast_if_dimension_le_one(*input2); - - AccessWindowHorizontal input1_access(input1, 0, num_elems_processed_per_iteration_complex); - AccessWindowHorizontal input2_access(input2, 0, num_elems_processed_per_iteration_complex); - AccessWindowHorizontal output_access(output, 0, num_elems_processed_per_iteration_complex); - - bool window_changed = update_window_and_padding(win_input1, input1_access) - || update_window_and_padding(win_input2, input2_access) - || update_window_and_padding(win, output_access); - - output_access.set_valid_region(win, valid_region); - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -NEComplexPixelWiseMultiplicationKernel::NEComplexPixelWiseMultiplicationKernel() - : _input1(nullptr), _input2(nullptr), _output(nullptr) -{ -} - -void NEComplexPixelWiseMultiplicationKernel::configure(const ITensor *input1, const ITensor *input2, ITensor *output) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_complex(input1->info(), input2->info(), output->info())); - - // Configure kernel window - auto win_config = validate_and_configure_window_complex(input1->info(), input2->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - - _input1 = input1; - _input2 = input2; - _output = output; - - // Create kernel - INEKernel::configure(win_config.second); -} - -Status NEComplexPixelWiseMultiplicationKernel::validate(const ITensorInfo *input1, const ITensorInfo *input2, const ITensorInfo *output) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input1, input2, output); - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_complex(input1, input2, output)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window_complex(input1->clone().get(), input2->clone().get(), output->clone().get()).first); - - return Status{}; -} - -void NEComplexPixelWiseMultiplicationKernel::run(const Window &window, const ThreadInfo &info) -{ - ARM_COMPUTE_UNUSED(info); - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - - Iterator input1(_input1, window.broadcast_if_dimension_le_one(_input1->info()->tensor_shape())); - Iterator input2(_input2, window.broadcast_if_dimension_le_one(_input2->info()->tensor_shape())); - Iterator output(_output, window); - - execute_window_loop(window, [&](const Coordinates &) - { - c_mul_F32_F32_F32_n(input1.ptr(), input2.ptr(), output.ptr()); - }, - input1, input2, output); -} - -BorderSize NEComplexPixelWiseMultiplicationKernel::border_size() const -{ - const unsigned int replicateSize = _output->info()->dimension(0) - std::min(_input1->info()->dimension(0), _input2->info()->dimension(0)); - const unsigned int border = std::min<unsigned int>(num_elems_processed_per_iteration_complex - 1U, replicateSize); - return { 0, border, 0, 0 }; -} -} // namespace arm_compute |