From ddb93bbf12fc9d685e7ddbef703a886d67cbda9b Mon Sep 17 00:00:00 2001 From: Georgios Pinitas Date: Fri, 2 Oct 2020 16:38:59 +0100 Subject: COMPMID-3637: Move wrapper to src Signed-off-by: Georgios Pinitas Change-Id: I524b0c4b49c7a7035b7d078b9585d77b0d438e10 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4083 Reviewed-by: Michele Di Giorgio Reviewed-by: Michalis Spyrou Comments-Addressed: Arm Jenkins --- .../kernels/detail/NEDirectConvolutionDetail.h | 965 --------------------- 1 file changed, 965 deletions(-) delete mode 100644 arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h (limited to 'arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h') diff --git a/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h b/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h deleted file mode 100644 index 78f08fdca6..0000000000 --- a/arm_compute/core/NEON/kernels/detail/NEDirectConvolutionDetail.h +++ /dev/null @@ -1,965 +0,0 @@ -/* - * Copyright (c) 2017-2020 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. - */ - -#ifndef ARM_COMPUTE_NEDIRECTCONVOLUTIONDETAIL_H -#define ARM_COMPUTE_NEDIRECTCONVOLUTIONDETAIL_H - -#include "arm_compute/core/AccessWindowStatic.h" -#include "arm_compute/core/NEON/NEFixedPoint.h" -#include "arm_compute/core/NEON/wrapper/wrapper.h" -#include "arm_compute/core/utils/misc/Requires.h" - -#include - -namespace arm_compute -{ -namespace detail -{ -/** Loads a 3x3 matrix as a row (float). - * - * @param[in] ptr Pointer to a float 3x3 matrix. - * @param[in] weights_offset (Optional) Weights quantization offset. - * - * @return The loaded matrix. - */ -inline float32x4x3_t load_matrix_row(const float *ptr, int weights_offset = 0) -{ - ARM_COMPUTE_UNUSED(weights_offset); - const float32x4x3_t r = - { - { - vld1q_dup_f32(ptr), - vld1q_dup_f32(1 + ptr), - vld1q_dup_f32(2 + ptr) - } - }; - return r; -} - -/** Loads a 3x3 matrix as a row (uint8_t/int8_t). - * - * @param[in] ptr Pointer to a uint8_t/int8_t 3x3 matrix. - * @param[in] weights_offset (Optional) Weights quantization offset. - * - * @return The loaded matrix. - */ -template < typename T, REQUIRES_TA(std::is_same::value || std::is_same::value) > -inline int32x4x3_t load_matrix_row(const T *ptr, int weights_offset = 0) -{ - const int32x4_t v_weights_offset = vdupq_n_s32(weights_offset); - - /* ptr is a pointer to a row in a 3x3 matrix, the function returns 3 vectors holding exactly the same value in all lanes: - r.val[0] contains the first element, r.val[1] the second element and r.val[2] the third element (in all lanes) */ - int32x4x3_t r = - { - { - vaddq_s32(v_weights_offset, vdupq_n_s32(*ptr)), - vaddq_s32(v_weights_offset, vdupq_n_s32(*(ptr + 1))), - vaddq_s32(v_weights_offset, vdupq_n_s32(*(ptr + 2))) - } - }; - return r; -} - -/** Stores a float32x4x2_t array into a memory location. - * - * @param[in] buffer Pointer to the memory location where the values will be stored. - * @param[in] values Values that will be stored. - * - */ -template -void store_results(float *buffer, const float32x4x2_t &values); - -template <> -inline void store_results<1>(float *buffer, const float32x4x2_t &values) -{ - vst1q_f32(buffer, values.val[0]); - vst1q_f32(buffer + 4, values.val[1]); -} - -template <> -inline void store_results<2>(float *buffer, const float32x4x2_t &values) -{ - vst1q_f32(buffer, values.val[0]); -} - -template <> -inline void store_results<3>(float *buffer, const float32x4x2_t &values) -{ - vst1_f32(buffer, vget_low_f32(values.val[0])); -} - -/** Stores a uint32_t array into a memory location. - * - * @param[in] buffer Pointer to the memory location where the values will be stored. - * @param[in] values Values that will be stored. - * - */ -template -void store_results(int32_t *buffer, const int32x4x2_t &values); - -template <> -inline void store_results<1>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1q_s32(buffer, values.val[0]); - vst1q_s32(buffer + 4, values.val[1]); -} - -template <> -inline void store_results<2>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1q_s32(buffer, values.val[0]); -} - -template <> -inline void store_results<3>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1_s32(buffer, vget_low_s32(values.val[0])); -} - -template -inline void accumulate_results(float *buffer, const float32x4x2_t &values); - -template <> -inline void accumulate_results<1>(float *buffer, const float32x4x2_t &values) -{ - vst1q_f32(buffer, vaddq_f32(vld1q_f32(buffer), values.val[0])); - vst1q_f32(buffer + 4, vaddq_f32(vld1q_f32(buffer + 4), values.val[1])); -} - -template <> -inline void accumulate_results<2>(float *buffer, const float32x4x2_t &values) -{ - vst1q_f32(buffer, vaddq_f32(vld1q_f32(buffer), values.val[0])); -} - -template <> -inline void accumulate_results<3>(float *buffer, const float32x4x2_t &values) -{ - vst1_f32(buffer, vadd_f32(vld1_f32(buffer), vget_low_f32(values.val[0]))); -} - -template -void accumulate_results(int32_t *buffer, const int32x4x2_t &values); - -template <> -inline void accumulate_results<1>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1q_s32(buffer, vaddq_s32(vld1q_s32(buffer), values.val[0])); - vst1q_s32(buffer + 4, vaddq_s32(vld1q_s32(buffer + 4), values.val[1])); -} - -template <> -inline void accumulate_results<2>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1q_s32(buffer, vaddq_s32(vld1q_s32(buffer), values.val[0])); -} - -template <> -inline void accumulate_results<3>(int32_t *buffer, const int32x4x2_t &values) -{ - vst1_s32(buffer, vadd_s32(vld1_s32(buffer), vget_low_s32(values.val[0]))); -} - -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -/** Stores a float16x8x2_t array into a memory location. - * - * @param[in] buffer Pointer to the memory location where the values will be stored. - * @param[in] values Values that will be stored. - * - */ -template -void store_results(float16_t *buffer, const float16x8x2_t &values); - -template <> -inline void store_results<1>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1q_f16(buffer, values.val[0]); - vst1q_f16(buffer + 8, values.val[1]); -} - -template <> -inline void store_results<2>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1q_f16(buffer, values.val[0]); -} - -template <> -inline void store_results<3>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1_f16(buffer, vget_low_f16(values.val[0])); -} - -template -inline void accumulate_results(float16_t *buffer, const float16x8x2_t &values); - -template <> -inline void accumulate_results<1>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1q_f16(buffer, vaddq_f16(vld1q_f16(buffer), values.val[0])); - vst1q_f16(buffer + 8, vaddq_f16(vld1q_f16(buffer + 8), values.val[1])); -} - -template <> -inline void accumulate_results<2>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1q_f16(buffer, vaddq_f16(vld1q_f16(buffer), values.val[0])); -} - -template <> -inline void accumulate_results<3>(float16_t *buffer, const float16x8x2_t &values) -{ - vst1_f16(buffer, vadd_f16(vld1_f16(buffer), vget_low_f16(values.val[0]))); -} -#endif /* __ARM_FEATURE_FP16_VECTOR_ARITHMETIC */ - -/** Perform a 3x3 convolution for 4 consecutive elements on float32 when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] input_offset (Optional) Input quantization offset. - * - */ -inline float32x4_t single_convolve_3x3_dilation(const float *in_top, const float *in_mid, const float *in_low, - const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, - const size_t dilation_x, int input_offset) -{ - ARM_COMPUTE_UNUSED(input_offset); - - const float32x4x3_t vtop = - { - { - vld1q_f32(in_top), - vld1q_f32(in_top + dilation_x), - vld1q_f32(in_top + 2 * dilation_x) - } - }; - const float32x4x3_t vmid = - { - { - vld1q_f32(in_mid), - vld1q_f32(in_mid + dilation_x), - vld1q_f32(in_mid + 2 * dilation_x) - } - }; - const float32x4x3_t vlow = - { - { - vld1q_f32(in_low), - vld1q_f32(in_low + dilation_x), - vld1q_f32(in_low + 2 * dilation_x) - } - }; - float32x4_t out = vmulq_f32(vtop.val[0], m0.val[0]); - out = vmlaq_f32(out, vtop.val[1], m0.val[1]); - out = vmlaq_f32(out, vtop.val[2], m0.val[2]); - - out = vmlaq_f32(out, vmid.val[0], m1.val[0]); - out = vmlaq_f32(out, vmid.val[1], m1.val[1]); - out = vmlaq_f32(out, vmid.val[2], m1.val[2]); - - out = vmlaq_f32(out, vlow.val[0], m2.val[0]); - out = vmlaq_f32(out, vlow.val[1], m2.val[1]); - out = vmlaq_f32(out, vlow.val[2], m2.val[2]); - - return out; -} - -/** Perform a 3x3 convolution for 8 consecutive elements on float32 when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset (Optional) Input quantization offset. - * - */ -inline float32x4x2_t convolve_3x3_dilation(const float *in_top, const float *in_mid, const float *in_low, - const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, - const size_t dilation_x, unsigned int stridex, int input_offset = 0) -{ - ARM_COMPUTE_ERROR_ON(stridex > 3); - float32x4x2_t out = - { - { - single_convolve_3x3_dilation(in_top, in_mid, in_low, m0, m1, m2, dilation_x, input_offset), - single_convolve_3x3_dilation(in_top + 4, in_mid + 4, in_low + 4, m0, m1, m2, dilation_x, input_offset) - } - }; - - if(stridex == 2) - { - out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 2), out.val[0], 1); - out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 0), out.val[0], 2); - out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[1], 2), out.val[0], 3); - } - else if(stridex == 3) - { - out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 3), out.val[0], 1); - } - - return out; -} - -/** Perform a convolve3x3 on float32. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[out] out_ptr Pointer to the output. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset (Optional) Input quantization offset. - * - */ -template -void convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, float *out_ptr, - const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, - unsigned int stridex, int input_offset = 0); - -template -inline void convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, float *out_ptr, - const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, - unsigned int stridex, int input_offset) -{ - ARM_COMPUTE_UNUSED(input_offset); - ARM_COMPUTE_ERROR_ON(stridex > 3); - - float32x4x2_t out = - { - { - vdupq_n_f32(0.f), - vdupq_n_f32(0.f) - } - }; - if(stridex == 2) - { - const float32x4x2_t vtop = vld2q_f32(in_top); - const float32x4x2_t vmid = vld2q_f32(in_mid); - const float32x4x2_t vlow = vld2q_f32(in_low); - const float32x4_t vtop_end = vld1q_f32(in_top + 8); - const float32x4_t vmid_end = vld1q_f32(in_mid + 8); - const float32x4_t vlow_end = vld1q_f32(in_low + 8); - - out.val[0] = vmulq_f32(vtop.val[0], m0.val[0]); - - out.val[0] = vmlaq_f32(out.val[0], vtop.val[1], m0.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop_end, 1), m0.val[2]); - - out.val[0] = vmlaq_f32(out.val[0], vmid.val[0], m1.val[0]); - out.val[0] = vmlaq_f32(out.val[0], vmid.val[1], m1.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid_end, 1), m1.val[2]); - - out.val[0] = vmlaq_f32(out.val[0], vlow.val[0], m2.val[0]); - out.val[0] = vmlaq_f32(out.val[0], vlow.val[1], m2.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow_end, 1), m2.val[2]); - - accumulate ? accumulate_results<2>(out_ptr, out) : store_results<2>(out_ptr, out); - } - else - { - const float32x4x3_t vtop = - { - { - vld1q_f32(in_top), - vld1q_f32(in_top + 4), - vld1q_f32(in_top + 8) - } - }; - const float32x4x3_t vmid = - { - { - vld1q_f32(in_mid), - vld1q_f32(in_mid + 4), - vld1q_f32(in_mid + 8) - } - }; - const float32x4x3_t vlow = - { - { - vld1q_f32(in_low), - vld1q_f32(in_low + 4), - vld1q_f32(in_low + 8) - } - }; - out.val[0] = vmulq_f32(vtop.val[0], m0.val[0]); - out.val[1] = vmulq_f32(vtop.val[1], m0.val[0]); - - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 1), m0.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vtop.val[0], vtop.val[1], 2), m0.val[2]); - - out.val[0] = vmlaq_f32(out.val[0], vmid.val[0], m1.val[0]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 1), m1.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vmid.val[0], vmid.val[1], 2), m1.val[2]); - - out.val[0] = vmlaq_f32(out.val[0], vlow.val[0], m2.val[0]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 1), m2.val[1]); - out.val[0] = vmlaq_f32(out.val[0], vextq_f32(vlow.val[0], vlow.val[1], 2), m2.val[2]); - - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 1), m0.val[1]); - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vtop.val[1], vtop.val[2], 2), m0.val[2]); - - out.val[1] = vmlaq_f32(out.val[1], vmid.val[1], m1.val[0]); - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 1), m1.val[1]); - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vmid.val[1], vmid.val[2], 2), m1.val[2]); - - out.val[1] = vmlaq_f32(out.val[1], vlow.val[1], m2.val[0]); - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 1), m2.val[1]); - out.val[1] = vmlaq_f32(out.val[1], vextq_f32(vlow.val[1], vlow.val[2], 2), m2.val[2]); - - if(stridex == 3) - { - out.val[0] = vsetq_lane_f32(vgetq_lane_f32(out.val[0], 3), out.val[0], 1); - accumulate ? accumulate_results<3>(out_ptr, out) : store_results<3>(out_ptr, out); - } - else - { - accumulate ? accumulate_results<1>(out_ptr, out) : store_results<1>(out_ptr, out); - } - } -} - -/** Perform a 3x3 convolution for 4 consecutive 8-bit elements when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] input_offset Input quantization offset. - * - */ -template < typename T, REQUIRES_TA(std::is_same::value || std::is_same::value) > -inline int32x4_t single_convolve_3x3_dilation(const T *in_top, const T *in_mid, const T *in_low, - const int32x4x3_t &m0, const int32x4x3_t &m1, const int32x4x3_t &m2, - size_t dilation_x, int32_t input_offset) -{ - using VectorType = typename std::conditional::value, uint8x8x3_t, int8x8x3_t>::type; - using OutputTagType = typename wrapper::traits::neon_bitvector_tag_t; - - const int32x4_t v_input_offset = wrapper::vdup_n(input_offset, OutputTagType{}); - - const VectorType vtop = - { - { - wrapper::vload(in_top), - wrapper::vload(in_top + dilation_x), - wrapper::vload(in_top + 2 * dilation_x) - } - }; - const VectorType vmid = - { - { - wrapper::vload(in_mid), - wrapper::vload(in_mid + dilation_x), - wrapper::vload(in_mid + 2 * dilation_x) - } - }; - const VectorType vlow = - { - { - wrapper::vload(in_low), - wrapper::vload(in_low + dilation_x), - wrapper::vload(in_low + 2 * dilation_x) - } - }; - - const int32x4x3_t vtop_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vtop.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vtop.val[1])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vtop.val[2])))), - } - }; - const int32x4x3_t vmid_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vmid.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vmid.val[1])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vmid.val[2])))), - } - }; - const int32x4x3_t vlow_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vlow.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vlow.val[1])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vlow.val[2])))), - } - }; - - int32x4_t out = wrapper::vmul(vtop_s32.val[0], m0.val[0]); - out = wrapper::vmla(out, vtop_s32.val[1], m0.val[1]); - out = wrapper::vmla(out, vtop_s32.val[2], m0.val[2]); - - out = wrapper::vmla(out, vmid_s32.val[0], m1.val[0]); - out = wrapper::vmla(out, vmid_s32.val[1], m1.val[1]); - out = wrapper::vmla(out, vmid_s32.val[2], m1.val[2]); - - out = wrapper::vmla(out, vlow_s32.val[0], m2.val[0]); - out = wrapper::vmla(out, vlow_s32.val[1], m2.val[1]); - out = wrapper::vmla(out, vlow_s32.val[2], m2.val[2]); - - return out; -} - -/** Perform a 3x3 convolution for 4 consecutive 8-bit elements when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset Input quantization offset. - * - */ -template < typename T, REQUIRES_TA(std::is_same::value || std::is_same::value) > -inline int32x4x2_t convolve_3x3_dilation(const T *in_top, const T *in_mid, const T *in_low, const int32x4x3_t &m0, const int32x4x3_t &m1, const int32x4x3_t &m2, - const size_t dilation_x, unsigned int stridex, int input_offset) -{ - ARM_COMPUTE_ERROR_ON(stridex > 3); - int32x4x2_t out = - { - { - single_convolve_3x3_dilation(in_top, in_mid, in_low, m0, m1, m2, dilation_x, input_offset), - single_convolve_3x3_dilation(in_top + 4, in_mid + 4, in_low + 4, m0, m1, m2, dilation_x, input_offset) - } - }; - - if(stridex == 2) - { - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[0], 2), out.val[0], 1); - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[1], 0), out.val[0], 2); - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[1], 2), out.val[0], 3); - } - else if(stridex == 3) - { - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[0], 3), out.val[0], 1); - } - return out; -} - -/** Perform a convolve3x3 on 8-bit elements - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[out] out_ptr Pointer to the output. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset Input quantization offset. - * - */ -template < bool accumulate, typename T1, typename T2, REQUIRES_TA(std::is_same::value || std::is_same::value) > -void convolve_3x3(const T1 *in_top, const T1 *in_mid, const T1 *in_low, T2 *out_ptr, - const int32x4x3_t &m0, const int32x4x3_t &m1, const int32x4x3_t &m2, - unsigned int stridex, int32_t input_offset) -{ - ARM_COMPUTE_ERROR_ON(stridex > 3); - using VectorType = typename std::conditional::value, uint8x8x2_t, int8x8x2_t>::type; - using OutputTagType = typename wrapper::traits::neon_bitvector_tag_t; - - const int32x4_t v_input_offset = wrapper::vdup_n(input_offset, OutputTagType{}); - - const VectorType vtop = - { - { - wrapper::vload(in_top), - wrapper::vload(in_top + 8) - } - }; - const VectorType vmid = - { - { - wrapper::vload(in_mid), - wrapper::vload(in_mid + 8) - } - }; - const VectorType vlow = - { - { - wrapper::vload(in_low), - wrapper::vload(in_low + 8) - } - }; - - const int32x4x3_t vtop_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vtop.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgethigh(wrapper::vmovl(vtop.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vtop.val[1])))), - } - }; - const int32x4x3_t vmid_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vmid.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgethigh(wrapper::vmovl(vmid.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vmid.val[1])))), - } - }; - const int32x4x3_t vlow_s32 = - { - { - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vlow.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgethigh(wrapper::vmovl(vlow.val[0])))), - wrapper::vaddw(v_input_offset, wrapper::vreinterpret(wrapper::vgetlow(wrapper::vmovl(vlow.val[1])))), - } - }; - - int32x4x2_t out - { - { - wrapper::vdup_n(static_cast(0), OutputTagType{}), - wrapper::vdup_n(static_cast(0), OutputTagType{}), - } - }; - - // 0 - out.val[0] = wrapper::vmla(out.val[0], vtop_s32.val[0], m0.val[0]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_1(vtop_s32.val[0], vtop_s32.val[1]), m0.val[1]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_2(vtop_s32.val[0], vtop_s32.val[1]), m0.val[2]); - - out.val[0] = wrapper::vmla(out.val[0], vmid_s32.val[0], m1.val[0]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_1(vmid_s32.val[0], vmid_s32.val[1]), m1.val[1]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_2(vmid_s32.val[0], vmid_s32.val[1]), m1.val[2]); - - out.val[0] = wrapper::vmla(out.val[0], vlow_s32.val[0], m2.val[0]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_1(vlow_s32.val[0], vlow_s32.val[1]), m2.val[1]); - out.val[0] = wrapper::vmla(out.val[0], wrapper::vext_2(vlow_s32.val[0], vlow_s32.val[1]), m2.val[2]); - - // 1 - out.val[1] = wrapper::vmla(out.val[1], vtop_s32.val[1], m0.val[0]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_1(vtop_s32.val[1], vtop_s32.val[2]), m0.val[1]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_2(vtop_s32.val[1], vtop_s32.val[2]), m0.val[2]); - - out.val[1] = wrapper::vmla(out.val[1], vmid_s32.val[1], m1.val[0]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_1(vmid_s32.val[1], vmid_s32.val[2]), m1.val[1]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_2(vmid_s32.val[1], vmid_s32.val[2]), m1.val[2]); - - out.val[1] = wrapper::vmla(out.val[1], vlow_s32.val[1], m2.val[0]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_1(vlow_s32.val[1], vlow_s32.val[2]), m2.val[1]); - out.val[1] = wrapper::vmla(out.val[1], wrapper::vext_2(vlow_s32.val[1], vlow_s32.val[2]), m2.val[2]); - - if(stridex == 1) - { - accumulate ? accumulate_results<1>(out_ptr, out) : store_results<1>(out_ptr, out); - } - else if(stridex == 2) - { - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[0], 2), out.val[0], 1); - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[1], 0), out.val[0], 2); - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[1], 2), out.val[0], 3); - - accumulate ? accumulate_results<2>(out_ptr, out) : store_results<2>(out_ptr, out); - } - else if(stridex == 3) - { - out.val[0] = wrapper::vsetlane(wrapper::vgetlane(out.val[0], 3), out.val[0], 1); - accumulate ? accumulate_results<3>(out_ptr, out) : store_results<3>(out_ptr, out); - } -} - -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -/** Loads a 3x3 matrix as a row (float16_t). - * - * @param[in] ptr Pointer to a float 3x3 matrix. - * - * @return The loaded matrix. - */ -inline float16x8x3_t load_matrix_row(const float16_t *ptr, int weights_offset = 0) -{ - ARM_COMPUTE_UNUSED(weights_offset); - /* ptr is a pointer to a row in a 3x3 matrix, the function returns 3 vectors holding exactly the same value in all lanes: - r.val[0] contains the first element, r.val[1] the second element and r.val[2] the third element (in all lanes) */ - const float16x8x3_t r = - { - { - vld1q_dup_f16(ptr), - vld1q_dup_f16(1 + ptr), - vld1q_dup_f16(2 + ptr) - } - }; - return r; -} - -/** Perform a 3x3 convolution for 8 consecutive elements on float16 when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] input_offset (Optional)Input quantization offset. - * - */ -inline float16x8_t single_convolve_3x3_dilation(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, - const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, - const size_t dilation_x, int input_offset = 0) -{ - ARM_COMPUTE_UNUSED(input_offset); - const float16x8x3_t vtop = - { - { - vld1q_f16(in_top), - vld1q_f16(in_top + dilation_x), - vld1q_f16(in_top + 2 * dilation_x) - } - }; - const float16x8x3_t vmid = - { - { - vld1q_f16(in_mid), - vld1q_f16(in_mid + dilation_x), - vld1q_f16(in_mid + 2 * dilation_x) - } - }; - const float16x8x3_t vlow = - { - { - vld1q_f16(in_low), - vld1q_f16(in_low + dilation_x), - vld1q_f16(in_low + 2 * dilation_x) - } - }; - float16x8_t out = vmulq_f16(vtop.val[0], m0.val[0]); - out = vaddq_f16(out, vmulq_f16(vtop.val[1], m0.val[1])); - out = vaddq_f16(out, vmulq_f16(vtop.val[2], m0.val[2])); - - out = vaddq_f16(out, vmulq_f16(vmid.val[0], m1.val[0])); - out = vaddq_f16(out, vmulq_f16(vmid.val[1], m1.val[1])); - out = vaddq_f16(out, vmulq_f16(vmid.val[2], m1.val[2])); - - out = vaddq_f16(out, vmulq_f16(vlow.val[0], m2.val[0])); - out = vaddq_f16(out, vmulq_f16(vlow.val[1], m2.val[1])); - out = vaddq_f16(out, vmulq_f16(vlow.val[2], m2.val[2])); - - return out; -} - -/** Perform a 3x3 convolution for 16 consecutive elements on float16 when dilation.x() or dilation.y() is not 1. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] dilation_x Dilation, in elements across x. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset (Optional) Input quantization offset. - * - */ -inline float16x8x2_t convolve_3x3_dilation(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, - const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, - const size_t dilation_x, unsigned int stridex, int input_offset = 0) -{ - float16x8x2_t out = - { - { - single_convolve_3x3_dilation(in_top, in_mid, in_low, m0, m1, m2, dilation_x, input_offset), - single_convolve_3x3_dilation(in_top + 8, in_mid + 8, in_low + 8, m0, m1, m2, dilation_x, input_offset) - } - }; - - if(stridex == 2) - { - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 2), out.val[0], 1); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 4), out.val[0], 2); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 6), out.val[0], 3); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 0), out.val[0], 4); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 2), out.val[0], 5); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 4), out.val[0], 6); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 6), out.val[0], 7); - } - else if(stridex == 3) - { - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 3), out.val[0], 1); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 6), out.val[0], 2); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 1), out.val[0], 3); - } - - return out; -} - -/** Perform a convolve3x3 on float16. - * - * @param[in] in_top Pointer to the first row of the input. - * @param[in] in_mid Pointer to the second row of the input. - * @param[in] in_low Pointer to the third row of the input. - * @param[out] out_ptr Pointer to the output. - * @param[in] m0 First row of the filter. - * @param[in] m1 Second row of the filter. - * @param[in] m2 Third row of the filter. - * @param[in] stridex Stride value in elements across x. - * @param[in] input_offset (Optional) Input quantization offset. - * - */ -template -inline void convolve_3x3(const float16_t *in_top, const float16_t *in_mid, const float16_t *in_low, float16_t *out_ptr, - const float16x8x3_t &m0, const float16x8x3_t &m1, const float16x8x3_t &m2, - unsigned int stridex, int input_offset = 0) -{ - ARM_COMPUTE_UNUSED(input_offset); - - float16x8x2_t out = - { - { - vdupq_n_f16(0), - vdupq_n_f16(0) - } - }; - if(stridex == 2) - { - const float16x8x2_t vtop = vld2q_f16(in_top); - const float16x8x2_t vmid = vld2q_f16(in_mid); - const float16x8x2_t vlow = vld2q_f16(in_low); - const float16x8_t vtop_end = vld1q_f16(in_top + 16); - const float16x8_t vmid_end = vld1q_f16(in_mid + 16); - const float16x8_t vlow_end = vld1q_f16(in_low + 16); - - out.val[0] = vmulq_f16(vtop.val[0], m0.val[0]); - - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vtop.val[1], m0.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vtop.val[0], vtop_end, 1), m0.val[2])); - - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vmid.val[0], m1.val[0])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vmid.val[1], m1.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vmid.val[0], vmid_end, 1), m1.val[2])); - - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vlow.val[0], m2.val[0])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vlow.val[1], m2.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vlow.val[0], vlow_end, 1), m2.val[2])); - - accumulate ? accumulate_results<2>(out_ptr, out) : store_results<2>(out_ptr, out); - } - else - { - const float16x8x3_t vtop = - { - { - vld1q_f16(in_top), - vld1q_f16(in_top + 8), - vld1q_f16(in_top + 16) - } - }; - const float16x8x3_t vmid = - { - { - vld1q_f16(in_mid), - vld1q_f16(in_mid + 8), - vld1q_f16(in_mid + 16) - } - }; - const float16x8x3_t vlow = - { - { - vld1q_f16(in_low), - vld1q_f16(in_low + 8), - vld1q_f16(in_low + 16) - } - }; - out.val[0] = vmulq_f16(vtop.val[0], m0.val[0]); - out.val[1] = vmulq_f16(vtop.val[1], m0.val[0]); - - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vtop.val[0], vtop.val[1], 1), m0.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vtop.val[0], vtop.val[1], 2), m0.val[2])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vmid.val[0], m1.val[0])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vmid.val[0], vmid.val[1], 1), m1.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vmid.val[0], vmid.val[1], 2), m1.val[2])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vlow.val[0], m2.val[0])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vlow.val[0], vlow.val[1], 1), m2.val[1])); - out.val[0] = vaddq_f16(out.val[0], vmulq_f16(vextq_f16(vlow.val[0], vlow.val[1], 2), m2.val[2])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vtop.val[1], vtop.val[2], 1), m0.val[1])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vtop.val[1], vtop.val[2], 2), m0.val[2])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vmid.val[1], m1.val[0])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vmid.val[1], vmid.val[2], 1), m1.val[1])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vmid.val[1], vmid.val[2], 2), m1.val[2])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vlow.val[1], m2.val[0])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vlow.val[1], vlow.val[2], 1), m2.val[1])); - out.val[1] = vaddq_f16(out.val[1], vmulq_f16(vextq_f16(vlow.val[1], vlow.val[2], 2), m2.val[2])); - - if(stridex == 3) - { - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 3), out.val[0], 1); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[0], 6), out.val[0], 2); - out.val[0] = vsetq_lane_f16(vgetq_lane_f16(out.val[1], 1), out.val[0], 3); - - accumulate ? accumulate_results<3>(out_ptr, out) : store_results<3>(out_ptr, out); - } - else - { - accumulate ? accumulate_results<1>(out_ptr, out) : store_results<1>(out_ptr, out); - } - } -} -#endif /** __ARM_FEATURE_FP16_VECTOR_ARITHMETIC **/ - -/** Get the number of elements processed on 3x3 convolution. - * - * @param[in] num_elems_written_per_iteration Number of elements written per iteration on 3x3 convolution. - * @param[in] stridex Stride value in elements across x. - * - * @return The number of elements processed. - */ -inline int get_input_num_elems_processed(unsigned int num_elems_written_per_iteration, unsigned int stridex) -{ - switch(stridex) - { - case 1: - return num_elems_written_per_iteration; - case 2: - return num_elems_written_per_iteration << 1; - case 3: - return num_elems_written_per_iteration * 3; - default: - ARM_COMPUTE_ERROR("stridex not supported"); - return 0; - } -} -} -} // namespace arm_compute -#endif /* ARM_COMPUTE_NEDIRECTCONVOLUTIONDETAIL_H */ -- cgit v1.2.1