| /* |
| * 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 <arm_neon.h> |
| |
| 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<T, uint8_t>::value || std::is_same<T, int8_t>::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; |
| } |
| |
| /** 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[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. |
| * |
| */ |
| float32x4x2_t convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, |
| const float32x4x3_t &m0, const float32x4x3_t &m1, const float32x4x3_t &m2, |
| unsigned int stridex, int input_offset = 0); |
| |
| inline float32x4x2_t convolve_3x3(const float *in_top, const float *in_mid, const float *in_low, |
| 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]); |
| } |
| 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); |
| } |
| } |
| |
| 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] input_offset Input quantization offset. |
| * |
| */ |
| template < typename T, REQUIRES_TA(std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::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<std::is_same<T, uint8_t>::value, uint8x8x3_t, int8x8x3_t>::type; |
| using OutputTagType = typename wrapper::traits::neon_bitvector_tag_t<int32_t, wrapper::traits::BitWidth::W128>; |
| |
| 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<T, uint8_t>::value || std::is_same<T, int8_t>::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[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 < typename T, REQUIRES_TA(std::is_same<T, uint8_t>::value || std::is_same<T, int8_t>::value) > |
| int32x4x2_t convolve_3x3(const T *in_top, const T *in_mid, const T *in_low, |
| 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<std::is_same<T, uint8_t>::value, uint8x8x2_t, int8x8x2_t>::type; |
| using OutputTagType = typename wrapper::traits::neon_bitvector_tag_t<int32_t, wrapper::traits::BitWidth::W128>; |
| |
| 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<int32_t>(0), OutputTagType{}), |
| wrapper::vdup_n(static_cast<int32_t>(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 == 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; |
| } |
| |
| /** 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 <unsigned int stridex> |
| 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 <unsigned int stridex> |
| 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])); |
| } |
| |
| #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[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. |
| * |
| */ |
| inline float16x8x2_t convolve_3x3(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, |
| 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])); |
| } |
| 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); |
| } |
| } |
| |
| return out; |
| } |
| |
| /** 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 <unsigned int stridex> |
| 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])); |
| } |
| #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 */ |