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 insertions(+) create mode 100644 src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h (limited to 'src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h') diff --git a/src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h b/src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h new file mode 100644 index 0000000000..d7ee70a1cd --- /dev/null +++ b/src/core/NEON/kernels/detail/NEDirectConvolutionDetail.h @@ -0,0 +1,965 @@ +/* + * 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/utils/misc/Requires.h" +#include "src/core/NEON/NEFixedPoint.h" +#include "src/core/NEON/wrapper/wrapper.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