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488 lines
14 KiB
C
488 lines
14 KiB
C
/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_svm_sigmoid_predict_f32.c
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* Description: SVM Sigmoid Classifier
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*
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* $Date: 23 April 2021
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* $Revision: V1.9.0
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*
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* Target Processor: Cortex-M and Cortex-A cores
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* -------------------------------------------------------------------- */
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/*
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* Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
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*
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* SPDX-License-Identifier: Apache-2.0
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*
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* Licensed under the Apache License, Version 2.0 (the License); you may
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* not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an AS IS BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "dsp/svm_functions.h"
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#include <limits.h>
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#include <math.h>
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/**
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* @addtogroup sigmoidsvm
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* @{
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*/
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/**
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* @brief SVM sigmoid prediction
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* @param[in] S Pointer to an instance of the rbf SVM structure.
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* @param[in] in Pointer to input vector
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* @param[out] pResult Decision value
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* @return none.
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*
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*/
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#if defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE)
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#include "arm_helium_utils.h"
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#include "arm_vec_math.h"
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void arm_svm_sigmoid_predict_f32(
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const arm_svm_sigmoid_instance_f32 *S,
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const float32_t * in,
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int32_t * pResult)
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{
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/* inlined Matrix x Vector function interleaved with dot prod */
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uint32_t numRows = S->nbOfSupportVectors;
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uint32_t numCols = S->vectorDimension;
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const float32_t *pSupport = S->supportVectors;
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const float32_t *pSrcA = pSupport;
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const float32_t *pInA0;
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const float32_t *pInA1;
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uint32_t row;
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uint32_t blkCnt; /* loop counters */
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const float32_t *pDualCoef = S->dualCoefficients;
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float32_t sum = S->intercept;
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f32x4_t vSum = vdupq_n_f32(0.0f);
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row = numRows;
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/*
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* compute 4 rows in parrallel
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*/
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while (row >= 4) {
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const float32_t *pInA2, *pInA3;
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float32_t const *pSrcA0Vec, *pSrcA1Vec, *pSrcA2Vec, *pSrcA3Vec, *pInVec;
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f32x4_t vecIn, acc0, acc1, acc2, acc3;
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float32_t const *pSrcVecPtr = in;
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/*
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* Initialize the pointers to 4 consecutive MatrixA rows
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*/
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pInA0 = pSrcA;
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pInA1 = pInA0 + numCols;
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pInA2 = pInA1 + numCols;
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pInA3 = pInA2 + numCols;
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/*
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* Initialize the vector pointer
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*/
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pInVec = pSrcVecPtr;
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/*
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* reset accumulators
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*/
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acc0 = vdupq_n_f32(0.0f);
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acc1 = vdupq_n_f32(0.0f);
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acc2 = vdupq_n_f32(0.0f);
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acc3 = vdupq_n_f32(0.0f);
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pSrcA0Vec = pInA0;
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pSrcA1Vec = pInA1;
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pSrcA2Vec = pInA2;
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pSrcA3Vec = pInA3;
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blkCnt = numCols >> 2;
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while (blkCnt > 0U) {
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f32x4_t vecA;
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vecIn = vld1q(pInVec);
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pInVec += 4;
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vecA = vld1q(pSrcA0Vec);
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pSrcA0Vec += 4;
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acc0 = vfmaq(acc0, vecIn, vecA);
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vecA = vld1q(pSrcA1Vec);
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pSrcA1Vec += 4;
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acc1 = vfmaq(acc1, vecIn, vecA);
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vecA = vld1q(pSrcA2Vec);
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pSrcA2Vec += 4;
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acc2 = vfmaq(acc2, vecIn, vecA);
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vecA = vld1q(pSrcA3Vec);
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pSrcA3Vec += 4;
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acc3 = vfmaq(acc3, vecIn, vecA);
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blkCnt--;
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}
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/*
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* tail
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* (will be merged thru tail predication)
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*/
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blkCnt = numCols & 3;
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if (blkCnt > 0U) {
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mve_pred16_t p0 = vctp32q(blkCnt);
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f32x4_t vecA;
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vecIn = vldrwq_z_f32(pInVec, p0);
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vecA = vldrwq_z_f32(pSrcA0Vec, p0);
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acc0 = vfmaq(acc0, vecIn, vecA);
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vecA = vldrwq_z_f32(pSrcA1Vec, p0);
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acc1 = vfmaq(acc1, vecIn, vecA);
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vecA = vldrwq_z_f32(pSrcA2Vec, p0);
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acc2 = vfmaq(acc2, vecIn, vecA);
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vecA = vldrwq_z_f32(pSrcA3Vec, p0);
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acc3 = vfmaq(acc3, vecIn, vecA);
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}
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/*
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* Sum the partial parts
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*/
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f32x4_t vtmp = vuninitializedq_f32();
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc0), vtmp, 0);
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc1), vtmp, 1);
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc2), vtmp, 2);
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc3), vtmp, 3);
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vSum =
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vfmaq_f32(vSum, vld1q(pDualCoef),
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vtanhq_f32(vaddq_n_f32(vmulq_n_f32(vtmp, S->gamma), S->coef0)));
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pDualCoef += 4;
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pSrcA += numCols * 4;
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/*
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* Decrement the row loop counter
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*/
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row -= 4;
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}
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/*
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* compute 2 rows in parrallel
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*/
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if (row >= 2) {
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float32_t const *pSrcA0Vec, *pSrcA1Vec, *pInVec;
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f32x4_t vecIn, acc0, acc1;
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float32_t const *pSrcVecPtr = in;
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/*
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* Initialize the pointers to 2 consecutive MatrixA rows
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*/
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pInA0 = pSrcA;
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pInA1 = pInA0 + numCols;
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/*
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* Initialize the vector pointer
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*/
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pInVec = pSrcVecPtr;
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/*
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* reset accumulators
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*/
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acc0 = vdupq_n_f32(0.0f);
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acc1 = vdupq_n_f32(0.0f);
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pSrcA0Vec = pInA0;
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pSrcA1Vec = pInA1;
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blkCnt = numCols >> 2;
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while (blkCnt > 0U) {
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f32x4_t vecA;
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vecIn = vld1q(pInVec);
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pInVec += 4;
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vecA = vld1q(pSrcA0Vec);
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pSrcA0Vec += 4;
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acc0 = vfmaq(acc0, vecIn, vecA);
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vecA = vld1q(pSrcA1Vec);
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pSrcA1Vec += 4;
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acc1 = vfmaq(acc1, vecIn, vecA);
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blkCnt--;
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}
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/*
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* tail
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* (will be merged thru tail predication)
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*/
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blkCnt = numCols & 3;
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if (blkCnt > 0U) {
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mve_pred16_t p0 = vctp32q(blkCnt);
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f32x4_t vecA;
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vecIn = vldrwq_z_f32(pInVec, p0);
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vecA = vldrwq_z_f32(pSrcA0Vec, p0);
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acc0 = vfmaq(acc0, vecIn, vecA);
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vecA = vldrwq_z_f32(pSrcA1Vec, p0);
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acc1 = vfmaq(acc1, vecIn, vecA);
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}
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/*
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* Sum the partial parts
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*/
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f32x4_t vtmp = vuninitializedq_f32();
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc0), vtmp, 0);
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc1), vtmp, 1);
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vSum =
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vfmaq_m_f32(vSum, vld1q(pDualCoef),
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vtanhq_f32(vaddq_n_f32(vmulq_n_f32(vtmp, S->gamma), S->coef0)),
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vctp32q(2));
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pSrcA += numCols * 2;
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row -= 2;
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}
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if (row >= 1) {
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f32x4_t vecIn, acc0;
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float32_t const *pSrcA0Vec, *pInVec;
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float32_t const *pSrcVecPtr = in;
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/*
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* Initialize the pointers to last MatrixA row
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*/
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pInA0 = pSrcA;
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/*
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* Initialize the vector pointer
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*/
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pInVec = pSrcVecPtr;
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/*
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* reset accumulators
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*/
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acc0 = vdupq_n_f32(0.0f);
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pSrcA0Vec = pInA0;
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blkCnt = numCols >> 2;
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while (blkCnt > 0U) {
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f32x4_t vecA;
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vecIn = vld1q(pInVec);
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pInVec += 4;
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vecA = vld1q(pSrcA0Vec);
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pSrcA0Vec += 4;
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acc0 = vfmaq(acc0, vecIn, vecA);
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blkCnt--;
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}
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/*
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* tail
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* (will be merged thru tail predication)
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*/
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blkCnt = numCols & 3;
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if (blkCnt > 0U) {
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mve_pred16_t p0 = vctp32q(blkCnt);
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f32x4_t vecA;
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vecIn = vldrwq_z_f32(pInVec, p0);
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vecA = vldrwq_z_f32(pSrcA0Vec, p0);
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acc0 = vfmaq(acc0, vecIn, vecA);
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}
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/*
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* Sum the partial parts
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*/
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f32x4_t vtmp = vuninitializedq_f32();
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vtmp = vsetq_lane(vecAddAcrossF32Mve(acc0), vtmp, 0);
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vSum =
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vfmaq_m_f32(vSum, vld1q(pDualCoef),
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vtanhq_f32(vaddq_n_f32(vmulq_n_f32(vtmp, S->gamma), S->coef0)),
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vctp32q(1));
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}
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sum += vecAddAcrossF32Mve(vSum);
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*pResult = S->classes[STEP(sum)];
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}
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#else
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#if defined(ARM_MATH_NEON)
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#include "NEMath.h"
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void arm_svm_sigmoid_predict_f32(
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const arm_svm_sigmoid_instance_f32 *S,
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const float32_t * in,
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int32_t * pResult)
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{
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float32_t sum = S->intercept;
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float32_t dot;
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float32x4_t dotV;
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float32x4_t accuma,accumb,accumc,accumd,accum;
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float32x2_t accum2;
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float32x4_t vec1;
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float32x4_t coef0 = vdupq_n_f32(S->coef0);
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float32x4_t vec2,vec2a,vec2b,vec2c,vec2d;
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uint32_t blkCnt;
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uint32_t vectorBlkCnt;
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const float32_t *pIn = in;
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const float32_t *pSupport = S->supportVectors;
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const float32_t *pSupporta = S->supportVectors;
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const float32_t *pSupportb;
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const float32_t *pSupportc;
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const float32_t *pSupportd;
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pSupportb = pSupporta + S->vectorDimension;
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pSupportc = pSupportb + S->vectorDimension;
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pSupportd = pSupportc + S->vectorDimension;
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const float32_t *pDualCoefs = S->dualCoefficients;
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vectorBlkCnt = S->nbOfSupportVectors >> 2;
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while (vectorBlkCnt > 0U)
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{
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accuma = vdupq_n_f32(0);
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accumb = vdupq_n_f32(0);
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accumc = vdupq_n_f32(0);
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accumd = vdupq_n_f32(0);
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pIn = in;
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blkCnt = S->vectorDimension >> 2;
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while (blkCnt > 0U)
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{
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vec1 = vld1q_f32(pIn);
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vec2a = vld1q_f32(pSupporta);
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vec2b = vld1q_f32(pSupportb);
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vec2c = vld1q_f32(pSupportc);
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vec2d = vld1q_f32(pSupportd);
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pIn += 4;
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pSupporta += 4;
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pSupportb += 4;
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pSupportc += 4;
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pSupportd += 4;
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accuma = vmlaq_f32(accuma, vec1,vec2a);
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accumb = vmlaq_f32(accumb, vec1,vec2b);
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accumc = vmlaq_f32(accumc, vec1,vec2c);
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accumd = vmlaq_f32(accumd, vec1,vec2d);
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blkCnt -- ;
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}
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accum2 = vpadd_f32(vget_low_f32(accuma),vget_high_f32(accuma));
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dotV = vsetq_lane_f32(vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1),dotV,0);
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accum2 = vpadd_f32(vget_low_f32(accumb),vget_high_f32(accumb));
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dotV = vsetq_lane_f32(vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1),dotV,1);
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accum2 = vpadd_f32(vget_low_f32(accumc),vget_high_f32(accumc));
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dotV = vsetq_lane_f32(vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1),dotV,2);
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accum2 = vpadd_f32(vget_low_f32(accumd),vget_high_f32(accumd));
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dotV = vsetq_lane_f32(vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1),dotV,3);
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blkCnt = S->vectorDimension & 3;
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while (blkCnt > 0U)
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{
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dotV = vsetq_lane_f32(vgetq_lane_f32(dotV,0) + *pIn * *pSupporta++, dotV,0);
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dotV = vsetq_lane_f32(vgetq_lane_f32(dotV,1) + *pIn * *pSupportb++, dotV,1);
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dotV = vsetq_lane_f32(vgetq_lane_f32(dotV,2) + *pIn * *pSupportc++, dotV,2);
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dotV = vsetq_lane_f32(vgetq_lane_f32(dotV,3) + *pIn * *pSupportd++, dotV,3);
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pIn++;
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blkCnt -- ;
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}
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vec1 = vld1q_f32(pDualCoefs);
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pDualCoefs += 4;
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// To vectorize later
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dotV = vmulq_n_f32(dotV, S->gamma);
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dotV = vaddq_f32(dotV, coef0);
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dotV = vtanhq_f32(dotV);
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accum = vmulq_f32(vec1,dotV);
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accum2 = vpadd_f32(vget_low_f32(accum),vget_high_f32(accum));
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sum += vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1);
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pSupporta += 3*S->vectorDimension;
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pSupportb += 3*S->vectorDimension;
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pSupportc += 3*S->vectorDimension;
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pSupportd += 3*S->vectorDimension;
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vectorBlkCnt -- ;
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}
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pSupport = pSupporta;
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vectorBlkCnt = S->nbOfSupportVectors & 3;
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while (vectorBlkCnt > 0U)
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{
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accum = vdupq_n_f32(0);
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dot = 0.0f;
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pIn = in;
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blkCnt = S->vectorDimension >> 2;
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while (blkCnt > 0U)
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{
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vec1 = vld1q_f32(pIn);
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vec2 = vld1q_f32(pSupport);
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pIn += 4;
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pSupport += 4;
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accum = vmlaq_f32(accum, vec1,vec2);
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blkCnt -- ;
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}
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accum2 = vpadd_f32(vget_low_f32(accum),vget_high_f32(accum));
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dot = vget_lane_f32(accum2, 0) + vget_lane_f32(accum2, 1);
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blkCnt = S->vectorDimension & 3;
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while (blkCnt > 0U)
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{
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dot = dot + *pIn++ * *pSupport++;
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blkCnt -- ;
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}
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sum += *pDualCoefs++ * tanhf(S->gamma * dot + S->coef0);
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vectorBlkCnt -- ;
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}
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*pResult=S->classes[STEP(sum)];
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}
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#else
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void arm_svm_sigmoid_predict_f32(
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const arm_svm_sigmoid_instance_f32 *S,
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const float32_t * in,
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int32_t * pResult)
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{
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float32_t sum=S->intercept;
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float32_t dot=0;
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uint32_t i,j;
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const float32_t *pSupport = S->supportVectors;
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for(i=0; i < S->nbOfSupportVectors; i++)
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{
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dot=0;
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for(j=0; j < S->vectorDimension; j++)
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{
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dot = dot + in[j]* *pSupport++;
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|
}
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|
sum += S->dualCoefficients[i] * tanhf(S->gamma * dot + S->coef0);
|
|
}
|
|
*pResult=S->classes[STEP(sum)];
|
|
}
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|
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#endif
|
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#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
|
|
|
|
/**
|
|
* @} end of sigmoidsvm group
|
|
*/
|