Hey-Edge / edge-impulse-sdk /CMSIS /DSP /Source /SVMFunctions /arm_svm_linear_predict_f16.c

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#include "edge-impulse-sdk/dsp/config.hpp"
#if EIDSP_LOAD_CMSIS_DSP_SOURCES
/* ----------------------------------------------------------------------
 * Project:      CMSIS DSP Library
 * Title:        arm_svm_linear_predict_f16.c
 * Description:  SVM Linear Classifier
 *
 * $Date:        23 April 2021
 * $Revision:    V1.9.0
 *
 * Target Processor: Cortex-M and Cortex-A cores
 * -------------------------------------------------------------------- */
/*
 * Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
 *
 * SPDX-License-Identifier: Apache-2.0
 *
 * Licensed under the Apache License, Version 2.0 (the License); you may
 * not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 * www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an AS IS BASIS, WITHOUT
 * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

#include "edge-impulse-sdk/CMSIS/DSP/Include/dsp/svm_functions_f16.h"

#if defined(ARM_FLOAT16_SUPPORTED)

#include <limits.h>
#include <math.h>


/**
 * @addtogroup linearsvm
 * @{
 */


/**
 * @brief SVM linear prediction
 * @param[in]    S          Pointer to an instance of the linear SVM structure.
 * @param[in]    in         Pointer to input vector
 * @param[out]   pResult    Decision value
 * @return none.
 *
 */
#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)

#include "edge-impulse-sdk/CMSIS/DSP/Include/arm_helium_utils.h"

void arm_svm_linear_predict_f16(
    const arm_svm_linear_instance_f16 *S,
    const float16_t * in,
    int32_t * pResult)
{
        /* inlined Matrix x Vector function interleaved with dot prod */
    uint32_t        numRows = S->nbOfSupportVectors;
    uint32_t        numCols = S->vectorDimension;
    const float16_t *pSupport = S->supportVectors;
    const float16_t *pSrcA = pSupport;
    const float16_t *pInA0;
    const float16_t *pInA1;
    uint32_t         row;
    uint32_t         blkCnt;     /* loop counters */
    const float16_t *pDualCoef = S->dualCoefficients;
    _Float16       sum = S->intercept;
    row = numRows;

    /*
     * compute 4 rows in parrallel
     */
    while (row >= 4) 
    {
        const float16_t *pInA2, *pInA3;
        float16_t const *pSrcA0Vec, *pSrcA1Vec, *pSrcA2Vec, *pSrcA3Vec, *pInVec;
        f16x8_t         vecIn, acc0, acc1, acc2, acc3;
        float16_t const *pSrcVecPtr = in;

        /*
         * Initialize the pointers to 4 consecutive MatrixA rows
         */
        pInA0 = pSrcA;
        pInA1 = pInA0 + numCols;
        pInA2 = pInA1 + numCols;
        pInA3 = pInA2 + numCols;
        /*
         * Initialize the vector pointer
         */
        pInVec = pSrcVecPtr;
        /*
         * reset accumulators
         */
        acc0 = vdupq_n_f16(0.0f);
        acc1 = vdupq_n_f16(0.0f);
        acc2 = vdupq_n_f16(0.0f);
        acc3 = vdupq_n_f16(0.0f);

        pSrcA0Vec = pInA0;
        pSrcA1Vec = pInA1;
        pSrcA2Vec = pInA2;
        pSrcA3Vec = pInA3;

        blkCnt = numCols >> 3;
        while (blkCnt > 0U) {
            f16x8_t         vecA;

            vecIn = vld1q(pInVec);
            pInVec += 8;
            vecA = vld1q(pSrcA0Vec);
            pSrcA0Vec += 8;
            acc0 = vfmaq(acc0, vecIn, vecA);
            vecA = vld1q(pSrcA1Vec);
            pSrcA1Vec += 8;
            acc1 = vfmaq(acc1, vecIn, vecA);
            vecA = vld1q(pSrcA2Vec);
            pSrcA2Vec += 8;
            acc2 = vfmaq(acc2, vecIn, vecA);
            vecA = vld1q(pSrcA3Vec);
            pSrcA3Vec += 8;
            acc3 = vfmaq(acc3, vecIn, vecA);

            blkCnt--;
        }
        /*
         * tail
         * (will be merged thru tail predication)
         */
        blkCnt = numCols & 7;
        if (blkCnt > 0U) {
            mve_pred16_t    p0 = vctp16q(blkCnt);
            f16x8_t         vecA;

            vecIn = vldrhq_z_f16(pInVec, p0);
            vecA = vldrhq_z_f16(pSrcA0Vec, p0);
            acc0 = vfmaq(acc0, vecIn, vecA);
            vecA = vldrhq_z_f16(pSrcA1Vec, p0);
            acc1 = vfmaq(acc1, vecIn, vecA);
            vecA = vldrhq_z_f16(pSrcA2Vec, p0);
            acc2 = vfmaq(acc2, vecIn, vecA);
            vecA = vldrhq_z_f16(pSrcA3Vec, p0);
            acc3 = vfmaq(acc3, vecIn, vecA);
        }
        /*
         * Sum the partial parts
         */
        acc0 = vmulq_n_f16(acc0,*pDualCoef++);
        acc0 = vfmaq_n_f16(acc0,acc1,*pDualCoef++);
        acc0 = vfmaq_n_f16(acc0,acc2,*pDualCoef++);
        acc0 = vfmaq_n_f16(acc0,acc3,*pDualCoef++);

        sum += (_Float16)vecAddAcrossF16Mve(acc0);

        pSrcA += numCols * 4;
        /*
         * Decrement the row loop counter
         */
        row -= 4;
    }

    /*
     * compute 2 rows in parallel
     */
    if (row >= 2) {
        float16_t const *pSrcA0Vec, *pSrcA1Vec, *pInVec;
        f16x8_t         vecIn, acc0, acc1;
        float16_t const *pSrcVecPtr = in;

        /*
         * Initialize the pointers to 2 consecutive MatrixA rows
         */
        pInA0 = pSrcA;
        pInA1 = pInA0 + numCols;
        /*
         * Initialize the vector pointer
         */
        pInVec = pSrcVecPtr;
        /*
         * reset accumulators
         */
        acc0 = vdupq_n_f16(0.0f);
        acc1 = vdupq_n_f16(0.0f);
        pSrcA0Vec = pInA0;
        pSrcA1Vec = pInA1;

        blkCnt = numCols >> 3;
        while (blkCnt > 0U) {
            f16x8_t         vecA;

            vecIn = vld1q(pInVec);
            pInVec += 8;
            vecA = vld1q(pSrcA0Vec);
            pSrcA0Vec += 8;
            acc0 = vfmaq(acc0, vecIn, vecA);
            vecA = vld1q(pSrcA1Vec);
            pSrcA1Vec += 8;
            acc1 = vfmaq(acc1, vecIn, vecA);

            blkCnt--;
        }
        /*
         * tail
         * (will be merged thru tail predication)
         */
        blkCnt = numCols & 7;
        if (blkCnt > 0U) {
            mve_pred16_t    p0 = vctp16q(blkCnt);
            f16x8_t         vecA;

            vecIn = vldrhq_z_f16(pInVec, p0);
            vecA = vldrhq_z_f16(pSrcA0Vec, p0);
            acc0 = vfmaq(acc0, vecIn, vecA);
            vecA = vldrhq_z_f16(pSrcA1Vec, p0);
            acc1 = vfmaq(acc1, vecIn, vecA);
        }
        /*
         * Sum the partial parts
         */
        acc0 = vmulq_n_f16(acc0,*pDualCoef++);
        acc0 = vfmaq_n_f16(acc0,acc1,*pDualCoef++);

        sum += (_Float16)vecAddAcrossF16Mve(acc0);

        pSrcA += numCols * 2;
        row -= 2;
    }

    if (row >= 1) {
        f16x8_t         vecIn, acc0;
        float16_t const *pSrcA0Vec, *pInVec;
        float16_t const *pSrcVecPtr = in;
        /*
         * Initialize the pointers to last MatrixA row
         */
        pInA0 = pSrcA;
        /*
         * Initialize the vector pointer
         */
        pInVec = pSrcVecPtr;
        /*
         * reset accumulators
         */
        acc0 = vdupq_n_f16(0.0f);

        pSrcA0Vec = pInA0;

        blkCnt = numCols >> 3;
        while (blkCnt > 0U) {
            f16x8_t         vecA;

            vecIn = vld1q(pInVec);
            pInVec += 8;
            vecA = vld1q(pSrcA0Vec);
            pSrcA0Vec += 8;
            acc0 = vfmaq(acc0, vecIn, vecA);

            blkCnt--;
        }
        /*
         * tail
         * (will be merged thru tail predication)
         */
        blkCnt = numCols & 7;
        if (blkCnt > 0U) {
            mve_pred16_t    p0 = vctp16q(blkCnt);
            f16x8_t         vecA;

            vecIn = vldrhq_z_f16(pInVec, p0);
            vecA = vldrhq_z_f16(pSrcA0Vec, p0);
            acc0 = vfmaq(acc0, vecIn, vecA);
        }
        /*
         * Sum the partial parts
         */
        sum += (_Float16)*pDualCoef++ * (_Float16)vecAddAcrossF16Mve(acc0);

    }

    *pResult = S->classes[STEP(sum)];
}

#else
void arm_svm_linear_predict_f16(
    const arm_svm_linear_instance_f16 *S,
    const float16_t * in,
    int32_t * pResult)
{
    _Float16 sum=S->intercept;
    _Float16 dot=0;
    uint32_t i,j;
    const float16_t *pSupport = S->supportVectors;

    for(i=0; i < S->nbOfSupportVectors; i++)
    {
        dot=0;
        for(j=0; j < S->vectorDimension; j++)
        {
            dot = (_Float16)dot + (_Float16)in[j]* (_Float16)*pSupport++;
        }
        sum += (_Float16)S->dualCoefficients[i] * (_Float16)dot;
    }
    *pResult=S->classes[STEP(sum)];
}
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */

/**
 * @} end of linearsvm group
 */

#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */ 


#endif // EIDSP_LOAD_CMSIS_DSP_SOURCES

	#include "edge-impulse-sdk/dsp/config.hpp"
	#if EIDSP_LOAD_CMSIS_DSP_SOURCES
	/* ----------------------------------------------------------------------
	* Project: CMSIS DSP Library
	* Title: arm_svm_linear_predict_f16.c
	* Description: SVM Linear Classifier
	*
	* $Date: 23 April 2021
	* $Revision: V1.9.0
	*
	* Target Processor: Cortex-M and Cortex-A cores
	* -------------------------------------------------------------------- */
	/*
	* Copyright (C) 2010-2021 ARM Limited or its affiliates. All rights reserved.
	*
	* SPDX-License-Identifier: Apache-2.0
	*
	* Licensed under the Apache License, Version 2.0 (the License); you may
	* not use this file except in compliance with the License.
	* You may obtain a copy of the License at
	*
	* www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an AS IS BASIS, WITHOUT
	* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	* See the License for the specific language governing permissions and
	* limitations under the License.
	*/

	#include "edge-impulse-sdk/CMSIS/DSP/Include/dsp/svm_functions_f16.h"

	#if defined(ARM_FLOAT16_SUPPORTED)

	#include <limits.h>
	#include <math.h>


	/**
	* @addtogroup linearsvm
	* @{
	*/


	/**
	* @brief SVM linear prediction
	* @param[in] S Pointer to an instance of the linear SVM structure.
	* @param[in] in Pointer to input vector
	* @param[out] pResult Decision value
	* @return none.
	*
	*/
	#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)

	#include "edge-impulse-sdk/CMSIS/DSP/Include/arm_helium_utils.h"

	void arm_svm_linear_predict_f16(
	const arm_svm_linear_instance_f16 *S,
	const float16_t * in,
	int32_t * pResult)
	{
	/* inlined Matrix x Vector function interleaved with dot prod */
	uint32_t numRows = S->nbOfSupportVectors;
	uint32_t numCols = S->vectorDimension;
	const float16_t *pSupport = S->supportVectors;
	const float16_t *pSrcA = pSupport;
	const float16_t *pInA0;
	const float16_t *pInA1;
	uint32_t row;
	uint32_t blkCnt; /* loop counters */
	const float16_t *pDualCoef = S->dualCoefficients;
	_Float16 sum = S->intercept;
	row = numRows;

	/*
	* compute 4 rows in parrallel
	*/
	while (row >= 4)
	{
	const float16_t pInA2, pInA3;
	float16_t const pSrcA0Vec, pSrcA1Vec, pSrcA2Vec, pSrcA3Vec, *pInVec;
	f16x8_t vecIn, acc0, acc1, acc2, acc3;
	float16_t const *pSrcVecPtr = in;

	/*
	* Initialize the pointers to 4 consecutive MatrixA rows
	*/
	pInA0 = pSrcA;
	pInA1 = pInA0 + numCols;
	pInA2 = pInA1 + numCols;
	pInA3 = pInA2 + numCols;
	/*
	* Initialize the vector pointer
	*/
	pInVec = pSrcVecPtr;
	/*
	* reset accumulators
	*/
	acc0 = vdupq_n_f16(0.0f);
	acc1 = vdupq_n_f16(0.0f);
	acc2 = vdupq_n_f16(0.0f);
	acc3 = vdupq_n_f16(0.0f);

	pSrcA0Vec = pInA0;
	pSrcA1Vec = pInA1;
	pSrcA2Vec = pInA2;
	pSrcA3Vec = pInA3;

	blkCnt = numCols >> 3;
	while (blkCnt > 0U) {
	f16x8_t vecA;

	vecIn = vld1q(pInVec);
	pInVec += 8;
	vecA = vld1q(pSrcA0Vec);
	pSrcA0Vec += 8;
	acc0 = vfmaq(acc0, vecIn, vecA);
	vecA = vld1q(pSrcA1Vec);
	pSrcA1Vec += 8;
	acc1 = vfmaq(acc1, vecIn, vecA);
	vecA = vld1q(pSrcA2Vec);
	pSrcA2Vec += 8;
	acc2 = vfmaq(acc2, vecIn, vecA);
	vecA = vld1q(pSrcA3Vec);
	pSrcA3Vec += 8;
	acc3 = vfmaq(acc3, vecIn, vecA);

	blkCnt--;
	}
	/*
	* tail
	* (will be merged thru tail predication)
	*/
	blkCnt = numCols & 7;
	if (blkCnt > 0U) {
	mve_pred16_t p0 = vctp16q(blkCnt);
	f16x8_t vecA;

	vecIn = vldrhq_z_f16(pInVec, p0);
	vecA = vldrhq_z_f16(pSrcA0Vec, p0);
	acc0 = vfmaq(acc0, vecIn, vecA);
	vecA = vldrhq_z_f16(pSrcA1Vec, p0);
	acc1 = vfmaq(acc1, vecIn, vecA);
	vecA = vldrhq_z_f16(pSrcA2Vec, p0);
	acc2 = vfmaq(acc2, vecIn, vecA);
	vecA = vldrhq_z_f16(pSrcA3Vec, p0);
	acc3 = vfmaq(acc3, vecIn, vecA);
	}
	/*
	* Sum the partial parts
	*/
	acc0 = vmulq_n_f16(acc0,*pDualCoef++);
	acc0 = vfmaq_n_f16(acc0,acc1,*pDualCoef++);
	acc0 = vfmaq_n_f16(acc0,acc2,*pDualCoef++);
	acc0 = vfmaq_n_f16(acc0,acc3,*pDualCoef++);

	sum += (_Float16)vecAddAcrossF16Mve(acc0);

	pSrcA += numCols * 4;
	/*
	* Decrement the row loop counter
	*/
	row -= 4;
	}

	/*
	* compute 2 rows in parallel
	*/
	if (row >= 2) {
	float16_t const pSrcA0Vec, pSrcA1Vec, *pInVec;
	f16x8_t vecIn, acc0, acc1;
	float16_t const *pSrcVecPtr = in;

	/*
	* Initialize the pointers to 2 consecutive MatrixA rows
	*/
	pInA0 = pSrcA;
	pInA1 = pInA0 + numCols;
	/*
	* Initialize the vector pointer
	*/
	pInVec = pSrcVecPtr;
	/*
	* reset accumulators
	*/
	acc0 = vdupq_n_f16(0.0f);
	acc1 = vdupq_n_f16(0.0f);
	pSrcA0Vec = pInA0;
	pSrcA1Vec = pInA1;

	blkCnt = numCols >> 3;
	while (blkCnt > 0U) {
	f16x8_t vecA;

	vecIn = vld1q(pInVec);
	pInVec += 8;
	vecA = vld1q(pSrcA0Vec);
	pSrcA0Vec += 8;
	acc0 = vfmaq(acc0, vecIn, vecA);
	vecA = vld1q(pSrcA1Vec);
	pSrcA1Vec += 8;
	acc1 = vfmaq(acc1, vecIn, vecA);

	blkCnt--;
	}
	/*
	* tail
	* (will be merged thru tail predication)
	*/
	blkCnt = numCols & 7;
	if (blkCnt > 0U) {
	mve_pred16_t p0 = vctp16q(blkCnt);
	f16x8_t vecA;

	vecIn = vldrhq_z_f16(pInVec, p0);
	vecA = vldrhq_z_f16(pSrcA0Vec, p0);
	acc0 = vfmaq(acc0, vecIn, vecA);
	vecA = vldrhq_z_f16(pSrcA1Vec, p0);
	acc1 = vfmaq(acc1, vecIn, vecA);
	}
	/*
	* Sum the partial parts
	*/
	acc0 = vmulq_n_f16(acc0,*pDualCoef++);
	acc0 = vfmaq_n_f16(acc0,acc1,*pDualCoef++);

	sum += (_Float16)vecAddAcrossF16Mve(acc0);

	pSrcA += numCols * 2;
	row -= 2;
	}

	if (row >= 1) {
	f16x8_t vecIn, acc0;
	float16_t const pSrcA0Vec, pInVec;
	float16_t const *pSrcVecPtr = in;
	/*
	* Initialize the pointers to last MatrixA row
	*/
	pInA0 = pSrcA;
	/*
	* Initialize the vector pointer
	*/
	pInVec = pSrcVecPtr;
	/*
	* reset accumulators
	*/
	acc0 = vdupq_n_f16(0.0f);

	pSrcA0Vec = pInA0;

	blkCnt = numCols >> 3;
	while (blkCnt > 0U) {
	f16x8_t vecA;

	vecIn = vld1q(pInVec);
	pInVec += 8;
	vecA = vld1q(pSrcA0Vec);
	pSrcA0Vec += 8;
	acc0 = vfmaq(acc0, vecIn, vecA);

	blkCnt--;
	}
	/*
	* tail
	* (will be merged thru tail predication)
	*/
	blkCnt = numCols & 7;
	if (blkCnt > 0U) {
	mve_pred16_t p0 = vctp16q(blkCnt);
	f16x8_t vecA;

	vecIn = vldrhq_z_f16(pInVec, p0);
	vecA = vldrhq_z_f16(pSrcA0Vec, p0);
	acc0 = vfmaq(acc0, vecIn, vecA);
	}
	/*
	* Sum the partial parts
	*/
	sum += (_Float16)pDualCoef++ (_Float16)vecAddAcrossF16Mve(acc0);

	}

	*pResult = S->classes[STEP(sum)];
	}

	#else
	void arm_svm_linear_predict_f16(
	const arm_svm_linear_instance_f16 *S,
	const float16_t * in,
	int32_t * pResult)
	{
	_Float16 sum=S->intercept;
	_Float16 dot=0;
	uint32_t i,j;
	const float16_t *pSupport = S->supportVectors;

	for(i=0; i < S->nbOfSupportVectors; i++)
	{
	dot=0;
	for(j=0; j < S->vectorDimension; j++)
	{
	dot = (_Float16)dot + (_Float16)in[j]* (_Float16)*pSupport++;
	}
	sum += (_Float16)S->dualCoefficients[i] * (_Float16)dot;
	}
	*pResult=S->classes[STEP(sum)];
	}
	#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */

	/**
	* @} end of linearsvm group
	*/

	#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */


	#endif // EIDSP_LOAD_CMSIS_DSP_SOURCES