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/* ----------------------------------------------------------------------
* Project: CMSIS DSP Library
* Title: arm_jensenshannon_distance_f16.c
* Description: Jensen-Shannon distance between two vectors
*
* $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 "dsp/distance_functions_f16.h"
#if defined(ARM_FLOAT16_SUPPORTED)
#include <limits.h>
#include <math.h>
/**
@ingroup FloatDist
*/
/**
@defgroup JensenShannon Jensen-Shannon distance
Jensen-Shannon distance
*/
/**
@addtogroup JensenShannon
@{
*/
#if !defined(ARM_MATH_MVE_FLOAT16) || defined(ARM_MATH_AUTOVECTORIZE)
/// @private
__STATIC_INLINE float16_t rel_entr(float16_t x, float16_t y)
{
return ((_Float16)x * (_Float16)logf((float32_t)((_Float16)x / (_Float16)y)));
}
#endif
#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)
#include "arm_helium_utils.h"
#include "arm_vec_math_f16.h"
float16_t arm_jensenshannon_distance_f16(const float16_t *pA,const float16_t *pB, uint32_t blockSize)
{
uint32_t blkCnt;
float16_t tmp;
f16x8_t a, b, t, tmpV, accumV;
accumV = vdupq_n_f16(0.0f);
blkCnt = blockSize >> 3;
while (blkCnt > 0U) {
a = vld1q(pA);
b = vld1q(pB);
t = vaddq(a, b);
t = vmulq(t, 0.5f);
tmpV = vmulq(a, vrecip_medprec_f16(t));
tmpV = vlogq_f16(tmpV);
accumV = vfmaq(accumV, a, tmpV);
tmpV = vmulq_f16(b, vrecip_medprec_f16(t));
tmpV = vlogq_f16(tmpV);
accumV = vfmaq(accumV, b, tmpV);
pA += 8;
pB += 8;
blkCnt--;
}
/*
* tail
* (will be merged thru tail predication)
*/
blkCnt = blockSize & 7;
if (blkCnt > 0U) {
mve_pred16_t p0 = vctp16q(blkCnt);
a = vldrhq_z_f16(pA, p0);
b = vldrhq_z_f16(pB, p0);
t = vaddq(a, b);
t = vmulq(t, 0.5f);
tmpV = vmulq_f16(a, vrecip_medprec_f16(t));
tmpV = vlogq_f16(tmpV);
accumV = vfmaq_m_f16(accumV, a, tmpV, p0);
tmpV = vmulq_f16(b, vrecip_medprec_f16(t));
tmpV = vlogq_f16(tmpV);
accumV = vfmaq_m_f16(accumV, b, tmpV, p0);
}
arm_sqrt_f16((_Float16)vecAddAcrossF16Mve(accumV) / 2.0f16, &tmp);
return (tmp);
}
#else
/**
* @brief Jensen-Shannon distance between two vectors
*
* This function is assuming that elements of second vector are > 0
* and 0 only when the corresponding element of first vector is 0.
* Otherwise the result of the computation does not make sense
* and for speed reasons, the cases returning NaN or Infinity are not
* managed.
*
* When the function is computing x log (x / y) with x == 0 and y == 0,
* it will compute the right result (0) but a division by zero will occur
* and should be ignored in client code.
*
* @param[in] pA First vector
* @param[in] pB Second vector
* @param[in] blockSize vector length
* @return distance
*
*/
float16_t arm_jensenshannon_distance_f16(const float16_t *pA,const float16_t *pB, uint32_t blockSize)
{
_Float16 left, right,sum, tmp;
float16_t result;
uint32_t i;
left = 0.0f16;
right = 0.0f16;
for(i=0; i < blockSize; i++)
{
tmp = ((_Float16)pA[i] + (_Float16)pB[i]) / 2.0f16;
left += (_Float16)rel_entr(pA[i], tmp);
right += (_Float16)rel_entr(pB[i], tmp);
}
sum = left + right;
arm_sqrt_f16((_Float16)sum/2.0f16, &result);
return(result);
}
#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
/**
* @} end of JensenShannon group
*/
#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */
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