/* ---------------------------------------------------------------------- * 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 #include /** @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) */