257 lines
6.7 KiB
C
257 lines
6.7 KiB
C
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/* ----------------------------------------------------------------------
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* Project: CMSIS DSP Library
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* Title: arm_mat_cholesky_f16.c
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* Description: Floating-point Cholesky decomposition
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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/matrix_functions_f16.h"
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#if defined(ARM_FLOAT16_SUPPORTED)
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/**
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@ingroup groupMatrix
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*/
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/**
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@addtogroup MatrixChol
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@{
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*/
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/**
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* @brief Floating-point Cholesky decomposition of positive-definite matrix.
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* @param[in] pSrc points to the instance of the input floating-point matrix structure.
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* @param[out] pDst points to the instance of the output floating-point matrix structure.
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* @return The function returns ARM_MATH_SIZE_MISMATCH, if the dimensions do not match.
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* @return execution status
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- \ref ARM_MATH_SUCCESS : Operation successful
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- \ref ARM_MATH_SIZE_MISMATCH : Matrix size check failed
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- \ref ARM_MATH_DECOMPOSITION_FAILURE : Input matrix cannot be decomposed
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* @par
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* If the matrix is ill conditioned or only semi-definite, then it is better using the LDL^t decomposition.
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* The decomposition of A is returning a lower triangular matrix U such that A = U U^t
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*/
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#if defined(ARM_MATH_MVE_FLOAT16) && !defined(ARM_MATH_AUTOVECTORIZE)
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#include "arm_helium_utils.h"
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arm_status arm_mat_cholesky_f16(
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const arm_matrix_instance_f16 * pSrc,
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arm_matrix_instance_f16 * pDst)
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{
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arm_status status; /* status of matrix inverse */
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#ifdef ARM_MATH_MATRIX_CHECK
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/* Check for matrix mismatch condition */
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if ((pSrc->numRows != pSrc->numCols) ||
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(pDst->numRows != pDst->numCols) ||
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(pSrc->numRows != pDst->numRows) )
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{
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/* Set status as ARM_MATH_SIZE_MISMATCH */
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status = ARM_MATH_SIZE_MISMATCH;
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}
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else
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#endif /* #ifdef ARM_MATH_MATRIX_CHECK */
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{
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int i,j,k;
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int n = pSrc->numRows;
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_Float16 invSqrtVj;
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float16_t *pA,*pG;
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int kCnt;
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mve_pred16_t p0;
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f16x8_t acc, acc0, acc1, acc2, acc3;
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f16x8_t vecGi;
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f16x8_t vecGj,vecGj0,vecGj1,vecGj2,vecGj3;
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pA = pSrc->pData;
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pG = pDst->pData;
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for(i=0 ;i < n ; i++)
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{
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for(j=i ; j+3 < n ; j+=4)
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{
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acc0 = vdupq_n_f16(0.0f16);
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acc0[0]=pA[(j + 0) * n + i];
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acc1 = vdupq_n_f16(0.0f16);
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acc1[0]=pA[(j + 1) * n + i];
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acc2 = vdupq_n_f16(0.0f16);
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acc2[0]=pA[(j + 2) * n + i];
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acc3 = vdupq_n_f16(0.0f16);
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acc3[0]=pA[(j + 3) * n + i];
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kCnt = i;
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for(k=0; k < i ; k+=8)
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{
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p0 = vctp16q(kCnt);
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vecGi=vldrhq_z_f16(&pG[i * n + k],p0);
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vecGj0=vldrhq_z_f16(&pG[(j + 0) * n + k],p0);
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vecGj1=vldrhq_z_f16(&pG[(j + 1) * n + k],p0);
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vecGj2=vldrhq_z_f16(&pG[(j + 2) * n + k],p0);
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vecGj3=vldrhq_z_f16(&pG[(j + 3) * n + k],p0);
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acc0 = vfmsq_m(acc0, vecGi, vecGj0, p0);
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acc1 = vfmsq_m(acc1, vecGi, vecGj1, p0);
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acc2 = vfmsq_m(acc2, vecGi, vecGj2, p0);
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acc3 = vfmsq_m(acc3, vecGi, vecGj3, p0);
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kCnt -= 8;
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}
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pG[(j + 0) * n + i] = vecAddAcrossF16Mve(acc0);
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pG[(j + 1) * n + i] = vecAddAcrossF16Mve(acc1);
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pG[(j + 2) * n + i] = vecAddAcrossF16Mve(acc2);
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pG[(j + 3) * n + i] = vecAddAcrossF16Mve(acc3);
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}
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for(; j < n ; j++)
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{
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kCnt = i;
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acc = vdupq_n_f16(0.0f16);
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acc[0] = pA[j * n + i];
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for(k=0; k < i ; k+=8)
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{
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p0 = vctp16q(kCnt);
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vecGi=vldrhq_z_f16(&pG[i * n + k],p0);
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vecGj=vldrhq_z_f16(&pG[j * n + k],p0);
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acc = vfmsq_m(acc, vecGi, vecGj,p0);
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kCnt -= 8;
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}
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pG[j * n + i] = vecAddAcrossF16Mve(acc);
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}
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if ((_Float16)pG[i * n + i] <= 0.0f16)
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{
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return(ARM_MATH_DECOMPOSITION_FAILURE);
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}
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invSqrtVj = 1.0f16/(_Float16)sqrtf((float32_t)pG[i * n + i]);
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for(j=i; j < n ; j++)
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{
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pG[j * n + i] = (_Float16)pG[j * n + i] * (_Float16)invSqrtVj ;
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}
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}
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status = ARM_MATH_SUCCESS;
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}
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/* Return to application */
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return (status);
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}
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#else
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arm_status arm_mat_cholesky_f16(
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const arm_matrix_instance_f16 * pSrc,
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arm_matrix_instance_f16 * pDst)
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{
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arm_status status; /* status of matrix inverse */
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#ifdef ARM_MATH_MATRIX_CHECK
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/* Check for matrix mismatch condition */
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if ((pSrc->numRows != pSrc->numCols) ||
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(pDst->numRows != pDst->numCols) ||
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(pSrc->numRows != pDst->numRows) )
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{
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/* Set status as ARM_MATH_SIZE_MISMATCH */
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status = ARM_MATH_SIZE_MISMATCH;
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}
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else
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#endif /* #ifdef ARM_MATH_MATRIX_CHECK */
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{
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int i,j,k;
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int n = pSrc->numRows;
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float16_t invSqrtVj;
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float16_t *pA,*pG;
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pA = pSrc->pData;
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pG = pDst->pData;
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for(i=0 ; i < n ; i++)
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{
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for(j=i ; j < n ; j++)
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{
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pG[j * n + i] = pA[j * n + i];
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for(k=0; k < i ; k++)
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{
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pG[j * n + i] = (_Float16)pG[j * n + i] - (_Float16)pG[i * n + k] * (_Float16)pG[j * n + k];
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}
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}
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if ((_Float16)pG[i * n + i] <= 0.0f16)
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{
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return(ARM_MATH_DECOMPOSITION_FAILURE);
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}
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/* The division is done in float32 for accuracy reason and
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because doing it in f16 would not have any impact on the performances.
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*/
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invSqrtVj = 1.0f/sqrtf((float32_t)pG[i * n + i]);
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for(j=i ; j < n ; j++)
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{
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pG[j * n + i] = (_Float16)pG[j * n + i] * (_Float16)invSqrtVj ;
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}
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}
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status = ARM_MATH_SUCCESS;
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}
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/* Return to application */
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return (status);
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}
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#endif /* defined(ARM_MATH_MVEF) && !defined(ARM_MATH_AUTOVECTORIZE) */
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/**
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@} end of MatrixChol group
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*/
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#endif /* #if defined(ARM_FLOAT16_SUPPORTED) */
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