mirror of
https://github.com/Relintai/pandemonium_engine.git
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143 lines
6.4 KiB
C
143 lines
6.4 KiB
C
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/* Copyright (c) 2014, Cisco Systems, INC
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Written by XiangMingZhu WeiZhou MinPeng YanWang
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions
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are met:
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- Redistributions of source code must retain the above copyright
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notice, this list of conditions and the following disclaimer.
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- Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
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LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
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A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER
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OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
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LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
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NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#ifdef HAVE_CONFIG_H
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#include "config.h"
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#endif
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#include <xmmintrin.h>
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#include <emmintrin.h>
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#include <smmintrin.h>
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#include "main.h"
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#include "celt/x86/x86cpu.h"
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/* Entropy constrained matrix-weighted VQ, hard-coded to 5-element vectors, for a single input data vector */
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void silk_VQ_WMat_EC_sse4_1(
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opus_int8 *ind, /* O index of best codebook vector */
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opus_int32 *rate_dist_Q14, /* O best weighted quant error + mu * rate */
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opus_int *gain_Q7, /* O sum of absolute LTP coefficients */
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const opus_int16 *in_Q14, /* I input vector to be quantized */
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const opus_int32 *W_Q18, /* I weighting matrix */
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const opus_int8 *cb_Q7, /* I codebook */
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const opus_uint8 *cb_gain_Q7, /* I codebook effective gain */
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const opus_uint8 *cl_Q5, /* I code length for each codebook vector */
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const opus_int mu_Q9, /* I tradeoff betw. weighted error and rate */
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const opus_int32 max_gain_Q7, /* I maximum sum of absolute LTP coefficients */
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opus_int L /* I number of vectors in codebook */
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)
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{
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opus_int k, gain_tmp_Q7;
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const opus_int8 *cb_row_Q7;
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opus_int16 diff_Q14[ 5 ];
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opus_int32 sum1_Q14, sum2_Q16;
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__m128i C_tmp1, C_tmp2, C_tmp3, C_tmp4, C_tmp5;
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/* Loop over codebook */
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*rate_dist_Q14 = silk_int32_MAX;
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cb_row_Q7 = cb_Q7;
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for( k = 0; k < L; k++ ) {
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gain_tmp_Q7 = cb_gain_Q7[k];
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diff_Q14[ 0 ] = in_Q14[ 0 ] - silk_LSHIFT( cb_row_Q7[ 0 ], 7 );
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C_tmp1 = OP_CVTEPI16_EPI32_M64( &in_Q14[ 1 ] );
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C_tmp2 = OP_CVTEPI8_EPI32_M32( &cb_row_Q7[ 1 ] );
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C_tmp2 = _mm_slli_epi32( C_tmp2, 7 );
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C_tmp1 = _mm_sub_epi32( C_tmp1, C_tmp2 );
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diff_Q14[ 1 ] = _mm_extract_epi16( C_tmp1, 0 );
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diff_Q14[ 2 ] = _mm_extract_epi16( C_tmp1, 2 );
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diff_Q14[ 3 ] = _mm_extract_epi16( C_tmp1, 4 );
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diff_Q14[ 4 ] = _mm_extract_epi16( C_tmp1, 6 );
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/* Weighted rate */
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sum1_Q14 = silk_SMULBB( mu_Q9, cl_Q5[ k ] );
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/* Penalty for too large gain */
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sum1_Q14 = silk_ADD_LSHIFT32( sum1_Q14, silk_max( silk_SUB32( gain_tmp_Q7, max_gain_Q7 ), 0 ), 10 );
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silk_assert( sum1_Q14 >= 0 );
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/* first row of W_Q18 */
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C_tmp3 = _mm_loadu_si128( (__m128i *)(&W_Q18[ 1 ] ) );
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C_tmp4 = _mm_mul_epi32( C_tmp3, C_tmp1 );
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C_tmp4 = _mm_srli_si128( C_tmp4, 2 );
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C_tmp1 = _mm_shuffle_epi32( C_tmp1, _MM_SHUFFLE( 0, 3, 2, 1 ) ); /* shift right 4 bytes */
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C_tmp3 = _mm_shuffle_epi32( C_tmp3, _MM_SHUFFLE( 0, 3, 2, 1 ) ); /* shift right 4 bytes */
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C_tmp5 = _mm_mul_epi32( C_tmp3, C_tmp1 );
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C_tmp5 = _mm_srli_si128( C_tmp5, 2 );
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C_tmp5 = _mm_add_epi32( C_tmp4, C_tmp5 );
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C_tmp5 = _mm_slli_epi32( C_tmp5, 1 );
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C_tmp5 = _mm_add_epi32( C_tmp5, _mm_shuffle_epi32( C_tmp5, _MM_SHUFFLE( 0, 0, 0, 2 ) ) );
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sum2_Q16 = _mm_cvtsi128_si32( C_tmp5 );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 0 ], diff_Q14[ 0 ] );
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sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 0 ] );
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/* second row of W_Q18 */
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sum2_Q16 = silk_SMULWB( W_Q18[ 7 ], diff_Q14[ 2 ] );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 8 ], diff_Q14[ 3 ] );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 9 ], diff_Q14[ 4 ] );
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sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 6 ], diff_Q14[ 1 ] );
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sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 1 ] );
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/* third row of W_Q18 */
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sum2_Q16 = silk_SMULWB( W_Q18[ 13 ], diff_Q14[ 3 ] );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 14 ], diff_Q14[ 4 ] );
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sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 12 ], diff_Q14[ 2 ] );
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sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 2 ] );
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/* fourth row of W_Q18 */
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sum2_Q16 = silk_SMULWB( W_Q18[ 19 ], diff_Q14[ 4 ] );
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sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
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sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 18 ], diff_Q14[ 3 ] );
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sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 3 ] );
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/* last row of W_Q18 */
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sum2_Q16 = silk_SMULWB( W_Q18[ 24 ], diff_Q14[ 4 ] );
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sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 4 ] );
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silk_assert( sum1_Q14 >= 0 );
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/* find best */
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if( sum1_Q14 < *rate_dist_Q14 ) {
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*rate_dist_Q14 = sum1_Q14;
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*ind = (opus_int8)k;
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*gain_Q7 = gain_tmp_Q7;
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}
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/* Go to next cbk vector */
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cb_row_Q7 += LTP_ORDER;
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}
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}
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