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27
28 #ifdef HAVE_CONFIG_H
29 #include "config.h"
30 #endif
31
32 #include "main.h"
33
34 /* Entropy constrained matrix-weighted VQ, hard-coded to 5-element vectors, for a single input data vector */
silk_VQ_WMat_EC_c(opus_int8 * ind,opus_int32 * rate_dist_Q14,opus_int * gain_Q7,const opus_int16 * in_Q14,const opus_int32 * W_Q18,const opus_int8 * cb_Q7,const opus_uint8 * cb_gain_Q7,const opus_uint8 * cl_Q5,const opus_int mu_Q9,const opus_int32 max_gain_Q7,opus_int L)35 void silk_VQ_WMat_EC_c(
36 opus_int8 *ind, /* O index of best codebook vector */
37 opus_int32 *rate_dist_Q14, /* O best weighted quant error + mu * rate */
38 opus_int *gain_Q7, /* O sum of absolute LTP coefficients */
39 const opus_int16 *in_Q14, /* I input vector to be quantized */
40 const opus_int32 *W_Q18, /* I weighting matrix */
41 const opus_int8 *cb_Q7, /* I codebook */
42 const opus_uint8 *cb_gain_Q7, /* I codebook effective gain */
43 const opus_uint8 *cl_Q5, /* I code length for each codebook vector */
44 const opus_int mu_Q9, /* I tradeoff betw. weighted error and rate */
45 const opus_int32 max_gain_Q7, /* I maximum sum of absolute LTP coefficients */
46 opus_int L /* I number of vectors in codebook */
47 )
48 {
49 opus_int k, gain_tmp_Q7;
50 const opus_int8 *cb_row_Q7;
51 opus_int16 diff_Q14[ 5 ];
52 opus_int32 sum1_Q14, sum2_Q16;
53
54 /* Loop over codebook */
55 *rate_dist_Q14 = silk_int32_MAX;
56 cb_row_Q7 = cb_Q7;
57 for( k = 0; k < L; k++ ) {
58 gain_tmp_Q7 = cb_gain_Q7[k];
59
60 diff_Q14[ 0 ] = in_Q14[ 0 ] - silk_LSHIFT( cb_row_Q7[ 0 ], 7 );
61 diff_Q14[ 1 ] = in_Q14[ 1 ] - silk_LSHIFT( cb_row_Q7[ 1 ], 7 );
62 diff_Q14[ 2 ] = in_Q14[ 2 ] - silk_LSHIFT( cb_row_Q7[ 2 ], 7 );
63 diff_Q14[ 3 ] = in_Q14[ 3 ] - silk_LSHIFT( cb_row_Q7[ 3 ], 7 );
64 diff_Q14[ 4 ] = in_Q14[ 4 ] - silk_LSHIFT( cb_row_Q7[ 4 ], 7 );
65
66 /* Weighted rate */
67 sum1_Q14 = silk_SMULBB( mu_Q9, cl_Q5[ k ] );
68
69 /* Penalty for too large gain */
70 sum1_Q14 = silk_ADD_LSHIFT32( sum1_Q14, silk_max( silk_SUB32( gain_tmp_Q7, max_gain_Q7 ), 0 ), 10 );
71
72 silk_assert( sum1_Q14 >= 0 );
73
74 /* first row of W_Q18 */
75 sum2_Q16 = silk_SMULWB( W_Q18[ 1 ], diff_Q14[ 1 ] );
76 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 2 ], diff_Q14[ 2 ] );
77 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 3 ], diff_Q14[ 3 ] );
78 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 4 ], diff_Q14[ 4 ] );
79 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
80 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 0 ], diff_Q14[ 0 ] );
81 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 0 ] );
82
83 /* second row of W_Q18 */
84 sum2_Q16 = silk_SMULWB( W_Q18[ 7 ], diff_Q14[ 2 ] );
85 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 8 ], diff_Q14[ 3 ] );
86 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 9 ], diff_Q14[ 4 ] );
87 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
88 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 6 ], diff_Q14[ 1 ] );
89 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 1 ] );
90
91 /* third row of W_Q18 */
92 sum2_Q16 = silk_SMULWB( W_Q18[ 13 ], diff_Q14[ 3 ] );
93 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 14 ], diff_Q14[ 4 ] );
94 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
95 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 12 ], diff_Q14[ 2 ] );
96 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 2 ] );
97
98 /* fourth row of W_Q18 */
99 sum2_Q16 = silk_SMULWB( W_Q18[ 19 ], diff_Q14[ 4 ] );
100 sum2_Q16 = silk_LSHIFT( sum2_Q16, 1 );
101 sum2_Q16 = silk_SMLAWB( sum2_Q16, W_Q18[ 18 ], diff_Q14[ 3 ] );
102 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 3 ] );
103
104 /* last row of W_Q18 */
105 sum2_Q16 = silk_SMULWB( W_Q18[ 24 ], diff_Q14[ 4 ] );
106 sum1_Q14 = silk_SMLAWB( sum1_Q14, sum2_Q16, diff_Q14[ 4 ] );
107
108 silk_assert( sum1_Q14 >= 0 );
109
110 /* find best */
111 if( sum1_Q14 < *rate_dist_Q14 ) {
112 *rate_dist_Q14 = sum1_Q14;
113 *ind = (opus_int8)k;
114 *gain_Q7 = gain_tmp_Q7;
115 }
116
117 /* Go to next cbk vector */
118 cb_row_Q7 += LTP_ORDER;
119 }
120 }
121