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This commit is contained in:
Timothy B. Terriberry 2014-10-03 21:49:57 -07:00
parent 020a0a48d5
commit 554b349cdb
37 changed files with 961 additions and 963 deletions
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6
README.draft
View File

@ -9,12 +9,12 @@ in the Makefile.
An up-to-date implementation conforming to this standard is available in a
Git repository at git://git.xiph.org/opus.git or on a website at:
http://opus-codec.org/
However, although that implementation is expected to remain conformant
with the standard, it is the code in this RFC that shall remain normative.
However, although that implementation is expected to remain conformant
with the standard, it is the code in this RFC that shall remain normative.
To build from the git repository instead of using this RFC, follow these
steps:
1) Clone the repository (latest implementation of this standard at the time
1) Clone the repository (latest implementation of this standard at the time
of publication)
% git clone git://git.opus-codec.org/opus.git

2
celt/dump_modes/Makefile
View File

@ -4,7 +4,7 @@ INCLUDES=-I. -I../ -I../.. -I../../include
all: dump_modes
dump_modes:
$(CC) $(CFLAGS) $(INCLUDES) -DCUSTOM_MODES_ONLY -DCUSTOM_MODES dump_modes.c ../modes.c ../cwrs.c ../rate.c ../entenc.c ../entdec.c ../mathops.c ../mdct.c ../kiss_fft.c -o dump_modes -lm
$(CC) $(CFLAGS) $(INCLUDES) -DCUSTOM_MODES_ONLY -DCUSTOM_MODES dump_modes.c ../modes.c ../cwrs.c ../rate.c ../entenc.c ../entdec.c ../mathops.c ../mdct.c ../kiss_fft.c -o dump_modes -lm
clean:
rm -f dump_modes

48
celt/dump_modes/dump_modes.c
View File

@ -171,18 +171,18 @@ void dump_modes(FILE *file, CELTMode **modes, int nb_modes)
fprintf(file, "#define FFT_STATE%d_%d_%d\n", mode->Fs, mdctSize, k);
fprintf (file, "static const kiss_fft_state fft_state%d_%d_%d = {\n",
mode->Fs, mdctSize, k);
fprintf (file, "%d,\t/* nfft */\n", mode->mdct.kfft[k]->nfft);
fprintf (file, WORD16 ",\t/* scale */\n", mode->mdct.kfft[k]->scale);
fprintf (file, "%d, /* nfft */\n", mode->mdct.kfft[k]->nfft);
fprintf (file, WORD16 ", /* scale */\n", mode->mdct.kfft[k]->scale);
#ifdef FIXED_POINT
fprintf (file, "%d,\t/* scale_shift */\n", mode->mdct.kfft[k]->scale_shift);
fprintf (file, "%d, /* scale_shift */\n", mode->mdct.kfft[k]->scale_shift);
#endif
fprintf (file, "%d,\t/* shift */\n", mode->mdct.kfft[k]->shift);
fprintf (file, "%d, /* shift */\n", mode->mdct.kfft[k]->shift);
fprintf (file, "{");
for (j=0;j<2*MAXFACTORS;j++)
fprintf (file, "%d, ", mode->mdct.kfft[k]->factors[j]);
fprintf (file, "},\t/* factors */\n");
fprintf (file, "fft_bitrev%d,\t/* bitrev */\n", mode->mdct.kfft[k]->nfft);
fprintf (file, "fft_twiddles%d_%d,\t/* bitrev */\n", mode->Fs, mdctSize);
fprintf (file, "}, /* factors */\n");
fprintf (file, "fft_bitrev%d, /* bitrev */\n", mode->mdct.kfft[k]->nfft);
fprintf (file, "fft_twiddles%d_%d, /* bitrev */\n", mode->Fs, mdctSize);
fprintf (file, "};\n");
fprintf(file, "#endif\n");
@ -208,37 +208,37 @@ void dump_modes(FILE *file, CELTMode **modes, int nb_modes)
/* Print the actual mode data */
fprintf(file, "static const CELTMode mode%d_%d_%d = {\n", mode->Fs, mdctSize, mode->overlap);
fprintf(file, INT32 ",\t/* Fs */\n", mode->Fs);
fprintf(file, "%d,\t/* overlap */\n", mode->overlap);
fprintf(file, "%d,\t/* nbEBands */\n", mode->nbEBands);
fprintf(file, "%d,\t/* effEBands */\n", mode->effEBands);
fprintf(file, INT32 ", /* Fs */\n", mode->Fs);
fprintf(file, "%d, /* overlap */\n", mode->overlap);
fprintf(file, "%d, /* nbEBands */\n", mode->nbEBands);
fprintf(file, "%d, /* effEBands */\n", mode->effEBands);
fprintf(file, "{");
for (j=0;j<4;j++)
fprintf(file, WORD16 ", ", mode->preemph[j]);
fprintf(file, "},\t/* preemph */\n");
fprintf(file, "}, /* preemph */\n");
if (standard)
fprintf(file, "eband5ms,\t/* eBands */\n");
fprintf(file, "eband5ms, /* eBands */\n");
else
fprintf(file, "eBands%d_%d,\t/* eBands */\n", mode->Fs, mdctSize);
fprintf(file, "eBands%d_%d, /* eBands */\n", mode->Fs, mdctSize);
fprintf(file, "%d,\t/* maxLM */\n", mode->maxLM);
fprintf(file, "%d,\t/* nbShortMdcts */\n", mode->nbShortMdcts);
fprintf(file, "%d,\t/* shortMdctSize */\n", mode->shortMdctSize);
fprintf(file, "%d, /* maxLM */\n", mode->maxLM);
fprintf(file, "%d, /* nbShortMdcts */\n", mode->nbShortMdcts);
fprintf(file, "%d, /* shortMdctSize */\n", mode->shortMdctSize);
fprintf(file, "%d,\t/* nbAllocVectors */\n", mode->nbAllocVectors);
fprintf(file, "%d, /* nbAllocVectors */\n", mode->nbAllocVectors);
if (standard)
fprintf(file, "band_allocation,\t/* allocVectors */\n");
fprintf(file, "band_allocation, /* allocVectors */\n");
else
fprintf(file, "allocVectors%d_%d,\t/* allocVectors */\n", mode->Fs, mdctSize);
fprintf(file, "allocVectors%d_%d, /* allocVectors */\n", mode->Fs, mdctSize);
fprintf(file, "logN%d,\t/* logN */\n", framerate);
fprintf(file, "window%d,\t/* window */\n", mode->overlap);
fprintf(file, "logN%d, /* logN */\n", framerate);
fprintf(file, "window%d, /* window */\n", mode->overlap);
fprintf(file, "{%d, %d, {", mode->mdct.n, mode->mdct.maxshift);
for (k=0;k<=mode->mdct.maxshift;k++)
fprintf(file, "&fft_state%d_%d_%d, ", mode->Fs, mdctSize, k);
fprintf (file, "}, mdct_twiddles%d},\t/* mdct */\n", mdctSize);
fprintf (file, "}, mdct_twiddles%d}, /* mdct */\n", mdctSize);
fprintf(file, "{%d, cache_index%d, cache_bits%d, cache_caps%d},\t/* cache */\n",
fprintf(file, "{%d, cache_index%d, cache_bits%d, cache_caps%d}, /* cache */\n",
mode->cache.size, mode->Fs/mdctSize, mode->Fs/mdctSize, mode->Fs/mdctSize);
fprintf(file, "};\n");
}

40
celt/mips/fixed_generic_mipsr1.h
View File

@ -35,38 +35,38 @@
#undef MULT16_32_Q15_ADD
static inline int MULT16_32_Q15_ADD(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}
#undef MULT16_32_Q15_SUB
static inline int MULT16_32_Q15_SUB(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}
#undef MULT16_16_Q15_ADD
static inline int MULT16_16_Q15_ADD(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}
#undef MULT16_16_Q15_SUB
static inline int MULT16_16_Q15_SUB(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}

20
celt/mips/kiss_fft_mipsr1.h
View File

@ -37,20 +37,20 @@
#undef S_MUL_ADD
static inline int S_MUL_ADD(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("madd $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}
#undef S_MUL_SUB
static inline int S_MUL_SUB(int a, int b, int c, int d) {
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
int m;
asm volatile("MULT $ac1, %0, %1" : : "r" ((int)a), "r" ((int)b));
asm volatile("msub $ac1, %0, %1" : : "r" ((int)c), "r" ((int)d));
asm volatile("EXTR.W %0,$ac1, %1" : "=r" (m): "i" (15));
return m;
}
#undef C_MUL

10
celt/mips/pitch_mipsr1.h
View File

@ -46,11 +46,11 @@ static inline void dual_inner_prod(const opus_val16 *x, const opus_val16 *y01, c
/* Compute the norm of X+Y and X-Y as |X|^2 + |Y|^2 +/- sum(xy) */
for (j=0;j<N;j++)
{
asm volatile("MADD $ac1, %0, %1" : : "r" ((int)x[j]), "r" ((int)y01[j]));
asm volatile("MADD $ac2, %0, %1" : : "r" ((int)x[j]), "r" ((int)y02[j]));
++j;
asm volatile("MADD $ac1, %0, %1" : : "r" ((int)x[j]), "r" ((int)y01[j]));
asm volatile("MADD $ac2, %0, %1" : : "r" ((int)x[j]), "r" ((int)y02[j]));
asm volatile("MADD $ac1, %0, %1" : : "r" ((int)x[j]), "r" ((int)y01[j]));
asm volatile("MADD $ac2, %0, %1" : : "r" ((int)x[j]), "r" ((int)y02[j]));
++j;
asm volatile("MADD $ac1, %0, %1" : : "r" ((int)x[j]), "r" ((int)y01[j]));
asm volatile("MADD $ac2, %0, %1" : : "r" ((int)x[j]), "r" ((int)y02[j]));
}
asm volatile ("mflo %0, $ac1": "=r"(xy01));
asm volatile ("mflo %0, $ac2": "=r"(xy02));

16
celt/static_modes_fixed.h
View File

@ -426,10 +426,10 @@ static const opus_int16 fft_bitrev60[60] = {
#define FFT_STATE48000_960_0
static const kiss_fft_state fft_state48000_960_0 = {
480, /* nfft */
17476, /* scale */
17476, /* scale */
8, /* scale_shift */
-1, /* shift */
{5, 96, 3, 32, 4, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 96, 3, 32, 4, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev480, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};
@ -439,10 +439,10 @@ fft_twiddles48000_960, /* bitrev */
#define FFT_STATE48000_960_1
static const kiss_fft_state fft_state48000_960_1 = {
240, /* nfft */
17476, /* scale */
17476, /* scale */
7, /* scale_shift */
1, /* shift */
{5, 48, 3, 16, 4, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 48, 3, 16, 4, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev240, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};
@ -452,10 +452,10 @@ fft_twiddles48000_960, /* bitrev */
#define FFT_STATE48000_960_2
static const kiss_fft_state fft_state48000_960_2 = {
120, /* nfft */
17476, /* scale */
17476, /* scale */
6, /* scale_shift */
2, /* shift */
{5, 24, 3, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 24, 3, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev120, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};
@ -465,10 +465,10 @@ fft_twiddles48000_960, /* bitrev */
#define FFT_STATE48000_960_3
static const kiss_fft_state fft_state48000_960_3 = {
60, /* nfft */
17476, /* scale */
17476, /* scale */
5, /* scale_shift */
3, /* shift */
{5, 12, 3, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 12, 3, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev60, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};

6
celt/static_modes_float.h
View File

@ -440,7 +440,7 @@ static const kiss_fft_state fft_state48000_960_1 = {
240, /* nfft */
0.004166667f, /* scale */
1, /* shift */
{5, 48, 3, 16, 4, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 48, 3, 16, 4, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev240, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};
@ -452,7 +452,7 @@ static const kiss_fft_state fft_state48000_960_2 = {
120, /* nfft */
0.008333333f, /* scale */
2, /* shift */
{5, 24, 3, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 24, 3, 8, 2, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev120, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};
@ -464,7 +464,7 @@ static const kiss_fft_state fft_state48000_960_3 = {
60, /* nfft */
0.016666667f, /* scale */
3, /* shift */
{5, 12, 3, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
{5, 12, 3, 4, 4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, }, /* factors */
fft_bitrev60, /* bitrev */
fft_twiddles48000_960, /* bitrev */
};

8
celt/tests/test_unit_entropy.c
View File

@ -66,10 +66,10 @@ int main(int _argc,char **_argv){
const char *env_seed;
ret=0;
entropy=0;
if (_argc > 2) {
fprintf(stderr, "Usage: %s [<seed>]\n", _argv[0]);
return 1;
}
if (_argc > 2) {
fprintf(stderr, "Usage: %s [<seed>]\n", _argv[0]);
return 1;
}
env_seed = getenv("SEED");
if (_argc > 1)
seed = atoi(_argv[1]);

2
celt/tests/test_unit_mathops.c
View File

@ -224,7 +224,7 @@ void testexp2(void)
float error2 = fabs(exp(0.6931471805599453094*x/1024.0)-celt_exp2(x)/65536.0);
if (error1>0.0002&&error2>0.00004)
{
fprintf (stderr, "celt_exp2 failed: x = "WORD", error1 = %f, error2 = %f\n", x,error1,error2);
fprintf (stderr, "celt_exp2 failed: x = "WORD", error1 = %f, error2 = %f\n", x,error1,error2);
ret = 1;
}
}

2
doc/Doxyfile.in
View File

@ -611,7 +611,7 @@ WARN_LOGFILE =
# with spaces.
INPUT = @top_srcdir@/include/opus.h \
@top_srcdir@/include/opus_types.h \
@top_srcdir@/include/opus_types.h \
@top_srcdir@/include/opus_defines.h \
@top_srcdir@/include/opus_multistream.h \
@top_srcdir@/include/opus_custom.h

551
doc/customdoxygen.css
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File diff suppressed because it is too large Load Diff

10
doc/draft-ietf-codec-opus-update.xml
View File

@ -58,7 +58,7 @@
<middle>
<section title="Introduction">
<t>This document addresses minor issues that were discovered in the reference
implementation of the Opus codec that serves as the specification in
implementation of the Opus codec that serves as the specification in
<xref target="RFC6716">RFC 6716</xref>. Only issues affecting the decoder are
listed here. An up-to-date implementation of the Opus encoder can be found at
http://opus-codec.org/. The updated specification remains fully compatible with
@ -84,7 +84,7 @@
for( n = 0; n < DECODER_NUM_CHANNELS; n++ ) {
ret = silk_init_decoder( &channel_state[ n ] );
}
+ silk_memset(&((silk_decoder *)decState)->sStereo, 0,
+ silk_memset(&((silk_decoder *)decState)->sStereo, 0,
+ sizeof(((silk_decoder *)decState)->sStereo));
+ /* Not strictly needed, but it's cleaner that way */
+ ((silk_decoder *)decState)->prev_decode_only_middle = 0;
@ -218,16 +218,16 @@ RESAMPLER_ORDER_FIR_12 * sizeof( opus_int16 ) );
in the patch above are split using a backslash character. The backslashes
at the end of a line and the white space at the beginning
of the following line are not part of the patch. A properly formatted patch
including the three changes above is available at
including the three changes above is available at
<eref target="http://jmvalin.ca/misc_stuff/opus_update.patch"/>.
</t>
</section>
<section title="Downmix to Mono">
<t>The last issue is not strictly a bug, but it is an issue that has been reported
when downmixing an Opus decoded stream to mono, whether this is done inside the decoder
or as a post-processing step on the stereo decoder output. Opus intensity stereo allows
optionally coding the two channels 180-degrees out of phase on a per-band basis.
optionally coding the two channels 180-degrees out of phase on a per-band basis.
This provides better stereo quality than forcing the two channels to be in phase,
but when the output is downmixed to mono, the energy in the affected bands is cancelled
sometimes resulting in audible artefacts.

16
doc/draft-ietf-payload-rtp-opus.xml
View File

@ -419,7 +419,7 @@
</figure>
<t>
<xref target='opus-packetization'/> shows supported frame sizes in
<xref target='opus-packetization'/> shows supported frame sizes in
milliseconds of encoded speech or audio data for the speech and audio modes
(Mode) and sampling rates (fs) of Opus and shows how the timestamp is
incremented for packetization (ts incr). If the Opus encoder
@ -427,7 +427,7 @@
increment is the sum of the increments for the individual frames.
</t>
<texttable anchor='opus-packetization' title="Supported Opus frame
<texttable anchor='opus-packetization' title="Supported Opus frame
sizes and timestamp increments">
<ttcol align='center'>Mode</ttcol>
<ttcol align='center'>fs</ttcol>
@ -517,7 +517,7 @@
usage and encoding complexity, so an encoder SHOULD NOT encode
frequencies above the audio bandwidth specified by maxplaybackrate.
This parameter can take any value between 8000 and 48000, although
commonly the value will match one of the Opus bandwidths
commonly the value will match one of the Opus bandwidths
(<xref target="bandwidth_definitions"/>).
By default, the receiver is assumed to have no limitations, i.e. 48000.
<vspace blankLines='1'/>
@ -531,7 +531,7 @@
This parameter is useful to avoid wasting receiver resources by operating the audio
processing pipeline (e.g. echo cancellation) at a higher rate than necessary.
This parameter can take any value between 8000 and 48000, although
commonly the value will match one of the Opus bandwidths
commonly the value will match one of the Opus bandwidths
(<xref target="bandwidth_definitions"/>).
By default, the sender is assumed to have no limitations, i.e. 48000.
<vspace blankLines='1'/>
@ -708,9 +708,9 @@
mapped to "a=ptime" and "a=maxptime" attributes, respectively, in the
SDP.</t>
<t>The OPTIONAL media type parameters "maxaveragebitrate",
"maxplaybackrate", "minptime", "stereo", "cbr", "useinbandfec", and
"usedtx", when present, MUST be included in the "a=fmtp" attribute
<t>The OPTIONAL media type parameters "maxaveragebitrate",
"maxplaybackrate", "minptime", "stereo", "cbr", "useinbandfec", and
"usedtx", when present, MUST be included in the "a=fmtp" attribute
in the SDP, expressed as a media type string in the form of a
semicolon-separated list of parameter=value pairs (e.g.,
maxaveragebitrate=20000). They MUST NOT be specified in an
@ -838,7 +838,7 @@
of the other side MUST NOT send with an average bitrate higher than
"maxaveragebitrate" as it might overload the network and/or
receiver. The "maxaveragebitrate" parameter typically will not
compromise interoperability; however, some values might cause
compromise interoperability; however, some values might cause
application performance to suffer, and ought to be set with
care.</t>

14
doc/opus_in_isobmff.css
View File

@ -11,13 +11,13 @@
/* Boxes */
.pre
{
white-space: pre; /* CSS 2.0 */
white-space: pre-wrap; /* CSS 2.1 */
white-space: -pre-wrap; /* Opera 4-6 */
white-space: -o-pre-wrap; /* Opera 7 */
white-space: -moz-pre-wrap; /* Mozilla */
white-space: -hp-pre-wrap; /* HP Printers */
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white-space: -moz-pre-wrap; /* Mozilla */
white-space: -hp-pre-wrap; /* HP Printers */
word-wrap : break-word; /* IE 5+ */
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20
doc/opus_logo.svg
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@ -59,11 +59,11 @@
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Width:  |  Height:  |  Size: 8.4 KiB

After

Width:  |  Height:  |  Size: 8.5 KiB

2
doc/release.txt
View File

@ -10,7 +10,7 @@
- Verify 'make distcheck' produces a tarball with
the desired name.
- Push tag to public repo.
- Upload source package 'opus-${version}.tar.gz'
- Upload source package 'opus-${version}.tar.gz'
- Add to https://svn.xiph.org/releases/opus/
- Update checksum files
- svn commit

20
silk/CNG.c
View File

@ -128,16 +128,16 @@ void silk_CNG(
ALLOC( CNG_sig_Q10, length + MAX_LPC_ORDER, opus_int32 );
/* Generate CNG excitation */
gain_Q16 = silk_SMULWW( psDec->sPLC.randScale_Q14, psDec->sPLC.prevGain_Q16[1] );
if( gain_Q16 >= (1 << 21) || psCNG->CNG_smth_Gain_Q16 > (1 << 23) ) {
gain_Q16 = silk_SMULTT( gain_Q16, gain_Q16 );
gain_Q16 = silk_SUB_LSHIFT32(silk_SMULTT( psCNG->CNG_smth_Gain_Q16, psCNG->CNG_smth_Gain_Q16 ), gain_Q16, 5 );
gain_Q16 = silk_LSHIFT32( silk_SQRT_APPROX( gain_Q16 ), 16 );
} else {
gain_Q16 = silk_SMULWW( gain_Q16, gain_Q16 );
gain_Q16 = silk_SUB_LSHIFT32(silk_SMULWW( psCNG->CNG_smth_Gain_Q16, psCNG->CNG_smth_Gain_Q16 ), gain_Q16, 5 );
gain_Q16 = silk_LSHIFT32( silk_SQRT_APPROX( gain_Q16 ), 8 );
}
gain_Q16 = silk_SMULWW( psDec->sPLC.randScale_Q14, psDec->sPLC.prevGain_Q16[1] );
if( gain_Q16 >= (1 << 21) || psCNG->CNG_smth_Gain_Q16 > (1 << 23) ) {
gain_Q16 = silk_SMULTT( gain_Q16, gain_Q16 );
gain_Q16 = silk_SUB_LSHIFT32(silk_SMULTT( psCNG->CNG_smth_Gain_Q16, psCNG->CNG_smth_Gain_Q16 ), gain_Q16, 5 );
gain_Q16 = silk_LSHIFT32( silk_SQRT_APPROX( gain_Q16 ), 16 );
} else {
gain_Q16 = silk_SMULWW( gain_Q16, gain_Q16 );
gain_Q16 = silk_SUB_LSHIFT32(silk_SMULWW( psCNG->CNG_smth_Gain_Q16, psCNG->CNG_smth_Gain_Q16 ), gain_Q16, 5 );
gain_Q16 = silk_LSHIFT32( silk_SQRT_APPROX( gain_Q16 ), 8 );
}
silk_CNG_exc( CNG_sig_Q10 + MAX_LPC_ORDER, psCNG->CNG_exc_buf_Q14, gain_Q16, length, &psCNG->rand_seed );
/* Convert CNG NLSF to filter representation */

8
silk/VQ_WMat_EC.c
View File

@ -55,7 +55,7 @@ void silk_VQ_WMat_EC_c(
*rate_dist_Q14 = silk_int32_MAX;
cb_row_Q7 = cb_Q7;
for( k = 0; k < L; k++ ) {
gain_tmp_Q7 = cb_gain_Q7[k];
gain_tmp_Q7 = cb_gain_Q7[k];
diff_Q14[ 0 ] = in_Q14[ 0 ] - silk_LSHIFT( cb_row_Q7[ 0 ], 7 );
diff_Q14[ 1 ] = in_Q14[ 1 ] - silk_LSHIFT( cb_row_Q7[ 1 ], 7 );
@ -66,8 +66,8 @@ void silk_VQ_WMat_EC_c(
/* Weighted rate */
sum1_Q14 = silk_SMULBB( mu_Q9, cl_Q5[ k ] );
/* Penalty for too large gain */
sum1_Q14 = silk_ADD_LSHIFT32( sum1_Q14, silk_max( silk_SUB32( gain_tmp_Q7, max_gain_Q7 ), 0 ), 10 );
/* Penalty for too large gain */
sum1_Q14 = silk_ADD_LSHIFT32( sum1_Q14, silk_max( silk_SUB32( gain_tmp_Q7, max_gain_Q7 ), 0 ), 10 );
silk_assert( sum1_Q14 >= 0 );
@ -111,7 +111,7 @@ void silk_VQ_WMat_EC_c(
if( sum1_Q14 < *rate_dist_Q14 ) {
*rate_dist_Q14 = sum1_Q14;
*ind = (opus_int8)k;
*gain_Q7 = gain_tmp_Q7;
*gain_Q7 = gain_tmp_Q7;
}
/* Go to next cbk vector */

6
silk/fixed/burg_modified_FIX.c
View File

@ -73,13 +73,13 @@ void silk_burg_modified_c(
rshifts = 32 + 1 + N_BITS_HEAD_ROOM - lz;
if (rshifts > MAX_RSHIFTS) rshifts = MAX_RSHIFTS;
if (rshifts < MIN_RSHIFTS) rshifts = MIN_RSHIFTS;
if (rshifts > 0) {
C0 = (opus_int32)silk_RSHIFT64(C0_64, rshifts );
C0 = (opus_int32)silk_RSHIFT64(C0_64, rshifts );
} else {
C0 = silk_LSHIFT32((opus_int32)C0_64, -rshifts );
}
CAb[ 0 ] = CAf[ 0 ] = C0 + silk_SMMUL( SILK_FIX_CONST( FIND_LPC_COND_FAC, 32 ), C0 ) + 1; /* Q(-rshifts) */
silk_memset( C_first_row, 0, SILK_MAX_ORDER_LPC * sizeof( opus_int32 ) );
if( rshifts > 0 ) {

2
silk/fixed/encode_frame_FIX.c
View File

@ -289,7 +289,7 @@ opus_int silk_encode_frame_FIX(
for( i = 0; i < psEnc->sCmn.nb_subfr; i++ ) {
sEncCtrl.Gains_Q16[ i ] = silk_LSHIFT_SAT32( silk_SMULWB( sEncCtrl.GainsUnq_Q16[ i ], gainMult_Q8 ), 8 );
}
/* Quantize gains */
psEnc->sShape.LastGainIndex = sEncCtrl.lastGainIndexPrev;
silk_gains_quant( psEnc->sCmn.indices.GainsIndices, sEncCtrl.Gains_Q16,

8
silk/fixed/find_pred_coefs_FIX.c
View File

@ -119,16 +119,16 @@ void silk_find_pred_coefs_FIX(
silk_memset( psEncCtrl->LTPCoef_Q14, 0, psEnc->sCmn.nb_subfr * LTP_ORDER * sizeof( opus_int16 ) );
psEncCtrl->LTPredCodGain_Q7 = 0;
psEnc->sCmn.sum_log_gain_Q7 = 0;
psEnc->sCmn.sum_log_gain_Q7 = 0;
}
/* Limit on total predictive coding gain */
if( psEnc->sCmn.first_frame_after_reset ) {
minInvGain_Q30 = SILK_FIX_CONST( 1.0f / MAX_PREDICTION_POWER_GAIN_AFTER_RESET, 30 );
} else {
} else {
minInvGain_Q30 = silk_log2lin( silk_SMLAWB( 16 << 7, (opus_int32)psEncCtrl->LTPredCodGain_Q7, SILK_FIX_CONST( 1.0 / 3, 16 ) ) ); /* Q16 */
minInvGain_Q30 = silk_DIV32_varQ( minInvGain_Q30,
silk_SMULWW( SILK_FIX_CONST( MAX_PREDICTION_POWER_GAIN, 0 ),
minInvGain_Q30 = silk_DIV32_varQ( minInvGain_Q30,
silk_SMULWW( SILK_FIX_CONST( MAX_PREDICTION_POWER_GAIN, 0 ),
silk_SMLAWB( SILK_FIX_CONST( 0.25, 18 ), SILK_FIX_CONST( 0.75, 18 ), psEncCtrl->coding_quality_Q14 ) ), 14 );
}

2
silk/float/find_LPC_FLP.c
View File

@ -99,6 +99,6 @@ void silk_find_LPC_FLP(
silk_A2NLSF_FLP( NLSF_Q15, a, psEncC->predictLPCOrder );
}
silk_assert( psEncC->indices.NLSFInterpCoef_Q2 == 4 ||
silk_assert( psEncC->indices.NLSFInterpCoef_Q2 == 4 ||
( psEncC->useInterpolatedNLSFs && !psEncC->first_frame_after_reset && psEncC->nb_subfr == MAX_NB_SUBFR ) );
}

4
silk/float/find_pred_coefs_FLP.c
View File

@ -91,13 +91,13 @@ void silk_find_pred_coefs_FLP(
}
silk_memset( psEncCtrl->LTPCoef, 0, psEnc->sCmn.nb_subfr * LTP_ORDER * sizeof( silk_float ) );
psEncCtrl->LTPredCodGain = 0.0f;
psEnc->sCmn.sum_log_gain_Q7 = 0;
psEnc->sCmn.sum_log_gain_Q7 = 0;
}
/* Limit on total predictive coding gain */
if( psEnc->sCmn.first_frame_after_reset ) {
minInvGain = 1.0f / MAX_PREDICTION_POWER_GAIN_AFTER_RESET;
} else {
} else {
minInvGain = (silk_float)pow( 2, psEncCtrl->LTPredCodGain / 3 ) / MAX_PREDICTION_POWER_GAIN;
minInvGain /= 0.25f + 0.75f * psEncCtrl->coding_quality;
}

4
silk/float/pitch_analysis_core_FLP.c
View File

@ -182,8 +182,8 @@ opus_int silk_pitch_analysis_core_FLP( /* O Voicing estimate: 0 voiced,
/* Calculate first vector products before loop */
cross_corr = xcorr[ max_lag_4kHz - min_lag_4kHz ];
normalizer = silk_energy_FLP( target_ptr, sf_length_8kHz ) +
silk_energy_FLP( basis_ptr, sf_length_8kHz ) +
normalizer = silk_energy_FLP( target_ptr, sf_length_8kHz ) +
silk_energy_FLP( basis_ptr, sf_length_8kHz ) +
sf_length_8kHz * 4000.0f;
C[ 0 ][ min_lag_4kHz ] += (silk_float)( 2 * cross_corr / normalizer );

6
silk/log2lin.c
View File

@ -33,7 +33,7 @@ POSSIBILITY OF SUCH DAMAGE.
/* Approximation of 2^() (very close inverse of silk_lin2log()) */
/* Convert input to a linear scale */
opus_int32 silk_log2lin(
opus_int32 silk_log2lin(
const opus_int32 inLog_Q7 /* I input on log scale */
)
{
@ -42,8 +42,8 @@ opus_int32 silk_log2lin(
if( inLog_Q7 < 0 ) {
return 0;
} else if ( inLog_Q7 >= 3967 ) {
return silk_int32_MAX;
}
return silk_int32_MAX;
}
out = silk_LSHIFT( 1, silk_RSHIFT( inLog_Q7, 7 ) );
frac_Q7 = inLog_Q7 & 0x7F;

2
silk/main.h
View File

@ -208,7 +208,7 @@ void silk_quant_LTP_gains(
opus_int16 B_Q14[ MAX_NB_SUBFR * LTP_ORDER ], /* I/O (un)quantized LTP gains */
opus_int8 cbk_index[ MAX_NB_SUBFR ], /* O Codebook Index */
opus_int8 *periodicity_index, /* O Periodicity Index */
opus_int32 *sum_gain_dB_Q7, /* I/O Cumulative max prediction gain */
opus_int32 *sum_gain_dB_Q7, /* I/O Cumulative max prediction gain */
const opus_int32 W_Q18[ MAX_NB_SUBFR*LTP_ORDER*LTP_ORDER ], /* I Error Weights in Q18 */
opus_int mu_Q9, /* I Mu value (R/D tradeoff) */
opus_int lowComplexity, /* I Flag for low complexity */

2
silk/mips/NSQ_del_dec_mipsr1.h
View File

@ -127,7 +127,7 @@ static inline void silk_noise_shape_quantizer_del_dec(
temp64 = __builtin_mips_madd( temp64, pred_lag_ptr[ -2 ], b_Q14_2 );
temp64 = __builtin_mips_madd( temp64, pred_lag_ptr[ -3 ], b_Q14_3 );
temp64 = __builtin_mips_madd( temp64, pred_lag_ptr[ -4 ], b_Q14_4 );
temp64 += 32768;
temp64 += 32768;
LTP_pred_Q14 = __builtin_mips_extr_w(temp64, 16);
LTP_pred_Q14 = silk_LSHIFT( LTP_pred_Q14, 1 ); /* Q13 -> Q14 */
pred_lag_ptr++;

19
silk/quant_LTP_gains.c
View File

@ -36,7 +36,7 @@ void silk_quant_LTP_gains(
opus_int16 B_Q14[ MAX_NB_SUBFR * LTP_ORDER ], /* I/O (un)quantized LTP gains */
opus_int8 cbk_index[ MAX_NB_SUBFR ], /* O Codebook Index */
opus_int8 *periodicity_index, /* O Periodicity Index */
opus_int32 *sum_log_gain_Q7, /* I/O Cumulative max prediction gain */
opus_int32 *sum_log_gain_Q7, /* I/O Cumulative max prediction gain */
const opus_int32 W_Q18[ MAX_NB_SUBFR*LTP_ORDER*LTP_ORDER ], /* I Error Weights in Q18 */
opus_int mu_Q9, /* I Mu value (R/D tradeoff) */
opus_int lowComplexity, /* I Flag for low complexity */
@ -52,7 +52,7 @@ void silk_quant_LTP_gains(
const opus_int16 *b_Q14_ptr;
const opus_int32 *W_Q18_ptr;
opus_int32 rate_dist_Q14_subfr, rate_dist_Q14, min_rate_dist_Q14;
opus_int32 sum_log_gain_tmp_Q7, best_sum_log_gain_Q7, max_gain_Q7, gain_Q7;
opus_int32 sum_log_gain_tmp_Q7, best_sum_log_gain_Q7, max_gain_Q7, gain_Q7;
/***************************************************/
/* iterate over different codebooks with different */
@ -75,22 +75,22 @@ void silk_quant_LTP_gains(
b_Q14_ptr = B_Q14;
rate_dist_Q14 = 0;
sum_log_gain_tmp_Q7 = *sum_log_gain_Q7;
sum_log_gain_tmp_Q7 = *sum_log_gain_Q7;
for( j = 0; j < nb_subfr; j++ ) {
max_gain_Q7 = silk_log2lin( ( SILK_FIX_CONST( MAX_SUM_LOG_GAIN_DB / 6.0, 7 ) - sum_log_gain_tmp_Q7 )
+ SILK_FIX_CONST( 7, 7 ) ) - gain_safety;
max_gain_Q7 = silk_log2lin( ( SILK_FIX_CONST( MAX_SUM_LOG_GAIN_DB / 6.0, 7 ) - sum_log_gain_tmp_Q7 )
+ SILK_FIX_CONST( 7, 7 ) ) - gain_safety;
silk_VQ_WMat_EC(
&temp_idx[ j ], /* O index of best codebook vector */
&rate_dist_Q14_subfr, /* O best weighted quantization error + mu * rate */
&gain_Q7, /* O sum of absolute LTP coefficients */
&gain_Q7, /* O sum of absolute LTP coefficients */
b_Q14_ptr, /* I input vector to be quantized */
W_Q18_ptr, /* I weighting matrix */
cbk_ptr_Q7, /* I codebook */
cbk_gain_ptr_Q7, /* I codebook effective gains */
cl_ptr_Q5, /* I code length for each codebook vector */
mu_Q9, /* I tradeoff between weighted error and rate */
max_gain_Q7, /* I maximum sum of absolute LTP coefficients */
max_gain_Q7, /* I maximum sum of absolute LTP coefficients */
cbk_size, /* I number of vectors in codebook */
arch /* I Run-time architecture */
);
@ -110,7 +110,7 @@ void silk_quant_LTP_gains(
min_rate_dist_Q14 = rate_dist_Q14;
*periodicity_index = (opus_int8)k;
silk_memcpy( cbk_index, temp_idx, nb_subfr * sizeof( opus_int8 ) );
best_sum_log_gain_Q7 = sum_log_gain_tmp_Q7;
best_sum_log_gain_Q7 = sum_log_gain_tmp_Q7;
}
/* Break early in low-complexity mode if rate distortion is below threshold */
@ -125,6 +125,5 @@ void silk_quant_LTP_gains(
B_Q14[ j * LTP_ORDER + k ] = silk_LSHIFT( cbk_ptr_Q7[ cbk_index[ j ] * LTP_ORDER + k ], 7 );
}
}
*sum_log_gain_Q7 = best_sum_log_gain_Q7;
*sum_log_gain_Q7 = best_sum_log_gain_Q7;
}

54
silk/resampler_rom.c
View File

@ -41,36 +41,36 @@ POSSIBILITY OF SUCH DAMAGE.
/* Tables with IIR and FIR coefficients for fractional downsamplers (123 Words) */
silk_DWORD_ALIGN const opus_int16 silk_Resampler_3_4_COEFS[ 2 + 3 * RESAMPLER_DOWN_ORDER_FIR0 / 2 ] = {
-20694, -13867,
-49, 64, 17, -157, 353, -496, 163, 11047, 22205,
-39, 6, 91, -170, 186, 23, -896, 6336, 19928,
-19, -36, 102, -89, -24, 328, -951, 2568, 15909,
-20694, -13867,
-49, 64, 17, -157, 353, -496, 163, 11047, 22205,
-39, 6, 91, -170, 186, 23, -896, 6336, 19928,
-19, -36, 102, -89, -24, 328, -951, 2568, 15909,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_2_3_COEFS[ 2 + 2 * RESAMPLER_DOWN_ORDER_FIR0 / 2 ] = {
-14457, -14019,
64, 128, -122, 36, 310, -768, 584, 9267, 17733,
12, 128, 18, -142, 288, -117, -865, 4123, 14459,
-14457, -14019,
64, 128, -122, 36, 310, -768, 584, 9267, 17733,
12, 128, 18, -142, 288, -117, -865, 4123, 14459,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_1_2_COEFS[ 2 + RESAMPLER_DOWN_ORDER_FIR1 / 2 ] = {
616, -14323,
-10, 39, 58, -46, -84, 120, 184, -315, -541, 1284, 5380, 9024,
616, -14323,
-10, 39, 58, -46, -84, 120, 184, -315, -541, 1284, 5380, 9024,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_1_3_COEFS[ 2 + RESAMPLER_DOWN_ORDER_FIR2 / 2 ] = {
16102, -15162,
-13, 0, 20, 26, 5, -31, -43, -4, 65, 90, 7, -157, -248, -44, 593, 1583, 2612, 3271,
16102, -15162,
-13, 0, 20, 26, 5, -31, -43, -4, 65, 90, 7, -157, -248, -44, 593, 1583, 2612, 3271,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_1_4_COEFS[ 2 + RESAMPLER_DOWN_ORDER_FIR2 / 2 ] = {
22500, -15099,
3, -14, -20, -15, 2, 25, 37, 25, -16, -71, -107, -79, 50, 292, 623, 982, 1288, 1464,
22500, -15099,
3, -14, -20, -15, 2, 25, 37, 25, -16, -71, -107, -79, 50, 292, 623, 982, 1288, 1464,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_1_6_COEFS[ 2 + RESAMPLER_DOWN_ORDER_FIR2 / 2 ] = {
27540, -15257,
17, 12, 8, 1, -10, -22, -30, -32, -22, 3, 44, 100, 168, 243, 317, 381, 429, 455,
27540, -15257,
17, 12, 8, 1, -10, -22, -30, -32, -22, 3, 44, 100, 168, 243, 317, 381, 429, 455,
};
silk_DWORD_ALIGN const opus_int16 silk_Resampler_2_3_COEFS_LQ[ 2 + 2 * 2 ] = {
@ -81,16 +81,16 @@ silk_DWORD_ALIGN const opus_int16 silk_Resampler_2_3_COEFS_LQ[ 2 + 2 * 2 ] = {
/* Table with interplation fractions of 1/24, 3/24, 5/24, ... , 23/24 : 23/24 (46 Words) */
silk_DWORD_ALIGN const opus_int16 silk_resampler_frac_FIR_12[ 12 ][ RESAMPLER_ORDER_FIR_12 / 2 ] = {
{ 189, -600, 617, 30567 },
{ 117, -159, -1070, 29704 },
{ 52, 221, -2392, 28276 },
{ -4, 529, -3350, 26341 },
{ -48, 758, -3956, 23973 },
{ -80, 905, -4235, 21254 },
{ -99, 972, -4222, 18278 },
{ -107, 967, -3957, 15143 },
{ -103, 896, -3487, 11950 },
{ -91, 773, -2865, 8798 },
{ -71, 611, -2143, 5784 },
{ -46, 425, -1375, 2996 },
{ 189, -600, 617, 30567 },
{ 117, -159, -1070, 29704 },
{ 52, 221, -2392, 28276 },
{ -4, 529, -3350, 26341 },
{ -48, 758, -3956, 23973 },
{ -80, 905, -4235, 21254 },
{ -99, 972, -4222, 18278 },
{ -107, 967, -3957, 15143 },
{ -103, 896, -3487, 11950 },
{ -91, 773, -2865, 8798 },
{ -71, 611, -2143, 5784 },
{ -46, 425, -1375, 2996 },
};

2
silk/structs.h
View File

@ -171,7 +171,7 @@ typedef struct {
opus_int32 pitchEstimationThreshold_Q16; /* Threshold for pitch estimator */
opus_int LTPQuantLowComplexity; /* Flag for low complexity LTP quantization */
opus_int mu_LTP_Q9; /* Rate-distortion tradeoff in LTP quantization */
opus_int32 sum_log_gain_Q7; /* Cumulative max prediction gain */
opus_int32 sum_log_gain_Q7; /* Cumulative max prediction gain */
opus_int NLSF_MSVQ_Survivors; /* Number of survivors in NLSF MSVQ */
opus_int first_frame_after_reset; /* Flag for deactivating NLSF interpolation, pitch prediction */
opus_int controlled_since_last_payload; /* Flag for ensuring codec_control only runs once per packet */

2
silk/tuning_parameters.h
View File

@ -64,7 +64,7 @@ extern "C"
#define MU_LTP_QUANT_WB 0.02f
/* Max cumulative LTP gain */
#define MAX_SUM_LOG_GAIN_DB 250.0f
#define MAX_SUM_LOG_GAIN_DB 250.0f
/***********************/
/* High pass filtering */

112
src/mlp.c
View File

@ -41,36 +41,36 @@
#if 0
static OPUS_INLINE opus_val16 tansig_approx(opus_val32 _x) /* Q19 */
{
int i;
opus_val16 xx; /* Q11 */
/*double x, y;*/
opus_val16 dy, yy; /* Q14 */
/*x = 1.9073e-06*_x;*/
if (_x>=QCONST32(8,19))
return QCONST32(1.,14);
if (_x<=-QCONST32(8,19))
return -QCONST32(1.,14);
xx = EXTRACT16(SHR32(_x, 8));
/*i = lrint(25*x);*/
i = SHR32(ADD32(1024,MULT16_16(25, xx)),11);
/*x -= .04*i;*/
xx -= EXTRACT16(SHR32(MULT16_16(20972,i),8));
/*x = xx*(1./2048);*/
/*y = tansig_table[250+i];*/
yy = tansig_table[250+i];
/*y = yy*(1./16384);*/
dy = 16384-MULT16_16_Q14(yy,yy);
yy = yy + MULT16_16_Q14(MULT16_16_Q11(xx,dy),(16384 - MULT16_16_Q11(yy,xx)));
return yy;
int i;
opus_val16 xx; /* Q11 */
/*double x, y;*/
opus_val16 dy, yy; /* Q14 */
/*x = 1.9073e-06*_x;*/
if (_x>=QCONST32(8,19))
return QCONST32(1.,14);
if (_x<=-QCONST32(8,19))
return -QCONST32(1.,14);
xx = EXTRACT16(SHR32(_x, 8));
/*i = lrint(25*x);*/
i = SHR32(ADD32(1024,MULT16_16(25, xx)),11);
/*x -= .04*i;*/
xx -= EXTRACT16(SHR32(MULT16_16(20972,i),8));
/*x = xx*(1./2048);*/
/*y = tansig_table[250+i];*/
yy = tansig_table[250+i];
/*y = yy*(1./16384);*/
dy = 16384-MULT16_16_Q14(yy,yy);
yy = yy + MULT16_16_Q14(MULT16_16_Q11(xx,dy),(16384 - MULT16_16_Q11(yy,xx)));
return yy;
}
#else
/*extern const float tansig_table[501];*/
static OPUS_INLINE float tansig_approx(float x)
{
int i;
float y, dy;
float sign=1;
/* Tests are reversed to catch NaNs */
int i;
float y, dy;
float sign=1;
/* Tests are reversed to catch NaNs */
if (!(x<8))
return 1;
if (!(x>-8))
@ -80,43 +80,43 @@ static OPUS_INLINE float tansig_approx(float x)
if (celt_isnan(x))
return 0;
#endif
if (x<0)
{
x=-x;
sign=-1;
}
i = (int)floor(.5f+25*x);
x -= .04f*i;
y = tansig_table[i];
dy = 1-y*y;
y = y + x*dy*(1 - y*x);
return sign*y;
if (x<0)
{
x=-x;
sign=-1;
}
i = (int)floor(.5f+25*x);
x -= .04f*i;
y = tansig_table[i];
dy = 1-y*y;
y = y + x*dy*(1 - y*x);
return sign*y;
}
#endif
#if 0
void mlp_process(const MLP *m, const opus_val16 *in, opus_val16 *out)
{
int j;
opus_val16 hidden[MAX_NEURONS];
const opus_val16 *W = m->weights;
/* Copy to tmp_in */
for (j=0;j<m->topo[1];j++)
{
int k;
opus_val32 sum = SHL32(EXTEND32(*W++),8);
for (k=0;k<m->topo[0];k++)
sum = MAC16_16(sum, in[k],*W++);
hidden[j] = tansig_approx(sum);
}
for (j=0;j<m->topo[2];j++)
{
int k;
opus_val32 sum = SHL32(EXTEND32(*W++),14);
for (k=0;k<m->topo[1];k++)
sum = MAC16_16(sum, hidden[k], *W++);
out[j] = tansig_approx(EXTRACT16(PSHR32(sum,17)));
}
int j;
opus_val16 hidden[MAX_NEURONS];
const opus_val16 *W = m->weights;
/* Copy to tmp_in */
for (j=0;j<m->topo[1];j++)
{
int k;
opus_val32 sum = SHL32(EXTEND32(*W++),8);
for (k=0;k<m->topo[0];k++)
sum = MAC16_16(sum, in[k],*W++);
hidden[j] = tansig_approx(sum);
}
for (j=0;j<m->topo[2];j++)
{
int k;
opus_val32 sum = SHL32(EXTEND32(*W++),14);
for (k=0;k<m->topo[1];k++)
sum = MAC16_16(sum, hidden[k], *W++);
out[j] = tansig_approx(EXTRACT16(PSHR32(sum,17)));
}
}
#else
void mlp_process(const MLP *m, const float *in, float *out)

6
src/mlp.h
View File

@ -31,9 +31,9 @@
#include "arch.h"
typedef struct {
int layers;
const int *topo;
const float *weights;
int layers;
const int *topo;
const float *weights;
} MLP;
void mlp_process(const MLP *m, const float *in, float *out);

844
src/mlp_train.c
View File

@ -39,70 +39,70 @@ int stopped = 0;
void handler(int sig)
{
stopped = 1;
signal(sig, handler);
stopped = 1;
signal(sig, handler);
}
MLPTrain * mlp_init(int *topo, int nbLayers, float *inputs, float *outputs, int nbSamples)
{
int i, j, k;
MLPTrain *net;
int inDim, outDim;
net = malloc(sizeof(*net));
net->topo = malloc(nbLayers*sizeof(net->topo[0]));
for (i=0;i<nbLayers;i++)
net->topo[i] = topo[i];
inDim = topo[0];
outDim = topo[nbLayers-1];
net->in_rate = malloc((inDim+1)*sizeof(net->in_rate[0]));
net->weights = malloc((nbLayers-1)*sizeof(net->weights));
net->best_weights = malloc((nbLayers-1)*sizeof(net->weights));
for (i=0;i<nbLayers-1;i++)
{
net->weights[i] = malloc((topo[i]+1)*topo[i+1]*sizeof(net->weights[0][0]));
net->best_weights[i] = malloc((topo[i]+1)*topo[i+1]*sizeof(net->weights[0][0]));
}
double inMean[inDim];
for (j=0;j<inDim;j++)
{
double std=0;
inMean[j] = 0;
for (i=0;i<nbSamples;i++)
{
inMean[j] += inputs[i*inDim+j];
std += inputs[i*inDim+j]*inputs[i*inDim+j];
}
inMean[j] /= nbSamples;
std /= nbSamples;
net->in_rate[1+j] = .5/(.0001+std);
std = std-inMean[j]*inMean[j];
if (std<.001)
std = .001;
std = 1/sqrt(inDim*std);
for (k=0;k<topo[1];k++)
net->weights[0][k*(topo[0]+1)+j+1] = randn(std);
}
net->in_rate[0] = 1;
for (j=0;j<topo[1];j++)
{
double sum = 0;
for (k=0;k<inDim;k++)
sum += inMean[k]*net->weights[0][j*(topo[0]+1)+k+1];
net->weights[0][j*(topo[0]+1)] = -sum;
}
for (j=0;j<outDim;j++)
{
double mean = 0;
double std;
for (i=0;i<nbSamples;i++)
mean += outputs[i*outDim+j];
mean /= nbSamples;
std = 1/sqrt(topo[nbLayers-2]);
net->weights[nbLayers-2][j*(topo[nbLayers-2]+1)] = mean;
for (k=0;k<topo[nbLayers-2];k++)
net->weights[nbLayers-2][j*(topo[nbLayers-2]+1)+k+1] = randn(std);
}
return net;
int i, j, k;
MLPTrain *net;
int inDim, outDim;
net = malloc(sizeof(*net));
net->topo = malloc(nbLayers*sizeof(net->topo[0]));
for (i=0;i<nbLayers;i++)
net->topo[i] = topo[i];
inDim = topo[0];
outDim = topo[nbLayers-1];
net->in_rate = malloc((inDim+1)*sizeof(net->in_rate[0]));
net->weights = malloc((nbLayers-1)*sizeof(net->weights));
net->best_weights = malloc((nbLayers-1)*sizeof(net->weights));
for (i=0;i<nbLayers-1;i++)
{
net->weights[i] = malloc((topo[i]+1)*topo[i+1]*sizeof(net->weights[0][0]));
net->best_weights[i] = malloc((topo[i]+1)*topo[i+1]*sizeof(net->weights[0][0]));
}
double inMean[inDim];
for (j=0;j<inDim;j++)
{
double std=0;
inMean[j] = 0;
for (i=0;i<nbSamples;i++)
{
inMean[j] += inputs[i*inDim+j];
std += inputs[i*inDim+j]*inputs[i*inDim+j];
}
inMean[j] /= nbSamples;
std /= nbSamples;
net->in_rate[1+j] = .5/(.0001+std);
std = std-inMean[j]*inMean[j];
if (std<.001)
std = .001;
std = 1/sqrt(inDim*std);
for (k=0;k<topo[1];k++)
net->weights[0][k*(topo[0]+1)+j+1] = randn(std);
}
net->in_rate[0] = 1;
for (j=0;j<topo[1];j++)
{
double sum = 0;
for (k=0;k<inDim;k++)
sum += inMean[k]*net->weights[0][j*(topo[0]+1)+k+1];
net->weights[0][j*(topo[0]+1)] = -sum;
}
for (j=0;j<outDim;j++)
{
double mean = 0;
double std;
for (i=0;i<nbSamples;i++)
mean += outputs[i*outDim+j];
mean /= nbSamples;
std = 1/sqrt(topo[nbLayers-2]);
net->weights[nbLayers-2][j*(topo[nbLayers-2]+1)] = mean;
for (k=0;k<topo[nbLayers-2];k++)
net->weights[nbLayers-2][j*(topo[nbLayers-2]+1)+k+1] = randn(std);
}
return net;
}
#define MAX_NEURONS 100
@ -110,75 +110,75 @@ MLPTrain * mlp_init(int *topo, int nbLayers, float *inputs, float *outputs, int
double compute_gradient(MLPTrain *net, float *inputs, float *outputs, int nbSamples, double *W0_grad, double *W1_grad, double *error_rate)
{
int i,j;
int s;
int inDim, outDim, hiddenDim;
int *topo;
double *W0, *W1;
double rms=0;
int W0_size, W1_size;
double hidden[MAX_NEURONS];
double netOut[MAX_NEURONS];
double error[MAX_NEURONS];
int i,j;
int s;
int inDim, outDim, hiddenDim;
int *topo;
double *W0, *W1;
double rms=0;
int W0_size, W1_size;
double hidden[MAX_NEURONS];
double netOut[MAX_NEURONS];
double error[MAX_NEURONS];
topo = net->topo;
inDim = net->topo[0];
hiddenDim = net->topo[1];
outDim = net->topo[2];
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
W0 = net->weights[0];
W1 = net->weights[1];
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
for (i=0;i<outDim;i++)
netOut[i] = outputs[i];
for (i=0;i<outDim;i++)
error_rate[i] = 0;
for (s=0;s<nbSamples;s++)
{
float *in, *out;
in = inputs+s*inDim;
out = outputs + s*outDim;
for (i=0;i<hiddenDim;i++)
{
double sum = W0[i*(inDim+1)];
for (j=0;j<inDim;j++)
sum += W0[i*(inDim+1)+j+1]*in[j];
hidden[i] = tansig_approx(sum);
}
for (i=0;i<outDim;i++)
{
double sum = W1[i*(hiddenDim+1)];
for (j=0;j<hiddenDim;j++)
sum += W1[i*(hiddenDim+1)+j+1]*hidden[j];
netOut[i] = tansig_approx(sum);
error[i] = out[i] - netOut[i];
rms += error[i]*error[i];
error_rate[i] += fabs(error[i])>1;
/*error[i] = error[i]/(1+fabs(error[i]));*/
}
/* Back-propagate error */
for (i=0;i<outDim;i++)
{
float grad = 1-netOut[i]*netOut[i];
W1_grad[i*(hiddenDim+1)] += error[i]*grad;
for (j=0;j<hiddenDim;j++)
W1_grad[i*(hiddenDim+1)+j+1] += grad*error[i]*hidden[j];
}
for (i=0;i<hiddenDim;i++)
{
double grad;
grad = 0;
for (j=0;j<outDim;j++)
grad += error[j]*W1[j*(hiddenDim+1)+i+1];
grad *= 1-hidden[i]*hidden[i];
W0_grad[i*(inDim+1)] += grad;
for (j=0;j<inDim;j++)
W0_grad[i*(inDim+1)+j+1] += grad*in[j];
}
}
return rms;
topo = net->topo;
inDim = net->topo[0];
hiddenDim = net->topo[1];
outDim = net->topo[2];
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
W0 = net->weights[0];
W1 = net->weights[1];
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
for (i=0;i<outDim;i++)
netOut[i] = outputs[i];
for (i=0;i<outDim;i++)
error_rate[i] = 0;
for (s=0;s<nbSamples;s++)
{
float *in, *out;
in = inputs+s*inDim;
out = outputs + s*outDim;
for (i=0;i<hiddenDim;i++)
{
double sum = W0[i*(inDim+1)];
for (j=0;j<inDim;j++)
sum += W0[i*(inDim+1)+j+1]*in[j];
hidden[i] = tansig_approx(sum);
}
for (i=0;i<outDim;i++)
{
double sum = W1[i*(hiddenDim+1)];
for (j=0;j<hiddenDim;j++)
sum += W1[i*(hiddenDim+1)+j+1]*hidden[j];
netOut[i] = tansig_approx(sum);
error[i] = out[i] - netOut[i];
rms += error[i]*error[i];
error_rate[i] += fabs(error[i])>1;
/*error[i] = error[i]/(1+fabs(error[i]));*/
}
/* Back-propagate error */
for (i=0;i<outDim;i++)
{
float grad = 1-netOut[i]*netOut[i];
W1_grad[i*(hiddenDim+1)] += error[i]*grad;
for (j=0;j<hiddenDim;j++)
W1_grad[i*(hiddenDim+1)+j+1] += grad*error[i]*hidden[j];
}
for (i=0;i<hiddenDim;i++)
{
double grad;
grad = 0;
for (j=0;j<outDim;j++)
grad += error[j]*W1[j*(hiddenDim+1)+i+1];
grad *= 1-hidden[i]*hidden[i];
W0_grad[i*(inDim+1)] += grad;
for (j=0;j<inDim;j++)
W0_grad[i*(inDim+1)+j+1] += grad*in[j];
}
}
return rms;
}
#define NB_THREADS 8
@ -187,315 +187,315 @@ sem_t sem_begin[NB_THREADS];
sem_t sem_end[NB_THREADS];
struct GradientArg {
int id;
int done;
MLPTrain *net;
float *inputs;
float *outputs;
int nbSamples;
double *W0_grad;
double *W1_grad;
double rms;
double error_rate[MAX_OUT];
int id;
int done;
MLPTrain *net;
float *inputs;
float *outputs;
int nbSamples;
double *W0_grad;
double *W1_grad;
double rms;
double error_rate[MAX_OUT];
};
void *gradient_thread_process(void *_arg)
{
int W0_size, W1_size;
struct GradientArg *arg = _arg;
int *topo = arg->net->topo;
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
double W0_grad[W0_size];
double W1_grad[W1_size];
arg->W0_grad = W0_grad;
arg->W1_grad = W1_grad;
while (1)
{
sem_wait(&sem_begin[arg->id]);
if (arg->done)
break;
arg->rms = compute_gradient(arg->net, arg->inputs, arg->outputs, arg->nbSamples, arg->W0_grad, arg->W1_grad, arg->error_rate);
sem_post(&sem_end[arg->id]);
}
fprintf(stderr, "done\n");
return NULL;
int W0_size, W1_size;
struct GradientArg *arg = _arg;
int *topo = arg->net->topo;
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
double W0_grad[W0_size];
double W1_grad[W1_size];
arg->W0_grad = W0_grad;
arg->W1_grad = W1_grad;
while (1)
{
sem_wait(&sem_begin[arg->id]);
if (arg->done)
break;
arg->rms = compute_gradient(arg->net, arg->inputs, arg->outputs, arg->nbSamples, arg->W0_grad, arg->W1_grad, arg->error_rate);
sem_post(&sem_end[arg->id]);
}
fprintf(stderr, "done\n");
return NULL;
}
float mlp_train_backprop(MLPTrain *net, float *inputs, float *outputs, int nbSamples, int nbEpoch, float rate)
{
int i, j;
int e;
float best_rms = 1e10;
int inDim, outDim, hiddenDim;
int *topo;
double *W0, *W1, *best_W0, *best_W1;
double *W0_old, *W1_old;
double *W0_old2, *W1_old2;
double *W0_grad, *W1_grad;
double *W0_oldgrad, *W1_oldgrad;
double *W0_rate, *W1_rate;
double *best_W0_rate, *best_W1_rate;
int W0_size, W1_size;
topo = net->topo;
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
struct GradientArg args[NB_THREADS];
pthread_t thread[NB_THREADS];
int samplePerPart = nbSamples/NB_THREADS;
int count_worse=0;
int count_retries=0;
int i, j;
int e;
float best_rms = 1e10;
int inDim, outDim, hiddenDim;
int *topo;
double *W0, *W1, *best_W0, *best_W1;
double *W0_old, *W1_old;
double *W0_old2, *W1_old2;
double *W0_grad, *W1_grad;
double *W0_oldgrad, *W1_oldgrad;
double *W0_rate, *W1_rate;
double *best_W0_rate, *best_W1_rate;
int W0_size, W1_size;
topo = net->topo;
W0_size = (topo[0]+1)*topo[1];
W1_size = (topo[1]+1)*topo[2];
struct GradientArg args[NB_THREADS];
pthread_t thread[NB_THREADS];
int samplePerPart = nbSamples/NB_THREADS;
int count_worse=0;
int count_retries=0;
topo = net->topo;
inDim = net->topo[0];
hiddenDim = net->topo[1];
outDim = net->topo[2];
W0 = net->weights[0];
W1 = net->weights[1];
best_W0 = net->best_weights[0];
best_W1 = net->best_weights[1];
W0_old = malloc(W0_size*sizeof(double));
W1_old = malloc(W1_size*sizeof(double));
W0_old2 = malloc(W0_size*sizeof(double));
W1_old2 = malloc(W1_size*sizeof(double));
W0_grad = malloc(W0_size*sizeof(double));
W1_grad = malloc(W1_size*sizeof(double));
W0_oldgrad = malloc(W0_size*sizeof(double));
W1_oldgrad = malloc(W1_size*sizeof(double));
W0_rate = malloc(W0_size*sizeof(double));
W1_rate = malloc(W1_size*sizeof(double));
best_W0_rate = malloc(W0_size*sizeof(double));
best_W1_rate = malloc(W1_size*sizeof(double));
memcpy(W0_old, W0, W0_size*sizeof(double));
memcpy(W0_old2, W0, W0_size*sizeof(double));
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W0_oldgrad, 0, W0_size*sizeof(double));
memcpy(W1_old, W1, W1_size*sizeof(double));
memcpy(W1_old2, W1, W1_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
memset(W1_oldgrad, 0, W1_size*sizeof(double));
rate /= nbSamples;
for (i=0;i<hiddenDim;i++)
for (j=0;j<inDim+1;j++)
W0_rate[i*(inDim+1)+j] = rate*net->in_rate[j];
for (i=0;i<W1_size;i++)
W1_rate[i] = rate;
for (i=0;i<NB_THREADS;i++)
{
args[i].net = net;
args[i].inputs = inputs+i*samplePerPart*inDim;
args[i].outputs = outputs+i*samplePerPart*outDim;
args[i].nbSamples = samplePerPart;
args[i].id = i;
args[i].done = 0;
sem_init(&sem_begin[i], 0, 0);
sem_init(&sem_end[i], 0, 0);
pthread_create(&thread[i], NULL, gradient_thread_process, &args[i]);
}
for (e=0;e<nbEpoch;e++)
{
double rms=0;
double error_rate[2] = {0,0};
for (i=0;i<NB_THREADS;i++)
{
sem_post(&sem_begin[i]);
}
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
for (i=0;i<NB_THREADS;i++)
{
sem_wait(&sem_end[i]);
rms += args[i].rms;
error_rate[0] += args[i].error_rate[0];
topo = net->topo;
inDim = net->topo[0];
hiddenDim = net->topo[1];
outDim = net->topo[2];
W0 = net->weights[0];
W1 = net->weights[1];
best_W0 = net->best_weights[0];
best_W1 = net->best_weights[1];
W0_old = malloc(W0_size*sizeof(double));
W1_old = malloc(W1_size*sizeof(double));
W0_old2 = malloc(W0_size*sizeof(double));
W1_old2 = malloc(W1_size*sizeof(double));
W0_grad = malloc(W0_size*sizeof(double));
W1_grad = malloc(W1_size*sizeof(double));
W0_oldgrad = malloc(W0_size*sizeof(double));
W1_oldgrad = malloc(W1_size*sizeof(double));
W0_rate = malloc(W0_size*sizeof(double));
W1_rate = malloc(W1_size*sizeof(double));
best_W0_rate = malloc(W0_size*sizeof(double));
best_W1_rate = malloc(W1_size*sizeof(double));
memcpy(W0_old, W0, W0_size*sizeof(double));
memcpy(W0_old2, W0, W0_size*sizeof(double));
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W0_oldgrad, 0, W0_size*sizeof(double));
memcpy(W1_old, W1, W1_size*sizeof(double));
memcpy(W1_old2, W1, W1_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
memset(W1_oldgrad, 0, W1_size*sizeof(double));
rate /= nbSamples;
for (i=0;i<hiddenDim;i++)
for (j=0;j<inDim+1;j++)
W0_rate[i*(inDim+1)+j] = rate*net->in_rate[j];
for (i=0;i<W1_size;i++)
W1_rate[i] = rate;
for (i=0;i<NB_THREADS;i++)
{
args[i].net = net;
args[i].inputs = inputs+i*samplePerPart*inDim;
args[i].outputs = outputs+i*samplePerPart*outDim;
args[i].nbSamples = samplePerPart;
args[i].id = i;
args[i].done = 0;
sem_init(&sem_begin[i], 0, 0);
sem_init(&sem_end[i], 0, 0);
pthread_create(&thread[i], NULL, gradient_thread_process, &args[i]);
}
for (e=0;e<nbEpoch;e++)
{
double rms=0;
double error_rate[2] = {0,0};
for (i=0;i<NB_THREADS;i++)
{
sem_post(&sem_begin[i]);
}
memset(W0_grad, 0, W0_size*sizeof(double));
memset(W1_grad, 0, W1_size*sizeof(double));
for (i=0;i<NB_THREADS;i++)
{
sem_wait(&sem_end[i]);
rms += args[i].rms;
error_rate[0] += args[i].error_rate[0];
error_rate[1] += args[i].error_rate[1];
for (j=0;j<W0_size;j++)
W0_grad[j] += args[i].W0_grad[j];
for (j=0;j<W1_size;j++)
W1_grad[j] += args[i].W1_grad[j];
}
for (j=0;j<W0_size;j++)
W0_grad[j] += args[i].W0_grad[j];
for (j=0;j<W1_size;j++)
W1_grad[j] += args[i].W1_grad[j];
}
float mean_rate = 0, min_rate = 1e10;
rms = (rms/(outDim*nbSamples));
error_rate[0] = (error_rate[0]/(nbSamples));
float mean_rate = 0, min_rate = 1e10;
rms = (rms/(outDim*nbSamples));
error_rate[0] = (error_rate[0]/(nbSamples));
error_rate[1] = (error_rate[1]/(nbSamples));
fprintf (stderr, "%f %f (%f %f) ", error_rate[0], error_rate[1], rms, best_rms);
if (rms < best_rms)
{
best_rms = rms;
for (i=0;i<W0_size;i++)
{
best_W0[i] = W0[i];
best_W0_rate[i] = W0_rate[i];
}
for (i=0;i<W1_size;i++)
{
best_W1[i] = W1[i];
best_W1_rate[i] = W1_rate[i];
}
count_worse=0;
count_retries=0;
} else {
count_worse++;
if (count_worse>30)
{
count_retries++;
count_worse=0;
for (i=0;i<W0_size;i++)
{
W0[i] = best_W0[i];
best_W0_rate[i] *= .7;
if (best_W0_rate[i]<1e-15) best_W0_rate[i]=1e-15;
W0_rate[i] = best_W0_rate[i];
W0_grad[i] = 0;
}
for (i=0;i<W1_size;i++)
{
W1[i] = best_W1[i];
best_W1_rate[i] *= .8;
if (best_W1_rate[i]<1e-15) best_W1_rate[i]=1e-15;
W1_rate[i] = best_W1_rate[i];
W1_grad[i] = 0;
}
}
}
if (count_retries>10)
break;
for (i=0;i<W0_size;i++)
{
if (W0_oldgrad[i]*W0_grad[i] > 0)
W0_rate[i] *= 1.01;
else if (W0_oldgrad[i]*W0_grad[i] < 0)
W0_rate[i] *= .9;
mean_rate += W0_rate[i];
if (W0_rate[i] < min_rate)
min_rate = W0_rate[i];
if (W0_rate[i] < 1e-15)
W0_rate[i] = 1e-15;
/*if (W0_rate[i] > .01)
W0_rate[i] = .01;*/
W0_oldgrad[i] = W0_grad[i];
W0_old2[i] = W0_old[i];
W0_old[i] = W0[i];
W0[i] += W0_grad[i]*W0_rate[i];
}
for (i=0;i<W1_size;i++)
{
if (W1_oldgrad[i]*W1_grad[i] > 0)
W1_rate[i] *= 1.01;
else if (W1_oldgrad[i]*W1_grad[i] < 0)
W1_rate[i] *= .9;
mean_rate += W1_rate[i];
if (W1_rate[i] < min_rate)
min_rate = W1_rate[i];
if (W1_rate[i] < 1e-15)
W1_rate[i] = 1e-15;
W1_oldgrad[i] = W1_grad[i];
W1_old2[i] = W1_old[i];
W1_old[i] = W1[i];
W1[i] += W1_grad[i]*W1_rate[i];
}
mean_rate /= (topo[0]+1)*topo[1] + (topo[1]+1)*topo[2];
fprintf (stderr, "%g %d", mean_rate, e);
if (count_retries)
fprintf(stderr, " %d", count_retries);
fprintf(stderr, "\n");
if (stopped)
break;
}
for (i=0;i<NB_THREADS;i++)
{
args[i].done = 1;
sem_post(&sem_begin[i]);
pthread_join(thread[i], NULL);
fprintf (stderr, "joined %d\n", i);
}
free(W0_old);
free(W1_old);
free(W0_grad);
free(W1_grad);
free(W0_rate);
free(W1_rate);
return best_rms;
fprintf (stderr, "%f %f (%f %f) ", error_rate[0], error_rate[1], rms, best_rms);
if (rms < best_rms)
{
best_rms = rms;
for (i=0;i<W0_size;i++)
{
best_W0[i] = W0[i];
best_W0_rate[i] = W0_rate[i];
}
for (i=0;i<W1_size;i++)
{
best_W1[i] = W1[i];
best_W1_rate[i] = W1_rate[i];
}
count_worse=0;
count_retries=0;
} else {
count_worse++;
if (count_worse>30)
{
count_retries++;
count_worse=0;
for (i=0;i<W0_size;i++)
{
W0[i] = best_W0[i];
best_W0_rate[i] *= .7;
if (best_W0_rate[i]<1e-15) best_W0_rate[i]=1e-15;
W0_rate[i] = best_W0_rate[i];
W0_grad[i] = 0;
}
for (i=0;i<W1_size;i++)
{
W1[i] = best_W1[i];
best_W1_rate[i] *= .8;
if (best_W1_rate[i]<1e-15) best_W1_rate[i]=1e-15;
W1_rate[i] = best_W1_rate[i];
W1_grad[i] = 0;
}
}
}
if (count_retries>10)
break;
for (i=0;i<W0_size;i++)
{
if (W0_oldgrad[i]*W0_grad[i] > 0)
W0_rate[i] *= 1.01;
else if (W0_oldgrad[i]*W0_grad[i] < 0)
W0_rate[i] *= .9;
mean_rate += W0_rate[i];
if (W0_rate[i] < min_rate)
min_rate = W0_rate[i];
if (W0_rate[i] < 1e-15)
W0_rate[i] = 1e-15;
/*if (W0_rate[i] > .01)
W0_rate[i] = .01;*/
W0_oldgrad[i] = W0_grad[i];
W0_old2[i] = W0_old[i];
W0_old[i] = W0[i];
W0[i] += W0_grad[i]*W0_rate[i];
}
for (i=0;i<W1_size;i++)
{
if (W1_oldgrad[i]*W1_grad[i] > 0)
W1_rate[i] *= 1.01;
else if (W1_oldgrad[i]*W1_grad[i] < 0)
W1_rate[i] *= .9;
mean_rate += W1_rate[i];
if (W1_rate[i] < min_rate)
min_rate = W1_rate[i];
if (W1_rate[i] < 1e-15)
W1_rate[i] = 1e-15;
W1_oldgrad[i] = W1_grad[i];
W1_old2[i] = W1_old[i];
W1_old[i] = W1[i];
W1[i] += W1_grad[i]*W1_rate[i];
}
mean_rate /= (topo[0]+1)*topo[1] + (topo[1]+1)*topo[2];
fprintf (stderr, "%g %d", mean_rate, e);
if (count_retries)
fprintf(stderr, " %d", count_retries);
fprintf(stderr, "\n");
if (stopped)
break;
}
for (i=0;i<NB_THREADS;i++)
{
args[i].done = 1;
sem_post(&sem_begin[i]);
pthread_join(thread[i], NULL);
fprintf (stderr, "joined %d\n", i);
}
free(W0_old);
free(W1_old);
free(W0_grad);
free(W1_grad);
free(W0_rate);
free(W1_rate);
return best_rms;
}
int main(int argc, char **argv)
{
int i, j;
int nbInputs;
int nbOutputs;
int nbHidden;
int nbSamples;
int nbEpoch;
int nbRealInputs;
unsigned int seed;
int ret;
float rms;
float *inputs;
float *outputs;
if (argc!=6)
{
fprintf (stderr, "usage: mlp_train <inputs> <hidden> <outputs> <nb samples> <nb epoch>\n");
return 1;
}
nbInputs = atoi(argv[1]);
nbHidden = atoi(argv[2]);
nbOutputs = atoi(argv[3]);
nbSamples = atoi(argv[4]);
nbEpoch = atoi(argv[5]);
nbRealInputs = nbInputs;
inputs = malloc(nbInputs*nbSamples*sizeof(*inputs));
outputs = malloc(nbOutputs*nbSamples*sizeof(*outputs));
seed = time(NULL);
/*seed = 1361480659;*/
fprintf (stderr, "Seed is %u\n", seed);
srand(seed);
build_tansig_table();
signal(SIGTERM, handler);
signal(SIGINT, handler);
signal(SIGHUP, handler);
for (i=0;i<nbSamples;i++)
{
for (j=0;j<nbRealInputs;j++)
ret = scanf(" %f", &inputs[i*nbInputs+j]);
for (j=0;j<nbOutputs;j++)
ret = scanf(" %f", &outputs[i*nbOutputs+j]);
if (feof(stdin))
{
nbSamples = i;
break;
}
}
int topo[3] = {nbInputs, nbHidden, nbOutputs};
MLPTrain *net;
int i, j;
int nbInputs;
int nbOutputs;
int nbHidden;
int nbSamples;
int nbEpoch;
int nbRealInputs;
unsigned int seed;
int ret;
float rms;
float *inputs;
float *outputs;
if (argc!=6)
{
fprintf (stderr, "usage: mlp_train <inputs> <hidden> <outputs> <nb samples> <nb epoch>\n");
return 1;
}
nbInputs = atoi(argv[1]);
nbHidden = atoi(argv[2]);
nbOutputs = atoi(argv[3]);
nbSamples = atoi(argv[4]);
nbEpoch = atoi(argv[5]);
nbRealInputs = nbInputs;
inputs = malloc(nbInputs*nbSamples*sizeof(*inputs));
outputs = malloc(nbOutputs*nbSamples*sizeof(*outputs));
fprintf (stderr, "Got %d samples\n", nbSamples);
net = mlp_init(topo, 3, inputs, outputs, nbSamples);
rms = mlp_train_backprop(net, inputs, outputs, nbSamples, nbEpoch, 1);
printf ("#include \"mlp.h\"\n\n");
printf ("/* RMS error was %f, seed was %u */\n\n", rms, seed);
printf ("static const float weights[%d] = {\n", (topo[0]+1)*topo[1] + (topo[1]+1)*topo[2]);
printf ("\n/* hidden layer */\n");
for (i=0;i<(topo[0]+1)*topo[1];i++)
{
printf ("%gf, ", net->weights[0][i]);
if (i%5==4)
printf("\n");
}
printf ("\n/* output layer */\n");
for (i=0;i<(topo[1]+1)*topo[2];i++)
{
printf ("%g, ", net->weights[1][i]);
if (i%5==4)
printf("\n");
}
printf ("};\n\n");
printf ("static const int topo[3] = {%d, %d, %d};\n\n", topo[0], topo[1], topo[2]);
printf ("const MLP net = {\n");
printf ("\t3,\n");
printf ("\ttopo,\n");
printf ("\tweights\n};\n");
return 0;
seed = time(NULL);
/*seed = 1361480659;*/
fprintf (stderr, "Seed is %u\n", seed);
srand(seed);
build_tansig_table();
signal(SIGTERM, handler);
signal(SIGINT, handler);
signal(SIGHUP, handler);
for (i=0;i<nbSamples;i++)
{
for (j=0;j<nbRealInputs;j++)
ret = scanf(" %f", &inputs[i*nbInputs+j]);
for (j=0;j<nbOutputs;j++)
ret = scanf(" %f", &outputs[i*nbOutputs+j]);
if (feof(stdin))
{
nbSamples = i;
break;
}
}
int topo[3] = {nbInputs, nbHidden, nbOutputs};
MLPTrain *net;
fprintf (stderr, "Got %d samples\n", nbSamples);
net = mlp_init(topo, 3, inputs, outputs, nbSamples);
rms = mlp_train_backprop(net, inputs, outputs, nbSamples, nbEpoch, 1);
printf ("#include \"mlp.h\"\n\n");
printf ("/* RMS error was %f, seed was %u */\n\n", rms, seed);
printf ("static const float weights[%d] = {\n", (topo[0]+1)*topo[1] + (topo[1]+1)*topo[2]);
printf ("\n/* hidden layer */\n");
for (i=0;i<(topo[0]+1)*topo[1];i++)
{
printf ("%gf, ", net->weights[0][i]);
if (i%5==4)
printf("\n");
}
printf ("\n/* output layer */\n");
for (i=0;i<(topo[1]+1)*topo[2];i++)
{
printf ("%g, ", net->weights[1][i]);
if (i%5==4)
printf("\n");
}
printf ("};\n\n");
printf ("static const int topo[3] = {%d, %d, %d};\n\n", topo[0], topo[1], topo[2]);
printf ("const MLP net = {\n");
printf ("\t3,\n");
printf ("\ttopo,\n");
printf ("\tweights\n};\n");
return 0;
}

44
src/mlp_train.h
View File

@ -32,31 +32,31 @@
#include <stdlib.h>
double tansig_table[501];
static inline double tansig_double(double x)
static inline double tansig_double(double x)
{
return 2./(1.+exp(-2.*x)) - 1.;
return 2./(1.+exp(-2.*x)) - 1.;
}
static inline void build_tansig_table()
{
int i;
for (i=0;i<501;i++)
tansig_table[i] = tansig_double(.04*(i-250));
int i;
for (i=0;i<501;i++)
tansig_table[i] = tansig_double(.04*(i-250));
}
static inline double tansig_approx(double x)
{
int i;
double y, dy;
if (x>=10)
return 1;
if (x<=-10)
return -1;
i = lrint(25*x);
x -= .04*i;
y = tansig_table[250+i];
dy = 1-y*y;
y = y + x*dy*(1 - y*x);
return y;
int i;
double y, dy;
if (x>=10)
return 1;
if (x<=-10)
return -1;
i = lrint(25*x);
x -= .04*i;
y = tansig_table[250+i];
dy = 1-y*y;
y = y + x*dy*(1 - y*x);
return y;
}
inline float randn(float sd)
@ -75,11 +75,11 @@ inline float randn(float sd)
typedef struct {
int layers;
int *topo;
double **weights;
double **best_weights;
double *in_rate;
int layers;
int *topo;
double **weights;
double **best_weights;
double *in_rate;
} MLPTrain;

4
src/opus_encoder.c
View File

@ -232,7 +232,7 @@ int opus_encoder_init(OpusEncoder* st, opus_int32 Fs, int channels, int applicat
st->lsb_depth = 24;
st->variable_duration = OPUS_FRAMESIZE_ARG;
/* Delay compensation of 4 ms (2.5 ms for SILK's extra look-ahead
/* Delay compensation of 4 ms (2.5 ms for SILK's extra look-ahead
+ 1.5 ms for SILK resamplers and stereo prediction) */
st->delay_compensation = st->Fs/250;
@ -2125,7 +2125,7 @@ int opus_encoder_ctl(OpusEncoder *st, int request, ...)
case OPUS_SET_MAX_BANDWIDTH_REQUEST:
{
opus_int32 value = va_arg(ap, opus_int32);
if (value < OPUS_BANDWIDTH_NARROWBAND || value > OPUS_BANDWIDTH_FULLBAND)
if (value < OPUS_BANDWIDTH_NARROWBAND || value > OPUS_BANDWIDTH_FULLBAND)
{
goto bad_arg;
}