blob: 9ee47d64d2181bb88de2867e587e945991b2b854 [file] [log] [blame]
#!/usr/local/bin/perl
use Inline C;
use Inline C => Config => CLEAN_AFTER_BUILD => 0, BUILD_NOISY => 1, ccflags => $Config{ccflags}." -I/vol/work/kupietz/Work2/kl/trunk/CollocatorDB -I, -L. -Wall -O4", libs => "-shared -lpthread -lcollocatordb -lrt -lsnappy -lz -lbz2 -llz4 -lzstd -lrocksdb -lgomp";
#use Inline C => Config => BUILD_NOISY => 1, CFLAGS => $Config{cflags}." -O4 -mtune k9";
#use Inline C => Config => CLEAN_AFTER_BUILD => 0, ccflags => $Config{ccflags}." -Ofast -march k8 -mtune k8 ";
use Mojolicious::Lite;
use Mojo::JSON qw(decode_json encode_json to_json);
use base 'Mojolicious::Plugin';
use Encode qw(decode encode);
use Getopt::Std;
use Mojo::Server::Daemon;
use Cwd;
app->static->paths->[0] = getcwd;
plugin 'Log::Access';
plugin "RequestBase";
our $opt_i = 0; # latin1-input?
our $opt_l = undef;
our $opt_p = 5676;
our $opt_m;
our $opt_M;
our $opt_n = '';
our $opt_d;
our $opt_D;
our $opt_G;
my %marked;
my $title="";
my $training_args="";
my $mergedEnd=0;
my %cache;
my %cccache; # classic collocator cache
my %spcache; # similar profile cache
getopts('d:D:Gil:p:m:n:M:');
if($opt_M) {
open my $handle, '<:encoding(UTF-8)', $opt_M
or die "Can't open '$opt_M' for reading: $!";
while(<$handle>) {
foreach my $mw (split /\s+/) {
$marked{$mw}=1
}
}
close($handle);
}
# -cbow 1 -size 200 -window 8 -negative 25 -hs 0 -sample 1e-4 -threads 40 -binary 1 -iter 15
if(!$ARGV[0]) {
init_net("vectors15.bin", $opt_n, ($opt_i? 1 : 0));
} else {
init_net($ARGV[0], $opt_n, ($opt_i? 1 : 0));
if(open(FILE, "$ARGV[0].args")) {
$training_args = <FILE>;
}
close(FILE);
$title = fname2corpusname($ARGV[0]);
}
my $have_sprofiles = load_sprofiles($ARGV[0]);
if($opt_m) {
$mergedEnd = mergeVectors($opt_m);
$title = "<span class=\"merged\">" . $title . "</span> vs. " . fname2corpusname($opt_m);
}
if($opt_d) { # -d: dump vecs and exit
dump_vecs($opt_d);
exit;
}
if($opt_D) { # -D: dump vecs for numpy and exit
dump_for_numpy($opt_D);
exit;
}
my $daemon = Mojo::Server::Daemon->new(
app => app,
listen => ['http://'.($opt_l ? $opt_l : '*').":$opt_p"]
);
if($opt_G) {
print "Filtering garbage\n";
filter_garbage();
}
get '*/js/*' => sub {
my $c = shift;
my $url = $c->req->url;
$url =~ s@/derekovecs@@g;
$c->app->log->info("GET: " . $url);
$c->reply->static($url);
};
get '*/css/*' => sub {
my $c = shift;
my $url = $c->req->url;
$url =~ s@/derekovecs/@/@g;
$c->app->log->info("GET: " . $url);
$c->reply->static($url);
};
sub fname2corpusname {
($_) = @_;
s@.*/@@;
s@\.en@-en@;
s@\..*@@;
return $_;
}
sub getClassicCollocatorsCached {
my ($c, $word) = @_;
my $s2 = "";
if($word > $mergedEnd) {
$word-=$mergedEnd;
}
if($opt_p >= 5000 && $opt_p < 5600) { # German non-reference
open PIPE, "GET http://compute:5673/getClassicCollocators?w=$word |" or
open PIPE, "GET http://klinux10:5673/getClassicCollocators?w=$word |";
}
if(!$cccache{$word}) {
$c->app->log->info("Getting classic collocates of $word.");
$cccache{$word} = getClassicCollocators($word);
$cccache{$word} =~ s/:(-?)(nan|inf)/:"${1}${2}"/g;
} else {
$c->app->log->info("Getting classic collocates for $word from cache.");
}
if($opt_p >= 5000 && $opt_p < 5600) { # German non-reference
while(<PIPE>) {
$s2 .= $_;
}
close(PIPE);
}
if(length($s2) > 2000) {
my $d1 = decode_json($cccache{$word});
my $d2 = decode_json($s2);
my %d2ld;
my $minLd = 14;
foreach my $i (@{$d2->{collocates}}) {
$d2ld{$i->{word}}=$i->{ld};
$minLd=$i->{ld} if($i->{ld} < $minLd);
}
foreach my $i (@{$d1->{collocates}}) {
my $w = $i->{word};
$i->{delta} = $i->{ld} - (defined $d2ld{$w} ? $d2ld{$w} : $minLd-0.1);
}
return(encode_json($d1));
} else {
my $d1 = decode_json($cccache{$word});
foreach my $i (@{$d1->{collocates}}) {
$i->{delta} = 0;
}
return(encode_json($d1));
}
}
sub getSimilarProfilesCached {
my ($c, $word) = @_;
if(!$spcache{$word}) {
$spcache{$word} = getSimilarProfiles($word);
} else {
$c->app->log->info("Getting similar profiles for $word from cache:");
}
return $spcache{$word};
}
post '/derekovecs/getVecsByRanks' => sub {
my $self = shift;
my $vec = getVecs($self->req->json);
$self->render(json => $vec);
};
any '*/getClassicCollocators' => sub {
my $self = shift;
$self->render(data => getClassicCollocatorsCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};
any '/getClassicCollocators' => sub {
my $self = shift;
$self->render(data => getClassicCollocatorsCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};
any '/getBiggestVocabDistances' => sub {
my $self = shift;
$self->render(data => getBiggestMergedDifferences(), format=>'json');
};
any '*/getBiggestVocabDistances' => sub {
my $self = shift;
$self->render(data => getBiggestMergedDifferences(), format=>'json');
};
any '*/getSimilarProfiles' => sub {
my $self = shift;
$self->render(data => getSimilarProfilesCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};
any '/getSimilarProfiles' => sub {
my $self = shift;
$self->render(data => getSimilarProfilesCached($self, $self->param("w") ? $self->param("w") : $self->req->json), format=>'json');
};
any '/getSimilarity' => sub {
my $self = shift;
my $w1 = $self->param("w1");
my $w2 = $self->param("w2");
$self->render(data => cos_similarity_as_json($w1, $w2), format=>'json');
};
any '*/getSimilarity' => sub {
my $self = shift;
my $w1 = $self->param("w1");
my $w2 = $self->param("w2");
$self->render(data => cos_similarity_as_json($w1, $w2), format=>'json');
};
get '*/img/*' => sub {
my $c = shift;
my $url = $c->req->url;
$url =~ s@/derekovecs@@g;
$c->app->log->info("GET: " . $url);
$c->reply->static($url);
};
get '/' => sub {
my $c = shift;
$c->app->log->info("get: ".$c->req->url->to_abs);
my $word=$c->param('word');
my $no_nbs=$c->param('n') || ($opt_m? 50 : 100);
my $no_iterations=$c->param('N') || 2000;
my $perplexity=$c->param('perplexity') || 20;
my $epsilon=$c->param('epsilon') || 5;
my $som=$c->param('som') || 0;
my $searchBaseVocabFirst=$c->param('sbf') || 0;
my $sort=$c->param('sort') || 0;
my $csv=$c->param('csv') || 0;
my $json=$c->param('json') || 0;
my $cutoff=$c->param('cutoff') || 500000;
my $dedupe=$c->param('dedupe') || 0;
my $nosp=$c->param('nosp') || 0;
my $res;
my @lists;
my @collocations;
if(defined($word) && $word !~ /^\s*$/) {
$c->inactivity_timeout(300);
$word =~ s/\s+/ /g;
if($opt_m && $word !~ /\|/) {
$word .= "|$word";
}
for my $w (split(' *\| *', $word)) {
if($opt_m) {
if($searchBaseVocabFirst) {
$searchBaseVocabFirst=0;
} else {
$searchBaseVocabFirst=1;
}
}
if ($cache{$w.$cutoff.$no_nbs.$sort.$dedupe,$searchBaseVocabFirst}) {
$c->app->log->info("Getting $w results from cache");
$res = $cache{$w.$cutoff.$no_nbs.$sort.$dedupe.$searchBaseVocabFirst}
} else {
$c->app->log->info('Looking for neighbours of '.$w);
if($opt_i) {
$res = get_neighbours(encode("iso-8859-1", $w), $no_nbs, $sort, $searchBaseVocabFirst, $cutoff, $dedupe, $nosp);
} else {
$res = get_neighbours($w, $no_nbs, $sort, $searchBaseVocabFirst, $cutoff, $dedupe, $nosp);
}
$cache{$w.$cutoff.$no_nbs.$sort.$dedupe} = $res;
}
push(@lists, $res->{paradigmatic});
}
}
$word =~ s/ *\| */ | /g;
if($json) {
return $c->render(json => {word => $word, list => \@lists, collocators=>$res->{syntagmatic}});
} elsif($csv) {
my $csv_data="";
for (my $i=0; $i <= $no_nbs; $i++) {
$csv_data .= $res->{paradigmatic}->[$i]->{word} . ", ";
}
for (my $i=0; $i < $no_nbs; $i++) {
$csv_data .= $res->{syntagmatic}->[$i]->{word} . ", ";
}
chop $csv_data;
chop $csv_data;
$csv_data .= "\n";
return $c->render(text=>$csv_data);
} else {
my $distantWords="";
if(!defined($word) || $word !~ /^\s*$/) {
$distantWords = getBiggestMergedDifferences();
}
$c->render(template=>"index", title=>$title, word=>$word, distantWords=>$distantWords, cutoff=>$cutoff, no_nbs=>$no_nbs, no_iterations => $no_iterations, epsilon=> $epsilon, perplexity=> $perplexity, show_som=>$som, searchBaseVocabFirst=>$searchBaseVocabFirst, sort=>$sort, training_args=>$training_args, mergedEnd=> $mergedEnd, haveSProfiles=> $have_sprofiles, dedupe=> $dedupe, marked=>\%marked, lists=> \@lists, collocators=> $res->{syntagmatic});
}
};
helper(bitvec2window => sub {
my ($self, $n) = @_;
my $str = unpack("B32", pack("N", $n));
$str =~ s/^\d{22}//;
$str =~ s/^(\d{5})/$1x/;
$str =~ s/0/·/g;
$str =~ s/1/+/g;
return $str;
});
$daemon->run; # app->start;
exit;
__END__
__C__
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <malloc.h>
#include <stdlib.h> //strlen
#include <sys/mman.h>
#include <pthread.h>
#include <collocatordb.h>
#define max_size 2000
#define max_w 50
#define MAX_NEIGHBOURS 1000
#define MAX_WORDS -1
#define MAX_THREADS 100
#define MAX_CC 50
#define EXP_TABLE_SIZE 1000
#define MAX_EXP 6
#define MIN_RESP 0.50
//the thread function
void *connection_handler(void *);
typedef struct {
long long wordi;
long position;
float activation;
float average;
float cprobability; // column wise probability
float cprobability_sum;
float probability;
float activation_sum;
float max_activation;
float heat[16];
} collocator;
typedef struct {
collocator *best;
int length;
} knn;
typedef struct {
long long wordi[MAX_NEIGHBOURS];
char sep[MAX_NEIGHBOURS];
int length;
} wordlist;
typedef struct {
long cutoff;
wordlist *wl;
char *token;
int N;
long from;
unsigned long upto;
collocator *best;
float *target_sums;
float *window_sums;
} knnpars;
typedef struct {
uint32_t index;
float value;
} sparse_t;
typedef struct {
uint32_t len;
sparse_t nbr[100];
} profile_t;
float *M, *M2=0L, *syn1neg_window, *expTable;
float *window_sums;
char *vocab;
char *garbage = NULL;
COLLOCATORDB *cdb = NULL;
profile_t *sprofiles = NULL;
size_t sprofiles_qty = 0;
long long words, size, merged_end;
long long merge_words = 0;
int num_threads=20;
int latin_enc=0;
int window;
/* load collocation profiles if file exists */
int load_sprofiles(char *vecsname) {
char *basename = strdup(vecsname);
char *pos = strstr(basename, ".vecs");
if(pos)
*pos=0;
char binsprofiles_fname[256];
strcpy(binsprofiles_fname, basename);
strcat(binsprofiles_fname, ".sprofiles.bin");
FILE *fp = fopen(binsprofiles_fname, "rb");
if (fp == NULL) {
printf("Collocation profiles %s not found. No problem.\n", binsprofiles_fname);
return 0;
}
fseek(fp, 0L, SEEK_END);
size_t sz = ftell(fp);
fclose(fp);
int fd = open(binsprofiles_fname, O_RDONLY);
sprofiles = mmap(0, sz, PROT_READ, MAP_SHARED, fd, 0);
if (sprofiles == MAP_FAILED) {
close(fd);
fprintf(stderr, "Cannot mmap %s\n", binsprofiles_fname);
sprofiles = NULL;
return 0;
} else {
sprofiles_qty = sz / sizeof(profile_t);
fprintf(stderr, "Successfully mmaped %s containing similar profiles for %ld word forms.\n", binsprofiles_fname, sprofiles_qty);
}
return 1;
}
int init_net(char *file_name, char *net_name, int latin) {
FILE *f, *binvecs, *binwords;
int binwords_fd, binvecs_fd, net_fd, i;
long long a, b, c, d, cn;
float len;
double val;
char binvecs_fname[256], binwords_fname[256];
strcpy(binwords_fname, file_name);
strcat(binwords_fname, ".words");
strcpy(binvecs_fname, file_name);
strcat(binvecs_fname, ".vecs");
latin_enc = latin;
f = fopen(file_name, "rb");
if (f == NULL) {
printf("Input file %s not found\n", file_name);
return -1;
}
fscanf(f, "%lld", &words);
if(MAX_WORDS > 0 && words > MAX_WORDS) words = MAX_WORDS;
fscanf(f, "%lld", &size);
if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) < 0 || (binwords_fd = open(binwords_fname, O_RDONLY)) < 0) {
printf("Converting %s to memory mappable structures\n", file_name);
vocab = (char *)malloc((long long)words * max_w * sizeof(char));
M = (float *)malloc((long long)words * (long long)size * sizeof(float));
if (M == NULL) {
printf("Cannot allocate memory: %lld MB %lld %lld\n", (long long)words * size * sizeof(float) / 1048576, words, size);
return -1;
}
if(strstr(file_name, ".txt")) {
for (b = 0; b < words; b++) {
a = 0;
while (1) {
vocab[b * max_w + a] = fgetc(f);
if (feof(f) || (vocab[b * max_w + a] == ' ')) break;
if ((a < max_w) && (vocab[b * max_w + a] != '\n')) a++;
}
vocab[b * max_w + a] = 0;
len = 0;
for (a = 0; a < size; a++) {
fscanf(f, "%lf", &val);
M[a + b * size] = val;
len += val * val;
}
len = sqrt(len);
for (a = 0; a < size; a++) M[a + b * size] /= len;
}
} else {
for (b = 0; b < words; b++) {
a = 0;
while (1) {
vocab[b * max_w + a] = fgetc(f);
if (feof(f) || (vocab[b * max_w + a] == ' ')) break;
if ((a < max_w) && (vocab[b * max_w + a] != '\n')) a++;
}
vocab[b * max_w + a] = 0;
fread(&M[b * size], sizeof(float), size, f);
len = 0;
for (a = 0; a < size; a++) len += M[a + b * size] * M[a + b * size];
len = sqrt(len);
for (a = 0; a < size; a++) M[a + b * size] /= len;
}
}
if( (binvecs = fopen(binvecs_fname, "wb")) != NULL && (binwords = fopen(binwords_fname, "wb")) != NULL) {
fwrite(M, sizeof(float), (long long)words * (long long)size, binvecs);
fclose(binvecs);
fwrite(vocab, sizeof(char), (long long)words * max_w, binwords);
fclose(binwords);
}
}
if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) >= 0 && (binwords_fd = open(binwords_fname, O_RDONLY)) >= 0) {
M = mmap(0, sizeof(float) * (long long)words * (long long)size, PROT_READ, MAP_SHARED, binvecs_fd, 0);
vocab = mmap(0, sizeof(char) * (long long)words * max_w, PROT_READ, MAP_SHARED, binwords_fd, 0);
if (M == MAP_FAILED || vocab == MAP_FAILED) {
close(binvecs_fd);
close(binwords_fd);
fprintf(stderr, "Cannot mmap %s or %s\n", binwords_fname, binvecs_fname);
exit(-1);
}
} else {
fprintf(stderr, "Cannot open %s or %s\n", binwords_fname, binvecs_fname);
exit(-1);
}
fclose(f);
if(net_name && strlen(net_name) > 0) {
if( (net_fd = open(net_name, O_RDONLY)) >= 0) {
window = (lseek(net_fd, 0, SEEK_END) - sizeof(float) * words * size) / words / size / sizeof(float) / 2;
// lseek(net_fd, sizeof(float) * words * size, SEEK_SET);
// munmap(M, sizeof(float) * words * size);
M2 = mmap(0, sizeof(float) * words * size + sizeof(float) * 2 * window * size * words, PROT_READ, MAP_SHARED, net_fd, 0);
if (M2 == MAP_FAILED) {
close(net_fd);
fprintf(stderr, "Cannot mmap %s\n", net_name);
exit(-1);
}
syn1neg_window = M2 + words * size;
} else {
fprintf(stderr, "Cannot open %s\n", net_name);
exit(-1);
}
fprintf(stderr, "Successfully memmaped %s. Determined window size: %d\n", net_name, window);
char collocatordb_name[2048];
strcpy(collocatordb_name, net_name);
char *ext = rindex(collocatordb_name, '.');
if(ext) {
strcpy(ext, ".rocksdb");
if(access(collocatordb_name, R_OK) == 0) {
*ext = 0;
fprintf(stderr, "Opening collocator DB %s\n", collocatordb_name);
cdb = open_collocatordb(collocatordb_name);
}
}
}
expTable = (float *) malloc((EXP_TABLE_SIZE + 1) * sizeof(float));
for (i = 0; i < EXP_TABLE_SIZE; i++) {
expTable[i] = exp((i / (float) EXP_TABLE_SIZE * 2 - 1) * MAX_EXP); // Precompute the exp() table
expTable[i] = expTable[i] / (expTable[i] + 1); // Precompute f(x) = x / (x + 1)
}
window_sums = malloc(sizeof(float) * (window+1) * 2);
return 0;
}
long mergeVectors(char *file_name){
FILE *f, *binvecs, *binwords;
int binwords_fd, binvecs_fd, net_fd, i;
long long a, b, c, d, cn;
float len;
float *merge_vecs;
char *merge_vocab;
/* long long merge_words, merge_size; */
long long merge_size;
char binvecs_fname[256], binwords_fname[256];
strcpy(binwords_fname, file_name);
strcat(binwords_fname, ".words");
strcpy(binvecs_fname, file_name);
strcat(binvecs_fname, ".vecs");
f = fopen(file_name, "rb");
if (f == NULL) {
printf("Input file %s not found\n", file_name);
exit -1;
}
fscanf(f, "%lld", &merge_words);
fscanf(f, "%lld", &merge_size);
if(merge_size != size){
fprintf(stderr, "vectors must have the same length\n");
exit(-1);
}
if( (binvecs_fd = open(binvecs_fname, O_RDONLY)) >= 0 && (binwords_fd = open(binwords_fname, O_RDONLY)) >= 0) {
merge_vecs = malloc(sizeof(float) * (words + merge_words) * size);
merge_vocab = malloc(sizeof(char) * (words + merge_words) * max_w);
if (merge_vecs == NULL || merge_vocab == NULL) {
close(binvecs_fd);
close(binwords_fd);
fprintf(stderr, "Cannot reserve memory for %s or %s\n", binwords_fname, binvecs_fname);
exit(-1);
}
read(binvecs_fd, merge_vecs, merge_words * size * sizeof(float));
read(binwords_fd, merge_vocab, merge_words * max_w);
} else {
fprintf(stderr, "Cannot open %s or %s\n", binwords_fname, binvecs_fname);
exit(-1);
}
printf("Successfully reallocated memory\nMerging...\n");
fflush(stdout);
memcpy(merge_vecs + merge_words * size, M, words * size * sizeof(float));
memcpy(merge_vocab + merge_words * max_w, vocab, words * max_w);
munmap(M, words * size * sizeof(float));
munmap(vocab, words * max_w);
M = merge_vecs;
vocab = merge_vocab;
merged_end = merge_words;
words += merge_words;
fclose(f);
printf("merged_end: %lld, words: %lld\n", merged_end, words);
//printBiggestMergedDifferences();
return((long) merged_end);
}
void filter_garbage() {
long i;
unsigned char *w, previous, c;
garbage = malloc(words);
memset(garbage, 0, words);
for (i = 0; i < words; i++) {
w = vocab + i * max_w;
previous = 0;
if(strncmp("quot", w, 4) == 0) {
garbage[i]=1;
// printf("Gargabe: %s\n", vocab + i * max_w);
} else {
while((c = *w++) && !garbage[i]) {
if( ((c <= 90 && c >= 65) && (previous >= 97 && previous <= 122)) ||
(previous == '-' && (c & 32)) ||
(previous == 0xc2 && (c == 0xa4 || c == 0xb6 )) ||
(previous == 'q' && c == 'u' && *(w) == 'o' && *(w+1) == 't') || /* quot */
c == '<'
) {
garbage[i]=1;
continue;
}
previous = c;
}
}
}
return;
}
knn *simpleGetCollocators(int word, int number, long cutoff, int *result) {
knnpars *pars = calloc(sizeof(knnpars), 1);
float *target_sums;
float *window_sums = malloc(sizeof(float) * (window+1) * 2);
pars->cutoff = (cutoff? cutoff : 300000);
long a = posix_memalign((void **) &target_sums, 128, pars->cutoff * sizeof(float));
for(a = 0; a < cutoff; a++)
target_sums[a] = 0;
pars->target_sums = target_sums;
pars->window_sums = window_sums;
pars->N = (number? number : 20);
pars->from = 0;
pars->upto = window * 2 -1;
knn *syn_nbs = NULL; // = (knn*) getCollocators(pars);
free(pars);
free(window_sums);
free(target_sums);
return syn_nbs;
}
void *getCollocators(void *args) {
knnpars *pars = args;
int N = pars->N;
int cc = pars->wl->wordi[0];
knn *nbs = NULL;
long window_layer_size = size * window * 2;
long a, b, c, d, e, window_offset, target, max_target=0, maxmax_target;
float f, max_f, maxmax_f;
float *target_sums=NULL, worstbest, wpos_sum;
collocator *best;
if(M2 == NULL || cc == -1)
return NULL;
a = posix_memalign((void **) &target_sums, 128, pars->cutoff * sizeof(float));
memset(target_sums, 0, pars->cutoff * sizeof(float));
best = malloc((N>200?N:200) * sizeof(collocator));
memset(best, 0, (N>200?N:200) * sizeof(collocator));
worstbest = MIN_RESP;
for (b = 0; b < pars->cutoff; b++)
target_sums[b]=0;
for (b = 0; b < N; b++) {
best[b].wordi = -1;
best[b].probability = 1;
best[b].activation = worstbest;
}
d = cc;
maxmax_f = -1;
maxmax_target = 0;
for (a = pars->from; a < pars->upto; a++) {
if(a >= window)
a++;
wpos_sum = 0;
printf("window pos: %ld\n", a);
if (a != window) {
max_f = -1;
window_offset = a * size;
if (a > window)
window_offset -= size;
for(target = 0; target < pars->cutoff; target ++) {
if(garbage && garbage[target]) continue;
if(target == d)
continue;
f = 0;
for (c = 0; c < size; c++)
f += M2[d* size + c] * syn1neg_window[target * window_layer_size + window_offset + c];
if (f < -MAX_EXP)
continue;
else if (f > MAX_EXP)
continue;
else
f = expTable[(int) ((f + MAX_EXP) * (EXP_TABLE_SIZE / MAX_EXP / 2))];
wpos_sum += f;
target_sums[target] += f;
if(f > worstbest) {
for (b = 0; b < N; b++) {
if (f > best[b].activation) {
memmove(best + b + 1, best + b, (N - b -1) * sizeof(collocator));
best[b].activation = f;
best[b].wordi = target;
best[b].position = window-a;
break;
}
}
if(b == N - 1)
worstbest = best[N-1].activation;
}
}
printf("%d %.2f\n", max_target, max_f);
printf("%s (%.2f) ", &vocab[max_target * max_w], max_f);
if(max_f > maxmax_f) {
maxmax_f = max_f;
maxmax_target = max_target;
}
for (b = 0; b < N; b++)
if(best[b].position == window-a)
best[b].cprobability = best[b].activation / wpos_sum;
} else {
printf("\x1b[1m%s\x1b[0m ", &vocab[d*max_w]);
}
pars->window_sums[a] = wpos_sum;
}
for (b = 0; b < pars->cutoff; b++)
pars->target_sums[b] += target_sums[b]; //(target_sums[b] / wpos_sum ) / (window * 2);
printf("Target-Summe von 0: %f\n", pars->target_sums[150298]);
free(target_sums);
for(b=0; b<N && best[b].wordi >= 0; b++);; // THIS LOOP IS NEEDED (b...)
// printf("%d: best syn: %s %.2f %.5f\n", b, &vocab[best[b].wordi*max_w], best[b].activation, best[b].probability);
// printf("\n");
nbs = malloc(sizeof(knn));
nbs->best = best;
nbs->length = b-1;
pthread_exit(nbs);
}
AV *getVecs(AV *array) {
int i, b;
AV *result = newAV();
for (i=0; i<=av_len(array); i++) {
SV** elem = av_fetch(array, i, 0);
if (elem != NULL) {
long j = (long) SvNV(*elem);
AV *vector = newAV();
for (b = 0; b < size; b++) {
av_push(vector, newSVnv(M[b + j * size]));
}
av_push(result, newRV_noinc(vector));
}
}
return result;
}
char *getSimilarProfiles(long node) {
int i;
char buffer[120000];
char pair_buffer[2048];
buffer[0]='[';
buffer[1]=0;
if(node >= sprofiles_qty) {
printf("Not available in precomputed profile\n");
return(strdup("[{\"w\":\"not available\", \"v\":0}]\n"));
}
printf("******* %s ******\n", &vocab[max_w * node]);
for(i=0; i < 100 && i < sprofiles[node].len; i++) {
sprintf(pair_buffer, "{\"w\":\"%s\", \"v\":%f},", &vocab[max_w * (sprofiles[node].nbr[i].index)], sprofiles[node].nbr[i].value);
strcat(buffer, pair_buffer);
}
buffer[strlen(buffer)-1]=']';
strcat(buffer, "\n");
printf(buffer);
return(strdup(buffer));
}
char *getClassicCollocators(long node) {
char *res = (cdb? strdup(get_collocators_as_json(cdb, node)) : "[]");
return res;
}
wordlist *getTargetWords(char *st1, int search_backw) {
wordlist *wl = malloc(sizeof(wordlist));
char st[100][max_size], sep[100];
long a, b=0, c=0, cn=0;
int unmerged;
while (1) {
st[cn][b] = st1[c];
b++;
c++;
st[cn][b] = 0;
if (st1[c] == 0) break;
if (st1[c] == ' ' || st1[c] == '-') {
sep[cn++] = st1[c];
b = 0;
c++;
}
}
cn++;
for (a = 0; a < cn; a++) {
if (search_backw) {
for (b = words - 1; b >= (merge_words? merge_words : 0) && strcmp(&vocab[b * max_w], st[a]) !=0; b--);
} else {
for (b = 0; b < (merge_words? merge_words : words) && strcmp(&vocab[b * max_w], st[a]) != 0; b++);
}
if (b == words) b = -1;
wl->wordi[a] = b;
if (b == -1) {
fprintf(stderr, "Out of dictionary word!\n");
cn--;
} else {
fprintf(stderr, "Word: \"%s\" Position in vocabulary: %lld\n", &vocab[wl->wordi[a]*max_w], wl->wordi[a]);
}
}
wl->length=cn;
return(wl);
}
float get_distance(long b, long c) {
long a;
float dist = 0;
for (a = 0; a < size; a++) dist += M[a + c * size] * M[a + b * size];
return dist;
}
char *getBiggestMergedDifferences() {
static char *result = NULL;
float dist, len, vec[max_size];
long long a, b, c, d, cn, *bi;
char ch;
knn *nbs = NULL;
int N = 1000;
if(merged_end == 0)
result = "[]";
if(result != NULL)
return result;
printf("Looking for biggest distances between main and merged vectors ...\n");
collocator *best;
best = malloc(N * sizeof(collocator));
memset(best, 0, N * sizeof(collocator));
float worstbest=1000000;
for (a = 0; a < N; a++) best[a].activation = worstbest;
for (c = 0; c < 500000; c++) {
if(garbage && garbage[c]) continue;
a = 0;
dist = 0;
for (a = 0; a < size; a++) dist += M[a + c * size] * M[a + (c+merged_end) * size];
if(dist < worstbest) {
for (a = 0; a < N; a++) {
if (dist < best[a].activation) {
memmove(best + a + 1, best + a, (N - a -1) * sizeof(collocator));
best[a].activation = dist;
best[a].wordi = c;
break;
}
}
worstbest = best[N-1].activation;
}
}
result = malloc(N*max_w);
char *p = result;
*p++ = '['; *p = 0;
for (a = 0; a < N; a++) {
p += sprintf(p, "{\"rank\":%d,\"word\":\"%s\",\"dist\":%.3f},", a, &vocab[best[a].wordi * max_w], 1-best[a].activation);
}
*--p = ']';
return(result);
}
float cos_similarity(long b, long c) {
float dist=0;
long a;
for (a = 0; a < size; a++) dist += M[b * size + a] * M[c * size + a];
return dist;
}
char *cos_similarity_as_json(char *w1, char *w2) {
wordlist *a, *b;
float res;
a = getTargetWords(w1, 0);
b = getTargetWords(w2, 0);
if (a == NULL || b==NULL || a->length != 1 || b->length != 1)
res = -1;
else
res = cos_similarity(a->wordi[0], b->wordi[0]);
fprintf(stderr, "a: %lld b: %lld res:%f\n", a->wordi[0], b->wordi[0], res);
char *json = malloc(16);
sprintf(json, "%.5f", res);
return json;
}
void *_get_neighbours(void *arg) {
knnpars *pars = arg;
char *st1 = pars->token;
int N = pars->N;
long from = pars -> from;
unsigned long upto = pars -> upto;
char file_name[max_size], st[100][max_size], *sep;
float dist, len, vec[max_size];
long long a, b, c, d, cn, *bi;
char ch;
knn *nbs = NULL;
wordlist *wl = pars->wl;
collocator *best = pars->best;
float worstbest=-1;
for (a = 0; a < N; a++) best[a].activation = 0;
a = 0;
bi = wl->wordi;
cn = wl->length;
sep = wl->sep;
b = bi[0];
c = 0;
if (b == -1) {
N = 0;
goto end;
}
for (a = 0; a < size; a++) vec[a] = 0;
for (b = 0; b < cn; b++) {
if (bi[b] == -1) continue;
if(b>0 && sep[b-1] == '-')
for (a = 0; a < size; a++) vec[a] -= M[a + bi[b] * size];
else
for (a = 0; a < size; a++) vec[a] += M[a + bi[b] * size];
}
len = 0;
for (a = 0; a < size; a++) len += vec[a] * vec[a];
len = sqrt(len);
for (a = 0; a < size; a++) vec[a] /= len;
for (a = 0; a < N; a++) best[a].activation = -1;
for (c = from; c < upto; c++) {
if(garbage && garbage[c]) continue;
a = 0;
// do not skip taget word
// for (b = 0; b < cn; b++) if (bi[b] == c) a = 1;
// if (a == 1) continue;
dist = 0;
for (a = 0; a < size; a++) dist += vec[a] * M[a + c * size];
if(dist > worstbest) {
for (a = 0; a < N; a++) {
if (dist > best[a].activation) {
memmove(best + a + 1, best + a, (N - a -1) * sizeof(collocator));
best[a].activation = dist;
best[a].wordi = c;
break;
}
}
worstbest = best[N-1].activation;
}
}
end:
pthread_exit(nbs);
}
int cmp_activation (const void * a, const void * b) {
float fb = ((collocator *)a)->activation;
float fa = ((collocator *)b)->activation;
return (fa > fb) - (fa < fb);
}
int cmp_probability (const void * a, const void * b) {
float fb = ((collocator *)a)->probability;
float fa = ((collocator *)b)->probability;
return (fa > fb) - (fa < fb);
}
SV *get_neighbours(char *st1, int N, int sort_by, int search_backw, long cutoff, int dedupe, int no_similar_profiles) {
HV *result = newHV();
float *target_sums=NULL, vec[max_size];
long long old_words;
long a, b, c, d, slice;
knn *para_nbs[MAX_THREADS];
knn *syn_nbs[MAX_THREADS];
knnpars pars[MAX_THREADS];
pthread_t *pt = (pthread_t *)malloc((num_threads+1) * sizeof(pthread_t));
wordlist *wl;
int syn_threads = (M2? window * 2 : 0);
int para_threads = (no_similar_profiles? 0 : num_threads - syn_threads);
collocator *best = NULL;
posix_memalign((void **) &best, 128, 10 * (N>=200? N : 200) * sizeof(collocator));
memset(best, 0, (N>=200? N : 200) * sizeof(collocator));
if(N>MAX_NEIGHBOURS) N=MAX_NEIGHBOURS;
if(cutoff < 1 || cutoff > words)
cutoff=words;
wl = getTargetWords(st1, search_backw);
if(wl == NULL || wl->length < 1)
goto end;
old_words = cutoff;
slice = cutoff / para_threads;
a = posix_memalign((void **) &target_sums, 128, cutoff * sizeof(float));
memset(target_sums, 0, cutoff * sizeof(float));
printf("Starting %d threads\n", para_threads);
fflush(stdout);
for(a=0; a < para_threads; a++) {
pars[a].cutoff = cutoff;
pars[a].token = st1;
pars[a].wl = wl;
pars[a].N = N;
pars[a].best = &best[N*a];
if(merge_words == 0 || search_backw == 0) {
pars[a].from = a*slice;
pars[a].upto = ((a+1)*slice > cutoff? cutoff : (a+1) * slice);
} else {
pars[a].from = merge_words + a * slice;
pars[a].upto = merge_words + ((a+1)*slice > cutoff? cutoff : (a+1) * slice);
}
printf("From: %ld, Upto: %ld\n", pars[a].from, pars[a].upto);
pthread_create(&pt[a], NULL, _get_neighbours, (void *) &pars[a]);
}
if(M2) {
for(a=0; a < syn_threads; a++) {
pars[a + para_threads].cutoff = cutoff;
pars[a + para_threads].target_sums = target_sums;
pars[a + para_threads].window_sums = window_sums;
pars[a + para_threads].wl = wl;
pars[a + para_threads].N = N;
pars[a + para_threads].from = a;
pars[a + para_threads].upto = a+1;
pthread_create(&pt[a + para_threads], NULL, getCollocators, (void *) &pars[a + para_threads]);
}
}
printf("Waiting for para threads to join\n");
fflush(stdout);
for (a = 0; a < para_threads; a++) pthread_join(pt[a], (void *) &para_nbs[a]);
printf("Para threads joint\n");
fflush(stdout);
/* if(!syn_nbs[0]) */
/* goto end; */
qsort(best, N*para_threads, sizeof(collocator), cmp_activation);
long long chosen[MAX_NEIGHBOURS];
printf("N: %ld\n", N);
AV* array = newAV();
int i, j;
int l1_words=0, l2_words=0;
for (a = 0, i = 0; i < N && a < N*para_threads; a++) {
int filtered=0;
long long c = best[a].wordi;
if ((merge_words && dedupe && i > 1) || (!merge_words && dedupe && i > 0)) {
for (j=0; j<i && !filtered; j++)
if (strcasestr(&vocab[c * max_w], &vocab[chosen[j] * max_w]) ||
strcasestr(&vocab[chosen[j] * max_w], &vocab[c * max_w])) {
printf("filtering %s %s\n", &vocab[chosen[j] * max_w], &vocab[c * max_w]);
filtered = 1;
}
if(filtered)
continue;
}
if(0 && merge_words > 0) {
if(c >= merge_words) {
if(l1_words > N / 2)
continue;
else
l1_words++;
} else {
if(l2_words > N / 2)
continue;
else
l2_words++;
}
}
// printf("%s l1:%d l2:%d i:%d a:%ld\n", &vocab[c * max_w], l1_words, l2_words, i, a);
// fflush(stdout);
HV* hash = newHV();
SV* word = newSVpvf(&vocab[c * max_w], 0);
chosen[i] = c;
if(latin_enc == 0) SvUTF8_on(word);
fflush(stdout);
hv_store(hash, "word", strlen("word"), word , 0);
hv_store(hash, "dist", strlen("dist"), newSVnv(best[a].activation), 0);
hv_store(hash, "rank", strlen("rank"), newSVuv(best[a].wordi), 0);
AV *vector = newAV();
for (b = 0; b < size; b++) {
av_push(vector, newSVnv(M[b + best[a].wordi * size]));
}
hv_store(hash, "vector", strlen("vector"), newRV_noinc((SV*)vector), 0);
av_push(array, newRV_noinc((SV*)hash));
i++;
}
hv_store(result, "paradigmatic", strlen("paradigmatic"), newRV_noinc((SV*)array), 0);
for(b=0; b < MAX_NEIGHBOURS; b++) {
best[b].wordi = -1L;
best[b].activation = 0;
best[b].probability = 0;
best[b].position = 0;
best[b].activation_sum = 0;
memset(best[b].heat, 0, sizeof(float)*16);
}
float total_activation = 0;
if (M2) {
printf("Waiting for syn threads to join\n");
fflush(stdout);
for (a = 0; a < syn_threads; a++) pthread_join(pt[a+para_threads], (void *) &syn_nbs[a]);
for (a = 0; a <= syn_threads; a++) {
if(a == window) continue;
total_activation += window_sums[a];
printf("window pos: %d, sum: %f\n", a, window_sums[a]);
}
printf("syn threads joint\n");
fflush(stdout);
for(b=0; b < syn_nbs[0]->length; b++) {
memcpy(best + b, &syn_nbs[0]->best[b], sizeof(collocator));
best[b].position = -1; // syn_nbs[0]->pos[b];
best[b].activation_sum = target_sums[syn_nbs[0]->best[b].wordi];
best[b].max_activation = 0.0;
best[b].average = 0.0;
best[b].probability = 0.0;
best[b].cprobability = syn_nbs[0]->best[b].cprobability;
memset(best[b].heat, 0, sizeof(float)*16);
}
float best_window_sum[MAX_NEIGHBOURS];
int found_index=0, i=0, j, w;
for(a=0; a < syn_threads; a++) {
for(b=0; b < syn_nbs[a]->length; b++) {
for(i=0; i < found_index; i++)
if(best[i].wordi == syn_nbs[a]->best[b].wordi)
break;
if(i >= found_index) {
best[found_index].max_activation = 0.0;
best[found_index].average = 0.0;
best[found_index].probability = 0.0;
memset(best[found_index].heat, 0, sizeof(float)*16);
best[found_index].cprobability = syn_nbs[a]->best[b].cprobability;
best[found_index].activation_sum = target_sums[syn_nbs[a]->best[b].wordi]; // syn_nbs[a]->best[b].activation_sum;
best[found_index++].wordi = syn_nbs[a]->best[b].wordi;
// printf("found: %s\n", &vocab[syn_nbs[a]->index[b] * max_w]);
}
}
}
sort_by =0; // ALWAYS AUTO-FOCUS
if(sort_by != 1 && sort_by != 2) { // sort by auto focus mean
printf("window: %d - syn_threads: %d, %d\n", window, syn_threads, (1 << syn_threads) -1);
int wpos;
int bits_set = 0;
for(i=0; i < found_index; i++) {
best[i].activation = best[i].probability = best[i].average = best[i].cprobability_sum = 0;
for(w=1; w < (1 << syn_threads); w++) { // loop through all possible windows
float word_window_sum = 0, word_window_average=0, word_cprobability_sum=0, word_activation_sum = 0, total_window_sum = 0;
bits_set = 0;
for(a=0; a < syn_threads; a++) {
if((1 << a) & w) {
wpos = (a >= window? a+1 : a);
total_window_sum += window_sums[wpos];
}
}
// printf("%d window-sum %f\n", w, total_window_sum);
for(a=0; a < syn_threads; a++) {
if((1 << a) & w) {
wpos = (a >= window? a+1 : a);
bits_set++;
for(b=0; b < syn_nbs[a]->length; b++)
if(best[i].wordi == syn_nbs[a]->best[b].wordi) {
// float acti = syn_nbs[a]->best[b].activation / total_window_sum;
// word_window_sum += syn_nbs[a]->dist[b] * syn_nbs[a]->norm[b]; // / window_sums[wpos]; // syn_nbs[a]->norm[b];
// word_window_sum += syn_nbs[a]->norm[b]; // / window_sums[wpos]; // syn_nbs[a]->norm[b];
// word_window_sum = (word_window_sum + syn_nbs[a]->norm[b]) - (word_window_sum * syn_nbs[a]->norm[b]); // syn_nbs[a]->norm[b];
word_window_sum += syn_nbs[a]->best[b].activation; // / window_sums[wpos]; // syn_nbs[a]->norm[b];
// word_window_sum += acti - (word_window_sum * acti); syn_nbs[a]->best[b].activation; // / window_sums[wpos]; // syn_nbs[a]->norm[b];
word_window_average += syn_nbs[a]->best[b].activation; // - word_window_average * syn_nbs[a]->best[b].activation; // conormalied activation sum
word_cprobability_sum += syn_nbs[a]->best[b].cprobability - word_cprobability_sum * syn_nbs[a]->best[b].cprobability; // conormalied column probability sum
word_activation_sum += syn_nbs[a]->best[b].activation;
if(syn_nbs[a]->best[b].activation > best[i].max_activation)
best[i].max_activation = syn_nbs[a]->best[b].activation;
if(syn_nbs[a]->best[b].activation > best[i].heat[wpos] )
best[i].heat[wpos] = syn_nbs[a]->best[b].activation;
}
}
}
if(bits_set) {
word_window_average /= bits_set;
// word_activation_sum /= bits_set;
// word_window_sum /= bits_set;
}
word_window_sum /= total_window_sum;
if(word_window_sum > best[i].probability) {
// best[i].position = w;
best[i].probability = word_window_sum;
}
if(word_cprobability_sum > best[i].cprobability_sum) {
best[i].position = w;
best[i].cprobability_sum = word_cprobability_sum;
}
best[i].average = word_window_average;
// best[i].activation = word_activation_sum;
}
}
qsort(best, found_index, sizeof(collocator), cmp_probability);
// for(i=0; i < found_index; i++) {
// printf("found: %s - sum: %f - window: %d\n", &vocab[best[i].wordi * max_w], best[i].activation, best[i].position);
// }
} else if(sort_by == 1) { // responsiveness any window position
int wpos;
for(i=0; i < found_index; i++) {
float word_window_sum = 0, word_activation_sum = 0, total_window_sum = 0;
for(a=0; a < syn_threads; a++) {
wpos = (a >= window? a+1 : a);
for(b=0; b < syn_nbs[a]->length; b++)
if(best[i].wordi == syn_nbs[a]->best[b].wordi) {
best[i].probability += syn_nbs[a]->best[b].probability;
if(syn_nbs[a]->best[b].activation > 0.25)
best[i].position |= 1 << wpos;
if(syn_nbs[a]->best[b].activation > best[i].activation) {
best[i].activation = syn_nbs[a]->best[b].activation;
}
}
}
}
qsort(best, found_index, sizeof(collocator), cmp_activation);
} else if(sort_by == 2) { // single window position
for(a=1; a < syn_threads; a++) {
for(b=0; b < syn_nbs[a]->length; b++) {
for(c=0; c < MAX_NEIGHBOURS; c++) {
if(syn_nbs[a]->best[b].activation > best[c].activation) {
for(d=MAX_NEIGHBOURS-1; d>c; d--) {
memmove(best + d, best + d - 1, sizeof(collocator));
}
memcpy(best + c, &syn_nbs[a]->best[b], sizeof(collocator));
best[c].position = 1 << (-syn_nbs[a]->best[b].position+window - (syn_nbs[a]->best[b].position < 0 ? 1:0));
break;
}
}
}
}
} else { // sort by mean p
for(a=1; a < syn_threads; a++) {
for(b=0; b < syn_nbs[a]->length; b++) {
for(c=0; c < MAX_NEIGHBOURS; c++) {
if(target_sums[syn_nbs[a]->best[b].wordi] > best[c].activation_sum) {
for(d=MAX_NEIGHBOURS-1; d>c; d--) {
memmove(best + d, best + d - 1, sizeof(collocator));
}
memcpy(best + c, &syn_nbs[a]->best[b], sizeof(collocator));
best[c].position = (1 << 2*window) - 1; // syn_nbs[a]->pos[b];
best[c].activation_sum = target_sums[syn_nbs[a]->best[b].wordi];
break;
}
}
}
}
}
array = newAV();
for (a = 0, i=0; a < MAX_NEIGHBOURS && best[a].wordi >= 0; a++) {
long long c = best[a].wordi;
/*
if (dedupe) {
int filtered=0;
for (j=0; j<i; j++)
if (strcasestr(&vocab[c * max_w], chosen[j]) ||
strcasestr(chosen[j], &vocab[c * max_w])) {
printf("filtering %s %s\n", chosen[j], &vocab[c * max_w]);
filtered = 1;
}
if(filtered)
continue;
}
*/
chosen[i++]=c;
HV* hash = newHV();
SV* word = newSVpvf(&vocab[best[a].wordi * max_w], 0);
AV* heat = newAV();
if(latin_enc == 0) SvUTF8_on(word);
hv_store(hash, "word", strlen("word"), word , 0);
hv_store(hash, "rank", strlen("rank"), newSVuv(best[a].wordi), 0);
hv_store(hash, "average", strlen("average"), newSVnv(best[a].average), 0);
hv_store(hash, "prob", strlen("prob"), newSVnv(best[a].probability), 0);
hv_store(hash, "cprob", strlen("cprob"), newSVnv(best[a].cprobability_sum), 0);
hv_store(hash, "max", strlen("max"), newSVnv(best[a].max_activation), 0); // newSVnv(target_sums[best[a].wordi]), 0);
hv_store(hash, "overall", strlen("overall"), newSVnv(best[a].activation_sum/total_activation), 0); // newSVnv(target_sums[best[a].wordi]), 0);
hv_store(hash, "pos", strlen("pos"), newSVnv(best[a].position), 0);
best[a].heat[5]=0;
for(i=10; i >= 0; i--) av_push(heat, newSVnv(best[a].heat[i]));
hv_store(hash, "heat", strlen("heat"), newRV_noinc((SV*)heat), 0);
av_push(array, newRV_noinc((SV*)hash));
}
hv_store(result, "syntagmatic", strlen("syntagmatic"), newRV_noinc((SV*)array), 0);
}
end:
// words = old_words; // why was this here?
free(best);
return newRV_noinc((SV*)result);
}
int dump_vecs(char *fname) {
long i, j;
FILE *f;
if(words>100000)
words=100000;
if((f=fopen(fname, "w")) == NULL) {
fprintf(stderr, "cannot open %s for writing\n", fname);
return(-1);
}
fprintf(f, "%lld %lld\n", words, size);
for (i=0; i < words; i++) {
fprintf(f, "%s ", &vocab[i * max_w]);
for(j=0; j < size - 1; j++)
fprintf(f, "%f ", M[i*size + j]);
fprintf(f, "%f\n", M[i*size + j]);
}
fclose(f);
return(0);
}
int dump_for_numpy(char *fname) {
long i, j;
FILE *f;
int max;
if(merged_end > 0)
max = 150000;
else
max = 300000;
if(words>300000)
words=300000;
if((f=fopen(fname, "w")) == NULL) {
fprintf(stderr, "cannot open %s for writing\n", fname);
return(-1);
}
for (i=0; i < max; i++) {
for(j=0; j < size - 1; j++)
fprintf(f, "%f\t", M[i*size + j]);
fprintf(f, "%f\n", M[i*size + j]);
printf("%s\n", &vocab[i * max_w]);
if(merged_end > 0) {
for(j=0; j < size - 1; j++)
fprintf(f, "%f\t", M[(merged_end + i)*size + j]);
fprintf(f, "%f\n", M[(merged_end + i)*size + j]);
printf("_%s\n", &vocab[i * max_w]);
}
}
fclose(f);
return(0);
}