| #!/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); |
| |
| 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 *) ¶_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); |
| } |