/*!
* This function performs a CNID db search
*
* Uses globals c1, c2, the search criteria
*
* @param vol (r) volume we are searching on ...
* @param dir (rw) directory we are starting from ...
* @param uname (r) UNIX name of object to search
* @param rmatches (r) maximum number of matches we can return
* @param pos (r) position we've stopped recently
* @param rbuf (w) output buffer
* @param nrecs (w) number of matches
* @param rsize (w) length of data written to output buffer
* @param ext (r) extended search flag
*/
static int catsearch_db(struct vol *vol,
struct dir *dir,
const char *uname,
int rmatches,
uint32_t *pos,
char *rbuf,
uint32_t *nrecs,
int *rsize,
int ext)
{
static char resbuf[DBD_MAX_SRCH_RSLTS * sizeof(cnid_t)];
static uint32_t cur_pos;
static int num_matches;
int ccr ,r;
int result = AFP_OK;
struct path path;
char *rrbuf = rbuf;
char buffer[MAXPATHLEN +2];
uint16_t flags = CONV_TOLOWER;
LOG(log_debug, logtype_afpd, "catsearch_db(req pos: %u): {pos: %u, name: %s}",
*pos, cur_pos, uname);
if (*pos != 0 && *pos != cur_pos) {
result = AFPERR_CATCHNG;
goto catsearch_end;
}
if (cur_pos == 0 || *pos == 0) {
if (convert_charset(vol->v_volcharset,
vol->v_volcharset,
vol->v_maccharset,
uname,
strlen(uname),
buffer,
MAXPATHLEN,
&flags) == (size_t)-1) {
LOG(log_error, logtype_afpd, "catsearch_db: conversion error");
result = AFPERR_MISC;
goto catsearch_end;
}
LOG(log_debug, logtype_afpd, "catsearch_db: %s", buffer);
if ((num_matches = cnid_find(vol->v_cdb,
buffer,
strlen(uname),
resbuf,
sizeof(resbuf))) == -1) {
result = AFPERR_MISC;
goto catsearch_end;
}
}
while (cur_pos < num_matches) {
char *name;
cnid_t cnid, did;
char resolvebuf[12 + MAXPATHLEN + 1];
struct dir *dir;
/* Next CNID to process from buffer */
memcpy(&cnid, resbuf + cur_pos * sizeof(cnid_t), sizeof(cnid_t));
did = cnid;
if ((name = cnid_resolve(vol->v_cdb, &did, resolvebuf, 12 + MAXPATHLEN + 1)) == NULL)
goto next;
LOG(log_debug, logtype_afpd, "catsearch_db: {pos: %u, name:%s, cnid: %u}",
cur_pos, name, ntohl(cnid));
if ((dir = dirlookup(vol, did)) == NULL)
goto next;
if (movecwd(vol, dir) < 0 )
goto next;
memset(&path, 0, sizeof(path));
path.u_name = name;
path.m_name = utompath(vol, name, cnid, utf8_encoding());
if (of_stat(vol, &path) != 0) {
switch (errno) {
case EACCES:
case ELOOP:
goto next;
case ENOENT:
default:
result = AFPERR_MISC;
goto catsearch_end;
}
}
/* For files path.d_dir is the parent dir, for dirs its the dir itself */
if (S_ISDIR(path.st.st_mode))
if ((dir = dirlookup(vol, cnid)) == NULL)
goto next;
path.d_dir = dir;
LOG(log_maxdebug, logtype_afpd,"catsearch_db: dir: %s, cwd: %s, name: %s",
cfrombstr(dir->d_fullpath), getcwdpath(), path.u_name);
/* At last we can check the search criteria */
ccr = crit_check(vol, &path);
if ((ccr & 1)) {
LOG(log_debug, logtype_afpd,"catsearch_db: match: %s/%s",
getcwdpath(), path.u_name);
/* bit 1 means that criteria has been met */
r = rslt_add(vol, &path, &rrbuf, ext);
if (r == 0) {
result = AFPERR_MISC;
goto catsearch_end;
}
*nrecs += r;
/* Number of matches limit */
if (--rmatches == 0)
goto catsearch_pause;
/* Block size limit */
if (rrbuf - rbuf >= 448)
goto catsearch_pause;
}
next:
cur_pos++;
} /* while */
/* finished */
result = AFPERR_EOF;
cur_pos = 0;
goto catsearch_end;
catsearch_pause:
*pos = cur_pos;
catsearch_end: /* Exiting catsearch: error condition */
*rsize = rrbuf - rbuf;
LOG(log_debug, logtype_afpd, "catsearch_db(req pos: %u): {pos: %u}", *pos, cur_pos);
return result;
}
void perceptron::multi_train(){
ofstream of_stat("perceptron_train_stat.txt");
cout << "iniciando perceptron multicapa";
//el numero de clases es el tamanio de un dato, menos numAtt
int epoch = 0;
while(true){
float sum_ecm = 0;
bool error = false;
int numOk=0;
int numInstance = 0;
for (vector<Caso>::iterator caso = training_data.begin(); caso != training_data.end(); ++caso)
{
Caso instance = caso[0];
numInstance++;
//Se reinician los valores de entrada y regla delta
for (std::vector<Neuron>::iterator itr = y.begin(); itr != y.end(); ++itr)
{
itr[0].in_value=0;
itr[0].delta_value = 0;
}
for (std::vector<Neuron>::iterator itr = z.begin(); itr != z.end(); ++itr)
{
itr[0].delta_value = 0;
if(itr[0].is_bias == 1)continue;
itr[0].in_value = 0;
}
//FEEDFORWARD
//por cada caso de entrenamiento, inicializar neuronas
int i=0;
for (std::vector<float>::iterator att = instance.first.begin(); att != instance.first.end(); ++att)
{
//input[i].in_value = att[0];
input[i].out_value = preProcesar(att[0],i);
i++;
if(input[i].is_bias==1){
//input[i++].out_value = 1;
}
}
//for (std::vector<Neuron>::iterator layer_in = input.begin(); layer_in != input.end(); ++layer_in)
//{
// if(layer_in[0].is_bias == 1) layer_in[0].out_value = 1;
// else layer_in[0].out_value = instance.first[i++];
//}
//e interpretamos la clase
int clase=1;
for (std::vector<int>::iterator citr = instance.second.begin(); citr != instance.second.end(); ++citr)
{
if(citr[0] == 1) break;
clase++;
}
//ahora, procedemos a calcular las salidas
//propagamos las entradas
for (std::vector<Link>::iterator link = l_z.begin(); link != l_z.end(); ++link)
{
link[0].sumLink();
}
//calculamos valor de capa media, aplicando la bipolar para calcular la salida
for (std::vector<Neuron>::iterator neuz = z.begin(); neuz != z.end(); ++ neuz)
{
if(neuz[0].is_bias==1) neuz[0].out_value = 1; //si es el sesgo, solo ponemos 1 en salida
else neuz[0].evalNeuron(0, &bipolar_sigmoidal);
//cout << "salida neurona z" << neuz[0].out_value << endl;
}
//propagamos a la salida
for (std::vector<Link>::iterator link_y = l_y.begin(); link_y != l_y.end(); ++ link_y)
{
link_y[0].sumLink();
}
//calculamos las salidas, y vemos la clase respuesta
int pred_class = 0;
int cnt = 1;
float max_value = -9999;
//tenemos que ver cual es la neurona activada, en caso de dos, dar error
for (std::vector<Neuron>::iterator neuy = y.begin(); neuy != y.end(); ++ neuy)
{
if(neuy[0].evalNeuron(0,&bipolar_sigmoidal)>= max_value){
pred_class = cnt;
max_value = neuy[0].out_value;
}
//cout << "salida y:" << neuy[0].out_value << "\n";
cnt++;
}
if(pred_class == clase){
//if(pred_class == 3)cout << "epoch: " << epoch << "pred: " <<pred_class << "value: "<< max_value<< endl;
numOk++;
}else{
error = true;
}
//BACKPROPAGATION:
//primero hallamos los delta value de las neuronas de salida
cnt = 0;
float ecm_contr = 0;
for (vector<Neuron>::iterator neuy = y.begin(); neuy != y.end(); ++ neuy, cnt++)
{
float val = -0.9;
if(instance.second[cnt]==1){ //para ver si es valor teorico 1 o -1 la neurona de salidas
val = 0.9;
}
neuy[0].delta_value = (val-neuy[0].out_value)*
(0.5*(1-neuy[0].out_value)*(1+neuy[0].out_value)); //BIPOLAR
//(neuy[0].out_value*(1-neuy[0].out_value)); //BINARY
ecm_contr += (val - neuy[0].out_value)*(val - neuy[0].out_value);
}
ecm_contr /= y.size();
sum_ecm += ecm_contr;
//vemos actualizacion pesos de salida
cnt = 0;
for (vector<Link>::iterator link_y = l_y.begin(); link_y != l_y.end(); ++link_y,cnt++)
{
if(link_y[0].from->is_bias == 1){
link_y[0].weight_update += learn_rate*link_y[0].to->delta_value;
}else {
link_y[0].weight_update += learn_rate*link_y[0].to->delta_value
*link_y[0].from->out_value;
}
}
//propagamos el valor delta
for (vector<Link>::iterator link_y = l_y.begin(); link_y != l_y.end(); ++link_y)
{
link_y[0].sumDelta();
}
//ahora calculamos la rectificacion de delta para las capas intermedias
for (std::vector<Neuron>::iterator neuz = z.begin(); neuz != z.end(); ++ neuz)
{
neuz[0].delta_value *= 0.5*(1+neuz[0].out_value)*(1-neuz[0].out_value); //BIPOLAR
//neuz[0].delta_value *= neuz[0].out_value*(1-neuz[0].out_value); //BINARY
}
//rectificamos pesos de entrada
for (std::vector<Link>::iterator link_z = l_z.begin(); link_z != l_z.end(); ++ link_z)
{
if(link_z[0].from->is_bias == 0)
link_z[0].weight_update += learn_rate*link_z[0].to->delta_value
*link_z[0].from->in_value;
else
link_z[0].weight_update += learn_rate*link_z[0].to->delta_value;
}
//rectificamos pesos
for (std::vector<Link>::iterator link_y = l_y.begin(); link_y != l_y.end(); ++link_y)
{
link_y[0].weight+=link_y[0].weight_update;
link_y[0].weight_update = 0;
}
for (std::vector<Link>::iterator link_z = l_z.begin(); link_z != l_z.end(); ++link_z)
{
link_z[0].weight+=link_z[0].weight_update;
link_z[0].weight_update = 0;
}
}
//if(epoch % 5 == 0)
sum_ecm = sum_ecm/(training_data.size());
cout << "Epoca num:"<<epoch <<" correctness: " <<((double)(numOk)/training_data.size())*100 << "\n";
of_stat << epoch << "\t" << 100 - ((double)(numOk)/training_data.size())*100 << "\t" << sum_ecm << endl;
// if(numOk == (training_data.size()-1)) break;
if(error == false) break;
if(epoch >= 1000) break;
epoch++;
}
cout << "\ntotal epocas :" << epoch << "\n";
of_stat.close();
}
static int catsearch(struct vol *vol,
struct dir *dir,
int rmatches,
uint32_t *pos,
char *rbuf,
uint32_t *nrecs,
int *rsize,
int ext)
{
static u_int32_t cur_pos; /* Saved position index (ID) - used to remember "position" across FPCatSearch calls */
static DIR *dirpos; /* UNIX structure describing currently opened directory. */
struct dir *currentdir; /* struct dir of current directory */
int cidx, r;
struct dirent *entry;
int result = AFP_OK;
int ccr;
struct path path;
char *vpath = vol->v_path;
char *rrbuf = rbuf;
time_t start_time;
int num_rounds = NUM_ROUNDS;
int cwd = -1;
int error;
int unlen;
if (*pos != 0 && *pos != cur_pos) {
result = AFPERR_CATCHNG;
goto catsearch_end;
}
/* FIXME: Category "offspring count ! */
/* We need to initialize all mandatory structures/variables and change working directory appropriate... */
if (*pos == 0) {
clearstack();
if (dirpos != NULL) {
closedir(dirpos);
dirpos = NULL;
}
if (addstack(vpath, dir, -1) == -1) {
result = AFPERR_MISC;
goto catsearch_end;
}
/* FIXME: Sometimes DID is given by client ! (correct this one above !) */
}
/* Save current path */
if ((cwd = open(".", O_RDONLY)) < 0) {
result = AFPERR_MISC;
goto catsearch_end;
}
/* So we are beginning... */
start_time = time(NULL);
while ((cidx = reducestack()) != -1) {
if ((currentdir = dirlookup(vol, dstack[cidx].ds_did)) == NULL) {
result = AFPERR_MISC;
goto catsearch_end;
}
LOG(log_debug, logtype_afpd, "catsearch: current struct dir: \"%s\"", cfrombstr(currentdir->d_fullpath));
error = movecwd(vol, currentdir);
if (!error && dirpos == NULL)
dirpos = opendir(".");
if (dirpos == NULL)
dirpos = opendir(bdata(currentdir->d_fullpath));
if (error || dirpos == NULL) {
switch (errno) {
case EACCES:
dstack[cidx].ds_checked = 1;
continue;
case EMFILE:
case ENFILE:
case ENOENT:
result = AFPERR_NFILE;
break;
case ENOMEM:
case ENOTDIR:
default:
result = AFPERR_MISC;
} /* switch (errno) */
goto catsearch_end;
}
while ((entry = readdir(dirpos)) != NULL) {
(*pos)++;
if (!check_dirent(vol, entry->d_name))
continue;
LOG(log_debug, logtype_afpd, "catsearch(\"%s\"): dirent: \"%s\"",
cfrombstr(currentdir->d_fullpath), entry->d_name);
memset(&path, 0, sizeof(path));
path.u_name = entry->d_name;
if (of_stat(vol, &path) != 0) {
switch (errno) {
case EACCES:
case ELOOP:
case ENOENT:
continue;
case ENOTDIR:
case EFAULT:
case ENOMEM:
case ENAMETOOLONG:
default:
result = AFPERR_MISC;
goto catsearch_end;
}
}
switch (S_IFMT & path.st.st_mode) {
case S_IFDIR:
/* here we can short cut
ie if in the same loop the parent dir wasn't in the cache
ALL dirsearch_byname will fail.
*/
unlen = strlen(path.u_name);
path.d_dir = dircache_search_by_name(vol,
currentdir,
path.u_name,
unlen);
if (path.d_dir == NULL) {
/* path.m_name is set by adddir */
if ((path.d_dir = dir_add(vol,
currentdir,
&path,
unlen)) == NULL) {
result = AFPERR_MISC;
goto catsearch_end;
}
}
path.m_name = cfrombstr(path.d_dir->d_m_name);
if (addstack(path.u_name, path.d_dir, cidx) == -1) {
result = AFPERR_MISC;
goto catsearch_end;
}
break;
case S_IFREG:
path.d_dir = currentdir;
break;
default:
continue;
}
ccr = crit_check(vol, &path);
/* bit 0 means that criteria has been met */
if ((ccr & 1)) {
r = rslt_add ( vol, &path, &rrbuf, ext);
if (r == 0) {
result = AFPERR_MISC;
goto catsearch_end;
}
*nrecs += r;
/* Number of matches limit */
if (--rmatches == 0)
goto catsearch_pause;
/* Block size limit */
if (rrbuf - rbuf >= 448)
goto catsearch_pause;
}
/* MacOS 9 doesn't like servers executing commands longer than few seconds */
if (--num_rounds <= 0) {
if (start_time != time(NULL)) {
result=AFP_OK;
goto catsearch_pause;
}
num_rounds = NUM_ROUNDS;
}
} /* while ((entry=readdir(dirpos)) != NULL) */
closedir(dirpos);
dirpos = NULL;
dstack[cidx].ds_checked = 1;
} /* while (current_idx = reducestack()) != -1) */
/* We have finished traversing our tree. Return EOF here. */
result = AFPERR_EOF;
goto catsearch_end;
catsearch_pause:
cur_pos = *pos;
save_cidx = cidx;
catsearch_end: /* Exiting catsearch: error condition */
*rsize = rrbuf - rbuf;
if (cwd != -1) {
if ((fchdir(cwd)) != 0) {
LOG(log_debug, logtype_afpd, "error chdiring back: %s", strerror(errno));
}
close(cwd);
}
return result;
} /* catsearch() */
