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#include "weights.h"
#include <sstream>
#include "fdict.h"
#include "filelib.h"
#include "stringlib.h"
#include "verbose.h"
using namespace std;
void Weights::InitFromFile(const string& filename,
vector<weight_t>* pweights,
vector<string>* feature_list) {
vector<weight_t>& weights = *pweights;
if (!SILENT) cerr << "Reading weights from " << filename << endl;
ReadFile in_file(filename);
istream& in = *in_file.stream();
assert(in);
bool read_text = true;
if (1) {
ReadFile hdrrf(filename);
istream& hi = *hdrrf.stream();
assert(hi);
char buf[10];
hi.read(buf, 5);
assert(hi.good());
if (strncmp(buf, "_PHWf", 5) == 0) {
read_text = false;
}
}
if (read_text) {
int weight_count = 0;
bool fl = false;
string buf;
double val = 0;
while (in) {
getline(in, buf);
if (buf.size() == 0) continue;
if (buf[0] == '#') continue;
if (buf[0] == ' ') {
cerr << "Weights file lines may not start with whitespace.\n" << buf << endl;
abort();
}
for (int i = buf.size() - 1; i > 0; --i)
if (buf[i] == '=' || buf[i] == '\t') { buf[i] = ' '; break; }
unsigned start = 0;
while(start < buf.size() && buf[start] == ' ') ++start;
unsigned end = 0;
while(end < buf.size() && buf[end] != ' ') ++end;
const unsigned fid = FD::Convert(buf.substr(start, end - start));
if (feature_list) { feature_list->push_back(buf.substr(start, end - start)); }
while(end < buf.size() && buf[end] == ' ') ++end;
val = strtod(&buf.c_str()[end], NULL);
if (std::isnan(val)) {
cerr << FD::Convert(fid) << " has weight NaN!\n";
abort();
}
if (weights.size() <= fid)
weights.resize(fid + 1);
weights[fid] = val;
++weight_count;
if (!SILENT) {
if (weight_count % 50000 == 0) { cerr << '.' << flush; fl = true; }
if (weight_count % 2000000 == 0) { cerr << " [" << weight_count << "]\n"; fl = false; }
}
}
if (!SILENT) {
if (fl) { cerr << endl; }
cerr << "Loaded " << weight_count << " feature weights\n";
}
} else { // !read_text
char buf[6];
in.read(buf, 5);
int num_keys;
in.read(reinterpret_cast<char*>(&num_keys), sizeof(size_t));
if (num_keys != FD::NumFeats()) {
cerr << "Hash function reports " << FD::NumFeats() << " keys but weights file contains " << num_keys << endl;
abort();
}
weights.resize(num_keys);
in.read(reinterpret_cast<char*>(&weights.front()), num_keys * sizeof(weight_t));
if (!in.good()) {
cerr << "Error loading weights!\n";
abort();
} else {
cerr << " Successfully loaded " << (num_keys * sizeof(weight_t)) << " bytes\n";
}
}
}
void Weights::WriteToFile(const string& fname,
const vector<weight_t>& weights,
bool hide_zero_value_features,
const string* extra) {
WriteFile out(fname);
ostream& o = *out.stream();
assert(o);
bool write_text = !FD::UsingPerfectHashFunction();
if (write_text) {
if (extra) { o << "# " << *extra << endl; }
o.precision(17);
const unsigned num_feats = FD::NumFeats();
for (unsigned i = 1; i < num_feats; ++i) {
const weight_t val = (i < weights.size() ? weights[i] : 0.0);
if (hide_zero_value_features && val == 0.0) continue;
o << FD::Convert(i) << ' ' << val << endl;
}
} else {
o.write("_PHWf", 5);
const size_t keys = FD::NumFeats();
assert(keys <= weights.size());
o.write(reinterpret_cast<const char*>(&keys), sizeof(keys));
o.write(reinterpret_cast<const char*>(&weights[0]), keys * sizeof(weight_t));
}
}
void Weights::InitSparseVector(const vector<weight_t>& dv,
SparseVector<weight_t>* sv) {
sv->clear();
for (unsigned i = 1; i < dv.size(); ++i) {
if (dv[i]) sv->set_value(i, dv[i]);
}
}
void Weights::SanityCheck(const vector<weight_t>& w) {
for (unsigned i = 1; i < w.size(); ++i) {
if (std::isnan(w[i]) || std::isinf(w[i])) {
cerr << FD::Convert(i) << " has bad weight: " << w[i] << endl;
abort();
}
}
}
struct FComp {
const vector<weight_t>& w_;
FComp(const vector<weight_t>& w) : w_(w) {}
bool operator()(int a, int b) const {
return fabs(w_[a]) > fabs(w_[b]);
}
};
void Weights::ShowLargestFeatures(const vector<weight_t>& w) {
vector<int> fnums(w.size());
for (unsigned i = 0; i < w.size(); ++i)
fnums[i] = i;
int nf = w.size();
if (nf > 10) nf = 10;
vector<int>::iterator mid = fnums.begin();
mid += nf;
partial_sort(fnums.begin(), mid, fnums.end(), FComp(w));
cerr << "TOP FEATURES:";
for (vector<int>::iterator i = fnums.begin(); i != mid; ++i) {
cerr << ' ' << FD::Convert(*i) << '=' << w[*i];
}
cerr << endl;
}
string Weights::GetString(const vector<weight_t>& w,
bool hide_zero_value_features) {
ostringstream os;
os.precision(17);
const unsigned nf = FD::NumFeats();
for (unsigned i = 1; i < nf; i++) {
weight_t val = (i < w.size() ? w[i] : 0.0);
if (hide_zero_value_features && val == 0.0) {
continue;
}
os << ' ' << FD::Convert(i) << '=' << val;
}
return os.str().substr(1);
}
void Weights::UpdateFromString(string& w_string,
vector<weight_t>& w) {
vector<string> tok = SplitOnWhitespace(w_string);
for (vector<string>::iterator i = tok.begin(); i != tok.end(); i++) {
int delim = i->find('=');
int fid = FD::Convert(i->substr(0, delim));
w[fid] = strtod(i->substr(delim + 1).c_str(), NULL);
}
}
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