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#include "weights.h"
#include <sstream>
#include "fdict.h"
#include "filelib.h"
#include "verbose.h"
using namespace std;
void Weights::InitFromFile(const std::string& filename, vector<string>* feature_list) {
if (!SILENT) cerr << "Reading weights from " << filename << endl;
ReadFile in_file(filename);
istream& in = *in_file.stream();
assert(in);
int weight_count = 0;
bool fl = false;
while (in) {
double val = 0;
string buf;
getline(in, buf);
if (buf.size() == 0) continue;
if (buf[0] == '#') continue;
for (int i = 0; i < buf.size(); ++i)
if (buf[i] == '=') buf[i] = ' ';
int start = 0;
while(start < buf.size() && buf[start] == ' ') ++start;
int end = 0;
while(end < buf.size() && buf[end] != ' ') ++end;
int fid = FD::Convert(buf.substr(start, end - start));
while(end < buf.size() && buf[end] == ' ') ++end;
val = strtod(&buf.c_str()[end], NULL);
if (isnan(val)) {
cerr << FD::Convert(fid) << " has weight NaN!\n";
abort();
}
if (wv_.size() <= fid)
wv_.resize(fid + 1);
wv_[fid] = val;
if (feature_list) { feature_list->push_back(FD::Convert(fid)); }
++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";
}
}
void Weights::WriteToFile(const std::string& fname, bool hide_zero_value_features, const string* extra) const {
WriteFile out(fname);
ostream& o = *out.stream();
assert(o);
if (extra) { o << "# " << *extra << endl; }
o.precision(17);
const int num_feats = FD::NumFeats();
for (int i = 1; i < num_feats; ++i) {
const double val = (i < wv_.size() ? wv_[i] : 0.0);
if (hide_zero_value_features && val == 0.0) continue;
o << FD::Convert(i) << ' ' << val << endl;
}
}
void Weights::InitVector(std::vector<double>* w) const {
*w = wv_;
}
void Weights::InitSparseVector(SparseVector<double>* w) const {
for (int i = 1; i < wv_.size(); ++i) {
const double& weight = wv_[i];
if (weight) w->set_value(i, weight);
}
}
void Weights::InitFromVector(const std::vector<double>& w) {
wv_ = w;
if (wv_.size() > FD::NumFeats())
cerr << "WARNING: initializing weight vector has more features than the global feature dictionary!\n";
wv_.resize(FD::NumFeats(), 0);
}
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