1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
|
#include "weights.h"
#include <sstream>
#include "fdict.h"
#include "filelib.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;
weight_t 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; }
int start = 0;
while(start < buf.size() && buf[start] == ' ') ++start;
int end = 0;
while(end < buf.size() && buf[end] != ' ') ++end;
const int 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 (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);
size_t 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 int num_feats = FD::NumFeats();
for (int 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 (int i = 0; i < w.size(); ++i) {
assert(!isnan(w[i]));
assert(!isinf(w[i]));
}
}
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 (int i = 0; i < w.size(); ++i)
fnums[i] = i;
int nf = FD::NumFeats();
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;
}
|
