From 38a5bee71f6b49515cd105a9467ff602ff9dee64 Mon Sep 17 00:00:00 2001 From: Chris Dyer Date: Tue, 13 Sep 2011 13:25:46 +0100 Subject: optional support for doing perfect hashing of feature strings to save lots of memory --- utils/weights.cc | 132 +++++++++++++++++++++++++++++++++++++------------------ 1 file changed, 89 insertions(+), 43 deletions(-) (limited to 'utils/weights.cc') diff --git a/utils/weights.cc b/utils/weights.cc index b994a2fe..0916b72a 100644 --- a/utils/weights.cc +++ b/utils/weights.cc @@ -13,40 +13,75 @@ void Weights::InitFromFile(const std::string& filename, vector* feature_ ReadFile in_file(filename); istream& in = *in_file.stream(); assert(in); - 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; - 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; - const 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(); + + bool read_text = true; + if (1) { + ReadFile hdrrf(filename); + istream& hi = *hdrrf.stream(); + assert(hi); + char buf[10]; + hi.get(buf, 6); + 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)); + 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 (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 (fl) { cerr << endl; } + cerr << "Loaded " << weight_count << " feature weights\n"; + } + } else { // !read_text + char buf[6]; + in.get(buf, 6); + size_t num_keys[2]; + in.get(reinterpret_cast(&num_keys[0]), sizeof(size_t) + 1); + if (num_keys[0] != FD::NumFeats()) { + cerr << "Hash function reports " << FD::NumFeats() << " keys but weights file contains " << num_keys[0] << endl; + abort(); + } + wv_.resize(num_keys[0]); + in.get(reinterpret_cast(&wv_[0]), num_keys[0] * sizeof(weight_t)); + if (!in.good()) { + cerr << "Error loading weights!\n"; + abort(); } - } - if (!SILENT) { - if (fl) { cerr << endl; } - cerr << "Loaded " << weight_count << " feature weights\n"; } } @@ -54,37 +89,48 @@ void Weights::WriteToFile(const std::string& fname, bool hide_zero_value_feature 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; + 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 < wv_.size() ? wv_[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 <= wv_.size()); + o.write(reinterpret_cast(&keys), sizeof(keys)); + o.write(reinterpret_cast(&wv_[0]), keys * sizeof(weight_t)); } } -void Weights::InitVector(std::vector* w) const { +void Weights::InitVector(std::vector* w) const { *w = wv_; } -void Weights::InitSparseVector(SparseVector* w) const { +void Weights::InitSparseVector(SparseVector* w) const { for (int i = 1; i < wv_.size(); ++i) { - const double& weight = wv_[i]; + const weight_t& weight = wv_[i]; if (weight) w->set_value(i, weight); } } -void Weights::InitFromVector(const std::vector& w) { +void Weights::InitFromVector(const std::vector& 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); } -void Weights::InitFromVector(const SparseVector& w) { +void Weights::InitFromVector(const SparseVector& w) { wv_.clear(); wv_.resize(FD::NumFeats(), 0.0); for (int i = 1; i < FD::NumFeats(); ++i) wv_[i] = w.value(i); } + -- cgit v1.2.3