diff options
| -rw-r--r-- | BUILDING | 17 | ||||
| -rw-r--r-- | Makefile.am | 2 | ||||
| -rw-r--r-- | configure.ac | 2 | ||||
| -rw-r--r-- | creg/Makefile.am | 11 | ||||
| -rw-r--r-- | creg/README | 17 | ||||
| -rw-r--r-- | creg/creg.cc | 384 | ||||
| -rw-r--r-- | creg/json_feature_map_lexer.h | 15 | ||||
| -rw-r--r-- | creg/json_feature_map_lexer.ll | 132 | ||||
| -rw-r--r-- | creg/test_data/auto-mpg.testfeat | 93 | ||||
| -rw-r--r-- | creg/test_data/auto-mpg.testresp | 93 | ||||
| -rw-r--r-- | creg/test_data/auto-mpg.trainfeat | 300 | ||||
| -rw-r--r-- | creg/test_data/auto-mpg.trainresp | 300 | ||||
| -rw-r--r-- | creg/test_data/iris.testfeat | 50 | ||||
| -rw-r--r-- | creg/test_data/iris.testresp | 50 | ||||
| -rw-r--r-- | creg/test_data/iris.trainfeat | 100 | ||||
| -rw-r--r-- | creg/test_data/iris.trainresp | 100 | ||||
| -rw-r--r-- | training/liblbfgs/lbfgs++.h | 30 | ||||
| -rw-r--r-- | training/liblbfgs/ll_test.cc | 4 | ||||
| -rw-r--r-- | utils/fast_sparse_vector.h | 16 |
19 files changed, 1686 insertions, 30 deletions
@@ -1,6 +1,5 @@ To build cdec, you'll need: - * Google c++ testing framework (http://code.google.com/p/googletest/) * boost headers & boost program_options (you may need to install a package like boost-devel) @@ -8,20 +7,14 @@ To build cdec, you'll need: Instructions for building ----------------------------------- - 1) Optional: Download and build SRILM - - 2) Download, build, and install Google Test (optional, this is necessary - to build unit tests that may be useful in development; system tests - work without it) - - 3) Use automake / autoconf to generate the configure script. + 1) Use automake / autoconf to generate the configure script. I'm not an expert at using these tools, but this should be sufficient: autoreconf -ifv - 4) Configure and build. Your command will look something like this. + 2) Configure and build. Your command will look something like this. - ./configure --disable-gtest + ./configure make If you get errors during configure about missing BOOST macros, then step 3 @@ -36,12 +29,12 @@ Instructions for building make LIBS+="-lz -lboost_program_options" \ CFLAGS+="-Wno-sign-compare" - 5) Test + 3) Test ./tests/run-system-tests.pl Everything should pass. - 6) Enjoy! + 4) Enjoy! diff --git a/Makefile.am b/Makefile.am index ea5e2b3f..0e08ee72 100644 --- a/Makefile.am +++ b/Makefile.am @@ -1,7 +1,7 @@ # warning - the subdirectories in the following list should # be kept in topologically sorted order. Also, DO NOT introduce # cyclic dependencies between these directories! -SUBDIRS = utils mteval klm/util klm/lm decoder phrasinator training training/liblbfgs mira dtrain dpmert pro-train rampion extools gi/pf gi/markov_al rst_parser +SUBDIRS = utils mteval klm/util klm/lm decoder phrasinator training training/liblbfgs creg mira dtrain dpmert pro-train rampion extools gi/pf gi/markov_al rst_parser #gi/pyp-topics/src gi/clda/src gi/posterior-regularisation/prjava diff --git a/configure.ac b/configure.ac index 849b100b..1e853fb6 100644 --- a/configure.ac +++ b/configure.ac @@ -130,4 +130,4 @@ then AM_CONDITIONAL([GLC], true) fi -AC_OUTPUT(Makefile rst_parser/Makefile utils/Makefile mteval/Makefile extools/Makefile decoder/Makefile phrasinator/Makefile training/Makefile training/liblbfgs/Makefile dpmert/Makefile pro-train/Makefile rampion/Makefile klm/util/Makefile klm/lm/Makefile mira/Makefile dtrain/Makefile gi/pyp-topics/src/Makefile gi/clda/src/Makefile gi/pf/Makefile gi/markov_al/Makefile) +AC_OUTPUT(Makefile rst_parser/Makefile utils/Makefile mteval/Makefile extools/Makefile decoder/Makefile phrasinator/Makefile training/Makefile training/liblbfgs/Makefile creg/Makefile dpmert/Makefile pro-train/Makefile rampion/Makefile klm/util/Makefile klm/lm/Makefile mira/Makefile dtrain/Makefile gi/pyp-topics/src/Makefile gi/clda/src/Makefile gi/pf/Makefile gi/markov_al/Makefile) diff --git a/creg/Makefile.am b/creg/Makefile.am new file mode 100644 index 00000000..9e25b838 --- /dev/null +++ b/creg/Makefile.am @@ -0,0 +1,11 @@ +bin_PROGRAMS = \ + creg + +creg_SOURCES = creg.cc json_feature_map_lexer.cc +creg_LDADD = $(top_srcdir)/training/liblbfgs/liblbfgs.a $(top_srcdir)/utils/libutils.a -lz + +json_feature_map_lexer.cc: json_feature_map_lexer.ll + $(LEX) -s -8 -CF -o$@ $< + +AM_CPPFLAGS = -W -Wall -DNDEBUG -I$(top_srcdir)/utils -I$(top_srcdir)/training + diff --git a/creg/README b/creg/README new file mode 100644 index 00000000..28a71d11 --- /dev/null +++ b/creg/README @@ -0,0 +1,17 @@ +creg is a fast tool for training linear and logistic regression models with +l_1 and l_2 regularization. Its data (feature and response) format is +compatible with ARKRegression. + +EXAMPLES + +Logistic regression example (training only): + $ ./creg -x test_data/iris.trainfeat -y test_data/iris.trainresp --l1 1.0 > weights.txt + +Logistic regression example (training and testing): + $ ./creg -x test_data/iris.trainfeat -y test_data/iris.trainresp --l1 1.0 \ + -t test_data/iris.testfeat -s test_data/iris.testresp > weights.txt + +Linear regression example (training and testing): + $ ./creg -n -x test_data/auto-mpg.trainfeat -y test_data/auto-mpg.trainresp --l2 1000 \ + -t test_data/auto-mpg.testfeat -s test_data/auto-mpg.testresp > weights.txt + diff --git a/creg/creg.cc b/creg/creg.cc new file mode 100644 index 00000000..005ec9ac --- /dev/null +++ b/creg/creg.cc @@ -0,0 +1,384 @@ +#include <cstdlib> +#include <iostream> +#include <vector> +#include <tr1/unordered_map> +#include <limits> +#include <cmath> + +#include <boost/program_options.hpp> +#include <boost/program_options/variables_map.hpp> + +#include "json_feature_map_lexer.h" +#include "prob.h" +#include "filelib.h" +#include "weights.h" +#include "sparse_vector.h" +#include "liblbfgs/lbfgs++.h" + +using namespace std; +using namespace std::tr1; +namespace po = boost::program_options; + +void InitCommandLine(int argc, char** argv, po::variables_map* conf) { + po::options_description opts("Configuration options"); + opts.add_options() + ("training_features,x", po::value<string>(), "File containing training instance features (ARKRegression format)") + ("training_responses,y", po::value<string>(), "File containing training response features (ARKRegression format)") + ("linear,n", "Linear (rather than logistic) regression") + ("l1",po::value<double>()->default_value(0.0), "l_1 regularization strength") + ("l2",po::value<double>()->default_value(0.0), "l_2 regularization strength") + ("test_features,t", po::value<string>(), "File containing training instance features (ARKRegression format)") + ("test_responses,s", po::value<string>(), "File containing training response features (ARKRegression format)") + ("weights,w", po::value<string>(), "Initial weights") + ("epsilon,e", po::value<double>()->default_value(1e-4), "Epsilon for convergence test. Terminates when ||g|| < epsilon * max(1, ||w||)") + ("memory_buffers,m",po::value<unsigned>()->default_value(40), "Number of memory buffers for LBFGS") + ("help,h", "Help"); + po::options_description dcmdline_options; + dcmdline_options.add(opts); + po::store(parse_command_line(argc, argv, dcmdline_options), *conf); + if (conf->count("help") || !conf->count("training_features") || !conf->count("training_responses")) { + cerr << dcmdline_options << endl; + exit(1); + } +} + +struct TrainingInstance { + SparseVector<float> x; + union { + unsigned label; // for categorical predictions + float value; // for continuous predictions + } y; +}; + +struct ReaderHelper { + explicit ReaderHelper(vector<TrainingInstance>* xyp) : xy_pairs(xyp), lc(), flag() {} + unordered_map<string, unsigned> id2ind; + vector<TrainingInstance>* xy_pairs; + int lc; + bool flag; +}; + +void ReaderCB(const string& id, const SparseVector<float>& fmap, void* extra) { + ReaderHelper& rh = *reinterpret_cast<ReaderHelper*>(extra); + ++rh.lc; + if (rh.lc % 1000 == 0) { cerr << '.'; rh.flag = true; } + if (rh.lc % 40000 == 0) { cerr << " [" << rh.lc << "]\n"; rh.flag = false; } + const unordered_map<string, unsigned>::iterator it = rh.id2ind.find(id); + if (it == rh.id2ind.end()) { + cerr << "Unlabeled example in line " << rh.lc << endl; + abort(); + } + (*rh.xy_pairs)[it->second - 1].x = fmap; +} + +void ReadLabeledInstances(const string& ffeats, + const string& fresp, + const bool is_continuous, + vector<TrainingInstance>* xy_pairs, + vector<string>* labels) { + bool flag = false; + xy_pairs->clear(); + int lc = 0; + ReaderHelper rh(xy_pairs); + unordered_map<string, unsigned> label2id; + cerr << "Reading responses from " << fresp << " ..." << endl; + ReadFile fr(fresp); + for (unsigned i = 0; i < labels->size(); ++i) + label2id[(*labels)[i]] = i; + istream& in = *fr.stream(); + string line; + while(getline(in, line)) { + ++lc; + if (lc % 1000 == 0) { cerr << '.'; flag = true; } + if (lc % 40000 == 0) { cerr << " [" << lc << "]\n"; flag = false; } + if (line.size() == 0) continue; + if (line[0] == '#') continue; + unsigned p = 0; + while (p < line.size() && line[p] != ' ' && line[p] != '\t') { ++p; } + unsigned& ind = rh.id2ind[line.substr(0, p)]; + if (ind != 0) { cerr << "ID " << line.substr(0, p) << " duplicated in line " << lc << endl; abort(); } + while (p < line.size() && (line[p] == ' ' || line[p] == '\t')) { ++p; } + assert(p < line.size()); + xy_pairs->push_back(TrainingInstance()); + ind = xy_pairs->size(); + if (is_continuous) { + xy_pairs->back().y.value = strtof(&line[p], 0); + } else { // categorical predictions + unordered_map<string, unsigned>::iterator it = label2id.find(line.substr(p)); + if (it == label2id.end()) { + const string label = line.substr(p); + it = label2id.insert(make_pair(label, labels->size())).first; + labels->push_back(label); + } + xy_pairs->back().y.label = it->second; // label id + } + } + if (flag) cerr << endl; + if (!is_continuous) { + cerr << "LABELS:"; + for (unsigned j = 0; j < labels->size(); ++j) + cerr << " " << (*labels)[j]; + cerr << endl; + } + cerr << "Reading features from " << ffeats << " ..." << endl; + ReadFile ff(ffeats); + JSONFeatureMapLexer::ReadRules(ff.stream(), ReaderCB, &rh); + if (rh.flag) cerr << endl; +} + +// helper base class (not polymorphic- just a container and some helper functions) for loss functions +// real loss functions should implement double operator()(const vector<double>& x, double* g), +// which should evaluate f(x) and g = f'(x) +struct BaseLoss { + // dimp1 = number of categorial outputs possible for logistic regression + // for linear regression, it should be 1 more than the dimension of the response variable + BaseLoss( + const vector<TrainingInstance>& tr, + unsigned dimp1, + unsigned numfeats, + unsigned ll2) : training(tr), K(dimp1), p(numfeats), l2(ll2) {} + + // weight vector layout for K classes, with p features + // w[0 : K-1] = bias weights + // w[y*p + K : y*p + K + p - 1] = feature weights for y^th class + // this representation is used in ComputeDotProducts and GradAdd + void ComputeDotProducts(const SparseVector<float>& fx, // feature vector of x + const vector<double>& w, // full weight vector + vector<double>* pdotprods) const { + vector<double>& dotprods = *pdotprods; + const unsigned km1 = K - 1; + dotprods.resize(km1); + for (unsigned y = 0; y < km1; ++y) + dotprods[y] = w[y]; // bias terms + for (SparseVector<float>::const_iterator it = fx.begin(); it != fx.end(); ++it) { + const float fval = it->second; + const unsigned fid = it->first; + for (unsigned y = 0; y < km1; ++y) + dotprods[y] += w[fid + y * p + km1] * fval; + } + } + + double ApplyRegularizationTerms(const vector<double>& weights, + double* g) const { + double reg = 0; + for (size_t i = K - 1; i < weights.size(); ++i) { + const double& w_i = weights[i]; + reg += l2 * w_i * w_i; + g[i] += 2 * l2 * w_i; + } + return reg; + } + + void GradAdd(const SparseVector<float>& fx, + const unsigned y, + const double scale, + double* acc) const { + acc[y] += scale; // class bias + for (SparseVector<float>::const_iterator it = fx.begin(); + it != fx.end(); ++it) + acc[it->first + y * p + K - 1] += it->second * scale; + } + + const vector<TrainingInstance>& training; + const unsigned K, p; + const double l2; +}; + +struct UnivariateSquaredLoss : public BaseLoss { + UnivariateSquaredLoss( + const vector<TrainingInstance>& tr, + unsigned numfeats, + const double l2) : BaseLoss(tr, 2, numfeats, l2) {} + + // evaluate squared loss and gradient + double operator()(const vector<double>& x, double* g) const { + fill(g, g + x.size(), 0.0); + double cll = 0; + vector<double> dotprods(1); // univariate prediction + for (unsigned i = 0; i < training.size(); ++i) { + const SparseVector<float>& fmapx = training[i].x; + const double refy = training[i].y.value; + ComputeDotProducts(fmapx, x, &dotprods); + double diff = dotprods[0] - refy; + cll += diff * diff; + + double scale = 2 * diff; + GradAdd(fmapx, 0, scale, g); + } + double reg = ApplyRegularizationTerms(x, g); + return cll + reg; + } + + // return root mse + double Evaluate(const vector<TrainingInstance>& test, + const vector<double>& w) const { + vector<double> dotprods(1); // K-1 degrees of freedom + double mse = 0; + for (unsigned i = 0; i < test.size(); ++i) { + const SparseVector<float>& fmapx = test[i].x; + const float refy = test[i].y.value; + ComputeDotProducts(fmapx, w, &dotprods); + double diff = dotprods[0] - refy; + cerr << "line=" << (i+1) << " true=" << refy << " pred=" << dotprods[0] << endl; + mse += diff * diff; + } + mse /= test.size(); + return sqrt(mse); + } +}; + +struct MulticlassLogLoss : public BaseLoss { + MulticlassLogLoss( + const vector<TrainingInstance>& tr, + unsigned k, + unsigned numfeats, + const double l2) : BaseLoss(tr, k, numfeats, l2) {} + + // evaluate log loss and gradient + double operator()(const vector<double>& x, double* g) const { + fill(g, g + x.size(), 0.0); + vector<double> dotprods(K - 1); // K-1 degrees of freedom + vector<prob_t> probs(K); + double cll = 0; + for (unsigned i = 0; i < training.size(); ++i) { + const SparseVector<float>& fmapx = training[i].x; + const unsigned refy = training[i].y.label; + //cerr << "FMAP: " << fmapx << endl; + ComputeDotProducts(fmapx, x, &dotprods); + prob_t z; + for (unsigned j = 0; j < dotprods.size(); ++j) + z += (probs[j] = prob_t(dotprods[j], init_lnx())); + z += (probs.back() = prob_t::One()); + for (unsigned y = 0; y < probs.size(); ++y) { + probs[y] /= z; + //cerr << " p(y=" << y << ")=" << probs[y].as_float() << "\tz=" << z << endl; + } + cll -= log(probs[refy]); // log p(y | x) + + for (unsigned y = 0; y < dotprods.size(); ++y) { + double scale = probs[y].as_float(); + if (y == refy) { scale -= 1.0; } + GradAdd(fmapx, y, scale, g); + } + } + double reg = ApplyRegularizationTerms(x, g); + return cll + reg; + } + + double Evaluate(const vector<TrainingInstance>& test, + const vector<double>& w) const { + vector<double> dotprods(K - 1); // K-1 degrees of freedom + double correct = 0; + for (unsigned i = 0; i < test.size(); ++i) { + const SparseVector<float>& fmapx = test[i].x; + const unsigned refy = test[i].y.label; + ComputeDotProducts(fmapx, w, &dotprods); + double best = 0; + unsigned besty = dotprods.size(); + for (unsigned y = 0; y < dotprods.size(); ++y) + if (dotprods[y] > best) { best = dotprods[y]; besty = y; } + if (refy == besty) { ++correct; } + } + return correct / test.size(); + } +}; + +template <class LossFunction> +double LearnParameters(LossFunction& loss, + const double l1, + const unsigned l1_start, + const unsigned memory_buffers, + const double eps, + vector<double>* px) { + LBFGS<LossFunction> lbfgs(px, loss, memory_buffers, l1, l1_start, eps); + lbfgs.MinimizeFunction(); + return 0; +} + +int main(int argc, char** argv) { + po::variables_map conf; + InitCommandLine(argc, argv, &conf); + string line; + double l1 = conf["l1"].as<double>(); + double l2 = conf["l2"].as<double>(); + const unsigned memory_buffers = conf["memory_buffers"].as<unsigned>(); + const double epsilon = conf["epsilon"].as<double>(); + if (l1 < 0.0) { + cerr << "L1 strength must be >= 0\n"; + return 1; + } + if (l2 < 0.0) { + cerr << "L2 strength must be >= 0\n"; + return 2; + } + + const bool is_continuous = conf.count("linear"); + const string xfile = conf["training_features"].as<string>(); + const string yfile = conf["training_responses"].as<string>(); + vector<string> labels; // only populated for non-continuous models + vector<TrainingInstance> training, test; + ReadLabeledInstances(xfile, yfile, is_continuous, &training, &labels); + if (conf.count("test_features")) { + const string txfile = conf["test_features"].as<string>(); + const string tyfile = conf["test_responses"].as<string>(); + ReadLabeledInstances(txfile, tyfile, is_continuous, &test, &labels); + } + + if (conf.count("weights")) { + cerr << "Initial weights are not implemented, please implement." << endl; + // TODO read weights for categorical and continuous predictions + // can't use normal cdec weight framework + abort(); + } + + cerr << " Number of features: " << FD::NumFeats() << endl; + cerr << "Number of training examples: " << training.size() << endl; + const unsigned p = FD::NumFeats(); + cout.precision(15); + + if (conf.count("linear")) { // linear regression + vector<double> weights(1 + FD::NumFeats(), 0.0); + cerr << " Number of parameters: " << weights.size() << endl; + UnivariateSquaredLoss loss(training, p, l2); + LearnParameters(loss, l1, 1, memory_buffers, epsilon, &weights); + + if (test.size()) + cerr << "Held-out root MSE: " << loss.Evaluate(test, weights) << endl; + + cout << p << "\t***CONTINUOUS***" << endl; + cout << "***BIAS***\t" << weights[0] << endl; + for (unsigned f = 0; f < p; ++f) { + const double w = weights[1 + f]; + if (w) + cout << FD::Convert(f) << "\t" << w << endl; + } + } else { // logistic regression + vector<double> weights((1 + FD::NumFeats()) * (labels.size() - 1), 0.0); + cerr << " Number of parameters: " << weights.size() << endl; + cerr << " Number of labels: " << labels.size() << endl; + const unsigned K = labels.size(); + const unsigned km1 = K - 1; + MulticlassLogLoss loss(training, K, p, l2); + LearnParameters(loss, l1, km1, memory_buffers, epsilon, &weights); + + if (test.size()) + cerr << "Held-out accuracy: " << loss.Evaluate(test, weights) << endl; + + cout << p << "\t***CATEGORICAL***"; + for (unsigned y = 0; y < K; ++y) + cout << '\t' << labels[y]; + cout << endl; + for (unsigned y = 0; y < km1; ++y) + cout << labels[y] << "\t***BIAS***\t" << weights[y] << endl; + for (unsigned y = 0; y < km1; ++y) { + for (unsigned f = 0; f < p; ++f) { + const double w = weights[km1 + y * p + f]; + if (w) + cout << labels[y] << "\t" << FD::Convert(f) << "\t" << w << endl; + } + } + } + + return 0; +} + diff --git a/creg/json_feature_map_lexer.h b/creg/json_feature_map_lexer.h new file mode 100644 index 00000000..3324aa29 --- /dev/null +++ b/creg/json_feature_map_lexer.h @@ -0,0 +1,15 @@ +#ifndef _RULE_LEXER_H_ +#define _RULE_LEXER_H_ + +#include <iostream> +#include <string> + +#include "sparse_vector.h" + +struct JSONFeatureMapLexer { + typedef void (*FeatureMapCallback)(const std::string& id, const SparseVector<float>& fmap, void* extra); + static void ReadRules(std::istream* in, FeatureMapCallback func, void* extra); +}; + +#endif + diff --git a/creg/json_feature_map_lexer.ll b/creg/json_feature_map_lexer.ll new file mode 100644 index 00000000..cbb6d9a9 --- /dev/null +++ b/creg/json_feature_map_lexer.ll @@ -0,0 +1,132 @@ +%option nounput +%{ + +#include "json_feature_map_lexer.h" +#include "fdict.h" +#include "fast_sparse_vector.h" + +#define YY_DECL int json_fmap_yylex (void) +#undef YY_INPUT +#define YY_INPUT(buf, result, max_size) (result = jfmap_stream->read(buf, max_size).gcount()) +#define YY_SKIP_YYWRAP 1 +int yywrap() { return 1; } + +JSONFeatureMapLexer::FeatureMapCallback json_fmap_callback = NULL; +void* json_fmap_callback_extra = NULL; +std::istream* jfmap_stream = NULL; +bool fl = true; +unsigned spos = 0; +char featname[16000]; +#define MAX_FEATS 20000 +std::pair<int, float> featmap[MAX_FEATS]; +unsigned curfeat = 0; +std::string instid; + +inline unsigned unicode_escape_to_utf8(uint16_t w1, uint16_t w2, char* putf8) { + uint32_t cp; + if((w1 & 0xfc00) == 0xd800) { + if((w2 & 0xfc00) == 0xdc00) { + cp = 0x10000 + (((static_cast<uint32_t>(w1) & 0x3ff) << 10) | (w2 & 0x3ff)); + } else { + abort(); + } + } else { + cp = w1; + } + + + if(cp < 0x80) { + putf8[0] = static_cast<char>(cp); + return 1; + } else if(cp < 0x0800) { + putf8[0] = 0xc0 | ((cp >> 6) & 0x1f); + putf8[1] = 0x80 | (cp & 0x3f); + return 2; + } else if(cp < 0x10000) { + putf8[0] = 0xe0 | ((cp >> 6) & 0x0f); + putf8[1] = 0x80 | ((cp >> 6) & 0x3f); + putf8[2] = 0x80 | (cp & 0x3f); + return 3; + } else if(cp < 0x1fffff) { + putf8[0] = 0xf0 | ((cp >> 18) & 0x07); + putf8[1] = 0x80 | ((cp >> 12) & 0x3f); + putf8[2] = 0x80 | ((cp >> 6) & 0x3f); + putf8[3] = 0x80 | (cp & 0x3f); + return 4; + } else { + abort(); + } + return 0; +} + +%} + +ID [^ \t\n\r]+ +HEX_D [a-fA-F0-9] +INT [-]?[0-9]+ +DOUBLE {INT}((\.[0-9]+)?([eE][-+]?[0-9]+)?) +WS [ \t\r\n] +LCB [{] +RCB [}] +UNESCAPED_CH [^\"\\\b\n\r\f\t] + +%x JSON PREVAL STRING JSONVAL POSTVAL DOUBLE +%% + +<INITIAL>{ID} { instid = yytext; BEGIN(JSON); } + +<JSON>{WS}*{LCB}{WS}* { BEGIN(PREVAL); } + +<PREVAL>\" { BEGIN(STRING); spos=0; } + +<STRING>\" { featname[spos] = 0; + featmap[curfeat].first = FD::Convert(featname); + BEGIN(JSONVAL); + } +<STRING>{UNESCAPED_CH} { featname[spos++] = yytext[0]; } +<STRING>\\\" { featname[spos++] = '"'; } +<STRING>\\\\ { featname[spos++] = '\\'; } +<STRING>\\\/ { featname[spos++] = '/'; } +<STRING>\\b { } +<STRING>\\f { } +<STRING>\\n { } +<STRING>\\r { } +<STRING>\\t { } +<STRING>\\u{HEX_D}{HEX_D}{HEX_D}{HEX_D} { abort(); + } + +<JSONVAL>{WS}*:{WS}* { BEGIN(DOUBLE); } +<DOUBLE>{DOUBLE} { featmap[curfeat++].second = strtod(yytext, 0); + BEGIN(POSTVAL); } + +<POSTVAL>{WS}*,{WS}* { BEGIN(PREVAL); } +<POSTVAL>{WS}*{RCB}\n* { + const SparseVector<float> x(&featmap[0], &featmap[curfeat]); + json_fmap_callback(instid, x, json_fmap_callback_extra); + curfeat = 0; + BEGIN(INITIAL); + } + +<PREVAL,POSTVAL,DOUBLE,JSONVAL,INITIAL>. { std::cerr << "bad input: " << yytext << std::endl; abort(); } + +%% + +void JSONFeatureMapLexer::ReadRules(std::istream* in, FeatureMapCallback func, void* extra) { + json_fmap_callback = func; + json_fmap_callback_extra = extra; + jfmap_stream = in; + json_fmap_yylex(); +} + +#if 0 +void cb(const std::string& id, const SparseVector<float>& fmap, void* extra) { + (void) extra; + static int cc = 0; + cc++; +} + +int main() { + JSONFeatureMapLexer::ReadRules(&std::cin, cb, NULL); +} +#endif + diff --git a/creg/test_data/auto-mpg.testfeat b/creg/test_data/auto-mpg.testfeat new file mode 100644 index 00000000..91c21e99 --- /dev/null +++ b/creg/test_data/auto-mpg.testfeat @@ -0,0 +1,93 @@ +test1_fiat_124b {"horsepower": 76.0, "acceleration": 14.5, "cylinders": 4.0, "displacement": 88.0, "weight": 2065.0} +test2_dodge_aspen {"horsepower": 110.0, "acceleration": 18.7, "cylinders": 6.0, "displacement": 225.0, "weight": 3620.0} +test3_toyota_celica_gt_liftback {"horsepower": 95.0, "acceleration": 14.8, "cylinders": 4.0, "displacement": 134.0, "weight": 2515.0} +test4_amc_matador {"horsepower": 110.0, "acceleration": 18.0, "cylinders": 6.0, "displacement": 258.0, "weight": 3632.0} +test5_audi_5000s_(diesel) {"horsepower": 67.0, "acceleration": 19.9, "cylinders": 5.0, "displacement": 121.0, "weight": 2950.0} +test6_datsun_310 {"horsepower": 65.0, "acceleration": 16.4, "cylinders": 4.0, "displacement": 86.0, "weight": 2019.0} +test7_chevrolet_woody {"horsepower": 60.0, "acceleration": 22.1, "cylinders": 4.0, "displacement": 98.0, "weight": 2164.0} +test8_volkswagen_1131_deluxe_sedan {"horsepower": 46.0, "acceleration": 20.5, "cylinders": 4.0, "displacement": 97.0, "weight": 1835.0} +test9_plymouth_satellite_sebring {"horsepower": 105.0, "acceleration": 16.5, "cylinders": 6.0, "displacement": 225.0, "weight": 3613.0} +test10_amc_matador {"horsepower": 120.0, "acceleration": 13.9, "cylinders": 8.0, "displacement": 304.0, "weight": 3962.0} +test11_chevrolet_chevette {"horsepower": 52.0, "acceleration": 22.2, "cylinders": 4.0, "displacement": 85.0, "weight": 2035.0} +test12_buick_century_special {"horsepower": 105.0, "acceleration": 15.8, "cylinders": 6.0, "displacement": 231.0, "weight": 3380.0} +test13_ford_escort_2h {"horsepower": 65.0, "acceleration": 20.7, "cylinders": 4.0, "displacement": 98.0, "weight": 2380.0} +test14_ford_torino_500 {"horsepower": 88.0, "acceleration": 15.5, "cylinders": 6.0, "displacement": 250.0, "weight": 3302.0} +test15_dodge_aries_wagon_(sw) {"horsepower": 92.0, "acceleration": 14.4, "cylinders": 4.0, "displacement": 156.0, "weight": 2620.0} +test16_plymouth_valiant {"horsepower": 105.0, "acceleration": 16.5, "cylinders": 6.0, "displacement": 225.0, "weight": 3121.0} +test17_amc_pacer {"horsepower": 90.0, "acceleration": 17.0, "cylinders": 6.0, "displacement": 232.0, "weight": 3211.0} +test18_honda_civic {"horsepower": 97.0, "acceleration": 15.0, "cylinders": 4.0, "displacement": 120.0, "weight": 2489.0} +test19_ford_ltd {"horsepower": 148.0, "acceleration": 13.5, "cylinders": 8.0, "displacement": 351.0, "weight": 4657.0} +test20_volkswagen_rabbit {"horsepower": 70.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 90.0, "weight": 1937.0} +test21_honda_civic_1500_gl {"horsepower": 67.0, "acceleration": 13.8, "cylinders": 4.0, "displacement": 91.0, "weight": 1850.0} +test22_chevrolet_impala {"horsepower": 165.0, "acceleration": 12.0, "cylinders": 8.0, "displacement": 350.0, "weight": 4209.0} +test23_chevrolet_chevette {"horsepower": 63.0, "acceleration": 17.0, "cylinders": 4.0, "displacement": 98.0, "weight": 2051.0} +test24_amc_concord {"horsepower": 90.0, "acceleration": 17.2, "cylinders": 6.0, "displacement": 232.0, "weight": 3210.0} +test25_ford_pinto {"horsepower": 83.0, "acceleration": 17.0, "cylinders": 4.0, "displacement": 140.0, "weight": 2639.0} +test26_ford_country_squire_(sw) {"horsepower": 142.0, "acceleration": 14.3, "cylinders": 8.0, "displacement": 351.0, "weight": 4054.0} +test27_plymouth_valiant_custom {"horsepower": 95.0, "acceleration": 16.0, "cylinders": 6.0, "displacement": 225.0, "weight": 3264.0} +test28_chevy_s-10 {"horsepower": 82.0, "acceleration": 19.4, "cylinders": 4.0, "displacement": 119.0, "weight": 2720.0} +test29_maxda_rx3 {"horsepower": 90.0, "acceleration": 13.5, "cylinders": 3.0, "displacement": 70.0, "weight": 2124.0} +test30_plymouth_sapporo {"horsepower": 105.0, "acceleration": 16.7, "cylinders": 4.0, "displacement": 156.0, "weight": 2745.0} +test31_amc_hornet {"horsepower": 90.0, "acceleration": 17.6, "cylinders": 6.0, "displacement": 232.0, "weight": 3085.0} +test32_chevrolet_caprice_classic {"horsepower": 145.0, "acceleration": 12.5, "cylinders": 8.0, "displacement": 305.0, "weight": 3880.0} +test33_pontiac_sunbird_coupe {"horsepower": 88.0, "acceleration": 16.0, "cylinders": 4.0, "displacement": 151.0, "weight": 2740.0} +test34_mercury_marquis_brougham {"horsepower": 198.0, "acceleration": 11.5, "cylinders": 8.0, "displacement": 429.0, "weight": 4952.0} +test35_mercury_monarch_ghia {"horsepower": 139.0, "acceleration": 12.8, "cylinders": 8.0, "displacement": 302.0, "weight": 3570.0} +test36_ford_country_squire_(sw) {"horsepower": 170.0, "acceleration": 12.0, "cylinders": 8.0, "displacement": 400.0, "weight": 4746.0} +test37_audi_fox {"horsepower": 83.0, "acceleration": 16.5, "cylinders": 4.0, "displacement": 98.0, "weight": 2219.0} +test38_triumph_tr7_coupe {"horsepower": 88.0, "acceleration": 15.1, "cylinders": 4.0, "displacement": 122.0, "weight": 2500.0} +test39_dodge_d100 {"horsepower": 150.0, "acceleration": 14.0, "cylinders": 8.0, "displacement": 318.0, "weight": 3755.0} +test40_mercury_cougar_brougham {"horsepower": 130.0, "acceleration": 14.9, "cylinders": 8.0, "displacement": 302.0, "weight": 4295.0} +test41_pontiac_phoenix_lj {"horsepower": 105.0, "acceleration": 19.2, "cylinders": 6.0, "displacement": 231.0, "weight": 3535.0} +test42_vw_rabbit_custom {"horsepower": 71.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 89.0, "weight": 1925.0} +test43_peugeot_504 {"horsepower": 87.0, "acceleration": 17.5, "cylinders": 4.0, "displacement": 110.0, "weight": 2672.0} +test44_datsun_310_gx {"horsepower": 67.0, "acceleration": 16.2, "cylinders": 4.0, "displacement": 91.0, "weight": 1995.0} +test45_dodge_monaco_(sw) {"horsepower": 180.0, "acceleration": 11.5, "cylinders": 8.0, "displacement": 383.0, "weight": 4955.0} +test46_chevrolet_monza_2+2 {"horsepower": 110.0, "acceleration": 13.5, "cylinders": 8.0, "displacement": 262.0, "weight": 3221.0} +test47_capri_ii {"horsepower": 92.0, "acceleration": 14.9, "cylinders": 4.0, "displacement": 140.0, "weight": 2572.0} +test48_mazda_rx2_coupe {"horsepower": 97.0, "acceleration": 13.5, "cylinders": 3.0, "displacement": 70.0, "weight": 2330.0} +test49_plymouth_fury {"horsepower": 95.0, "acceleration": 19.0, "cylinders": 6.0, "displacement": 225.0, "weight": 3785.0} +test50_plymouth_fury_iii {"horsepower": 215.0, "acceleration": 8.5, "cylinders": 8.0, "displacement": 440.0, "weight": 4312.0} +test51_dodge_st._regis {"horsepower": 135.0, "acceleration": 15.2, "cylinders": 8.0, "displacement": 318.0, "weight": 3830.0} +test52_amc_spirit_dl {"horsepower": 80.0, "acceleration": 15.0, "cylinders": 4.0, "displacement": 121.0, "weight": 2670.0} +test53_peugeot_504_(sw) {"horsepower": 87.0, "acceleration": 19.5, "cylinders": 4.0, "displacement": 120.0, "weight": 2979.0} +test54_chevroelt_chevelle_malibu {"horsepower": 105.0, "acceleration": 18.5, "cylinders": 6.0, "displacement": 250.0, "weight": 3897.0} +test55_opel_1900 {"horsepower": 90.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 116.0, "weight": 2123.0} +test56_dodge_challenger_se {"horsepower": 170.0, "acceleration": 10.0, "cylinders": 8.0, "displacement": 383.0, "weight": 3563.0} +test57_vw_pickup {"horsepower": 52.0, "acceleration": 24.6, "cylinders": 4.0, "displacement": 97.0, "weight": 2130.0} +test58_peugeot_604sl {"horsepower": 133.0, "acceleration": 15.8, "cylinders": 6.0, "displacement": 163.0, "weight": 3410.0} +test59_mazda_glc_4 {"horsepower": 68.0, "acceleration": 16.0, "cylinders": 4.0, "displacement": 91.0, "weight": 1985.0} +test60_audi_4000 {"horsepower": 78.0, "acceleration": 15.8, "cylinders": 4.0, "displacement": 97.0, "weight": 2188.0} +test61_plymouth_duster {"horsepower": 95.0, "acceleration": 16.5, "cylinders": 6.0, "displacement": 198.0, "weight": 3102.0} +test62_dodge_magnum_xe {"horsepower": 140.0, "acceleration": 13.7, "cylinders": 8.0, "displacement": 318.0, "weight": 4080.0} +test63_buick_century_limited {"horsepower": 110.0, "acceleration": 16.4, "cylinders": 6.0, "displacement": 181.0, "weight": 2945.0} +test64_chevrolet_monte_carlo_s {"horsepower": 145.0, "acceleration": 13.0, "cylinders": 8.0, "displacement": 350.0, "weight": 4082.0} +test65_amc_matador {"horsepower": 150.0, "acceleration": 11.5, "cylinders": 8.0, "displacement": 304.0, "weight": 3672.0} +test66_honda_accord {"horsepower": 75.0, "acceleration": 14.5, "cylinders": 4.0, "displacement": 107.0, "weight": 2205.0} +test67_plymouth_volare {"horsepower": 100.0, "acceleration": 17.2, "cylinders": 6.0, "displacement": 225.0, "weight": 3430.0} +test68_ford_galaxie_500 {"horsepower": 198.0, "acceleration": 10.0, "cylinders": 8.0, "displacement": 429.0, "weight": 4341.0} +test69_chevrolet_citation {"horsepower": 110.0, "acceleration": 12.6, "cylinders": 6.0, "displacement": 173.0, "weight": 2725.0} +test70_amc_ambassador_sst {"horsepower": 150.0, "acceleration": 11.5, "cylinders": 8.0, "displacement": 304.0, "weight": 3672.0} +test71_ford_thunderbird {"horsepower": 149.0, "acceleration": 14.5, "cylinders": 8.0, "displacement": 351.0, "weight": 4335.0} +test72_pontiac_phoenix {"horsepower": 90.0, "acceleration": 13.2, "cylinders": 4.0, "displacement": 151.0, "weight": 2556.0} +test73_vw_rabbit {"horsepower": 76.0, "acceleration": 14.7, "cylinders": 4.0, "displacement": 98.0, "weight": 2144.0} +test74_bmw_2002 {"horsepower": 113.0, "acceleration": 12.5, "cylinders": 4.0, "displacement": 121.0, "weight": 2234.0} +test75_dodge_colt {"horsepower": 105.0, "acceleration": 14.4, "cylinders": 4.0, "displacement": 156.0, "weight": 2800.0} +test76_mercury_capri_2000 {"horsepower": 86.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 122.0, "weight": 2220.0} +test77_ford_galaxie_500 {"horsepower": 153.0, "acceleration": 13.5, "cylinders": 8.0, "displacement": 351.0, "weight": 4154.0} +test78_volkswagen_rabbit_custom_diesel {"horsepower": 48.0, "acceleration": 21.5, "cylinders": 4.0, "displacement": 90.0, "weight": 1985.0} +test79_dodge_aspen_se {"horsepower": 100.0, "acceleration": 17.7, "cylinders": 6.0, "displacement": 225.0, "weight": 3651.0} +test80_mazda_glc_deluxe {"horsepower": 52.0, "acceleration": 19.4, "cylinders": 4.0, "displacement": 78.0, "weight": 1985.0} +test81_mazda_glc_custom {"horsepower": 68.0, "acceleration": 17.6, "cylinders": 4.0, "displacement": 91.0, "weight": 1970.0} +test82_audi_100ls {"horsepower": 91.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 114.0, "weight": 2582.0} +test83_oldsmobile_delta_88_royale {"horsepower": 160.0, "acceleration": 13.5, "cylinders": 8.0, "displacement": 350.0, "weight": 4456.0} +test84_ford_gran_torino {"horsepower": 137.0, "acceleration": 14.5, "cylinders": 8.0, "displacement": 302.0, "weight": 4042.0} +test85_plymouth_cricket {"horsepower": 70.0, "acceleration": 20.5, "cylinders": 4.0, "displacement": 91.0, "weight": 1955.0} +test86_plymouth_fury_iii {"horsepower": 150.0, "acceleration": 13.0, "cylinders": 8.0, "displacement": 318.0, "weight": 4096.0} +test87_plymouth_horizon {"horsepower": 70.0, "acceleration": 13.2, "cylinders": 4.0, "displacement": 105.0, "weight": 2200.0} +test88_peugeot_504 {"horsepower": 88.0, "acceleration": 21.9, "cylinders": 4.0, "displacement": 120.0, "weight": 3270.0} +test89_dodge_dart_custom {"horsepower": 150.0, "acceleration": 11.0, "cylinders": 8.0, "displacement": 318.0, "weight": 3399.0} +test90_pontiac_j2000_se_hatchback {"horsepower": 85.0, "acceleration": 16.2, "cylinders": 4.0, "displacement": 112.0, "weight": 2575.0} +test91_toyota_starlet {"horsepower": 58.0, "acceleration": 16.9, "cylinders": 4.0, "displacement": 79.0, "weight": 1755.0} +test92_mazda_glc_custom_l {"horsepower": 68.0, "acceleration": 18.2, "cylinders": 4.0, "displacement": 91.0, "weight": 2025.0} +test93_fiat_124_tc {"horsepower": 75.0, "acceleration": 14.0, "cylinders": 4.0, "displacement": 116.0, "weight": 2246.0} diff --git a/creg/test_data/auto-mpg.testresp b/creg/test_data/auto-mpg.testresp new file mode 100644 index 00000000..4f2cad37 --- /dev/null +++ b/creg/test_data/auto-mpg.testresp @@ -0,0 +1,93 @@ +test1_fiat_124b 30.0 +test2_dodge_aspen 18.6 +test3_toyota_celica_gt_liftback 21.1 +test4_amc_matador 16.0 +test5_audi_5000s_(diesel) 36.4 +test6_datsun_310 37.2 +test7_chevrolet_woody 24.5 +test8_volkswagen_1131_deluxe_sedan 26.0 +test9_plymouth_satellite_sebring 18.0 +test10_amc_matador 15.5 +test11_chevrolet_chevette 29.0 +test12_buick_century_special 20.6 +test13_ford_escort_2h 29.9 +test14_ford_torino_500 19.0 +test15_dodge_aries_wagon_(sw) 25.8 +test16_plymouth_valiant 18.0 +test17_amc_pacer 19.0 +test18_honda_civic 24.0 +test19_ford_ltd 14.0 +test20_volkswagen_rabbit 29.0 +test21_honda_civic_1500_gl 44.6 +test22_chevrolet_impala 14.0 +test23_chevrolet_chevette 30.5 +test24_amc_concord 19.4 +test25_ford_pinto 23.0 +test26_ford_country_squire_(sw) 15.5 +test27_plymouth_valiant_custom 19.0 +test28_chevy_s-10 31.0 +test29_maxda_rx3 18.0 +test30_plymouth_sapporo 23.2 +test31_amc_hornet 22.5 +test32_chevrolet_caprice_classic 17.5 +test33_pontiac_sunbird_coupe 24.5 +test34_mercury_marquis_brougham 12.0 +test35_mercury_monarch_ghia 20.2 +test36_ford_country_squire_(sw) 13.0 +test37_audi_fox 29.0 +test38_triumph_tr7_coupe 35.0 +test39_dodge_d100 13.0 +test40_mercury_cougar_brougham 15.0 +test41_pontiac_phoenix_lj 19.2 +test42_vw_rabbit_custom 31.9 +test43_peugeot_504 25.0 +test44_datsun_310_gx 38.0 +test45_dodge_monaco_(sw) 12.0 +test46_chevrolet_monza_2+2 20.0 +test47_capri_ii 25.0 +test48_mazda_rx2_coupe 19.0 +test49_plymouth_fury 18.0 +test50_plymouth_fury_iii 14.0 +test51_dodge_st._regis 18.2 +test52_amc_spirit_dl 27.4 +test53_peugeot_504_(sw) 21.0 +test54_chevroelt_chevelle_malibu 16.0 +test55_opel_1900 28.0 +test56_dodge_challenger_se 15.0 +test57_vw_pickup 44.0 +test58_peugeot_604sl 16.2 +test59_mazda_glc_4 34.1 +test60_audi_4000 34.3 +test61_plymouth_duster 20.0 +test62_dodge_magnum_xe 17.5 +test63_buick_century_limited 25.0 +test64_chevrolet_monte_carlo_s 15.0 +test65_amc_matador 14.0 +test66_honda_accord 36.0 +test67_plymouth_volare 20.5 +test68_ford_galaxie_500 15.0 +test69_chevrolet_citation 23.5 +test70_amc_ambassador_sst 17.0 +test71_ford_thunderbird 16.0 +test72_pontiac_phoenix 33.5 +test73_vw_rabbit 41.5 +test74_bmw_2002 26.0 +test75_dodge_colt 27.9 +test76_mercury_capri_2000 23.0 +test77_ford_galaxie_500 14.0 +test78_volkswagen_rabbit_custom_diesel 43.1 +test79_dodge_aspen_se 20.0 +test80_mazda_glc_deluxe 32.8 +test81_mazda_glc_custom 31.0 +test82_audi_100ls 20.0 +test83_oldsmobile_delta_88_royale 12.0 +test84_ford_gran_torino 14.0 +test85_plymouth_cricket 26.0 +test86_plymouth_fury_iii 14.0 +test87_plymouth_horizon 34.2 +test88_peugeot_504 19.0 +test89_dodge_dart_custom 15.0 +test90_pontiac_j2000_se_hatchback 31.0 +test91_toyota_starlet 39.1 +test92_mazda_glc_custom_l 37.0 +test93_fiat_124_tc 26.0 diff --git a/creg/test_data/auto-mpg.trainfeat b/creg/test_data/auto-mpg.trainfeat new file mode 100644 index 00000000..20b87d3f --- /dev/null +++ b/creg/test_data/auto-mpg.trainfeat @@ -0,0 +1,300 @@ +train1_buick_century_350 {"horsepower": 175.0, "acceleration": 13.0, "cylinders": 8.0, "displacement": 350.0, "weight": 4100.0} +train2_audi_100_ls {"horsepower": 90.0, "acceleration": 14.5, "cylinders": 4.0, "displacement": 107.0, "weight": 2430.0} +train3_chrysler_newport_royal {"horsepower": 190.0, "acceleration": 12.5, "cylinders": 8.0, "displacement": 400.0, "weight": 4422.0} +train4_mercury_zephyr_6 {"horsepower": 85.0, "acceleration": 18.2, "cylinders": 6.0, "displacement": 200.0, "weight": 2990.0} +train5_volkswagen_model_111 {"horsepower": 60.0, "acceleration": 19.0, "cylinders": 4.0, "displacement": 97.0, "weight": 1834.0} +train6_dodge_monaco_brougham {"horsepower": 145.0, "acceleration": 13.7, "cylinders": 8.0, "displacement": 318.0, "weight": 4140.0} +train7_mercedes-benz_240d {"horsepower": 67.0, "acceleration": 21.8, "cylinders": 4.0, "displacement": 146.0, "weight": 3250.0} +train8_datsun_510_(sw) {"horsepower": 92.0, "acceleration": 17.0, "cylinders": 4.0, "displacement": 97.0, "weight": 2288.0} +train9_opel_manta {"horsepower": 75.0, "acceleration": 15.5, "cylinders": 4.0, "displacement": 116.0, "weight": 2158.0} +train10_renault_12_(sw) {"horsepower": 69.0, "acceleration": 18.0, "cylinders": 4.0, "displacement": 96.0, "weight": 2189.0} +train11_chevrolet_nova {"horsepower": 100.0, "acceleration": 17.0, "cylinders": 6.0, "displacement": 250.0, "weight": 3336.0} +train12_plymouth_arrow_gs {"horsepower": 96.0, "acceleration": 15.5, "cylinders": 4.0, "displacement": 122.0, "weight": 2300.0} +train13_toyota_mark_ii {"horsepower": 108.0, "acceleration": 15.5, "cylinders": 6.0, "displacement": 156.0, "weight": 2930.0} +train14_chevrolet_caprice_classic {"horsepower": 150.0, "acceleration": 12.0, "cylinders": 8.0, "displacement": 400.0, "weight": 4464.0} +train15_ford_maverick {"horsepower": 88.0, 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"petal-length": 1.3, "petal-width": 0.2} +145 {"sepal-length": 4.6, "sepal-width": 3.4, "petal-length": 1.4, "petal-width": 0.3} +146 {"sepal-length": 5.7, "sepal-width": 2.6, "petal-length": 3.5, "petal-width": 1.0} +147 {"sepal-length": 5.8, "sepal-width": 2.8, "petal-length": 5.1, "petal-width": 2.4} +148 {"sepal-length": 7.7, "sepal-width": 2.8, "petal-length": 6.7, "petal-width": 2.0} +149 {"sepal-length": 6.3, "sepal-width": 2.9, "petal-length": 5.6, "petal-width": 1.8} diff --git a/creg/test_data/iris.testresp b/creg/test_data/iris.testresp new file mode 100644 index 00000000..0952e4da --- /dev/null +++ b/creg/test_data/iris.testresp @@ -0,0 +1,50 @@ +100 Iris-virginica +101 Iris-virginica +102 Iris-setosa +103 Iris-setosa +104 Iris-setosa +105 Iris-setosa +106 Iris-versicolor +107 Iris-versicolor +108 Iris-setosa +109 Iris-versicolor +110 Iris-versicolor +111 Iris-virginica +112 Iris-setosa +113 Iris-versicolor +114 Iris-setosa +115 Iris-virginica +116 Iris-setosa +117 Iris-versicolor +118 Iris-virginica +119 Iris-virginica +120 Iris-versicolor +121 Iris-setosa +122 Iris-setosa +123 Iris-virginica +124 Iris-versicolor +125 Iris-versicolor +126 Iris-versicolor +127 Iris-setosa +128 Iris-virginica +129 Iris-virginica +130 Iris-virginica +131 Iris-versicolor +132 Iris-versicolor +133 Iris-versicolor +134 Iris-setosa +135 Iris-virginica +136 Iris-virginica +137 Iris-versicolor +138 Iris-setosa +139 Iris-virginica +140 Iris-virginica +141 Iris-virginica +142 Iris-versicolor +143 Iris-setosa +144 Iris-setosa +145 Iris-setosa +146 Iris-versicolor +147 Iris-virginica +148 Iris-virginica +149 Iris-virginica diff --git a/creg/test_data/iris.trainfeat b/creg/test_data/iris.trainfeat new file mode 100644 index 00000000..a930a446 --- /dev/null +++ b/creg/test_data/iris.trainfeat @@ -0,0 +1,100 @@ +0 {"sepal-length": 5.4, "sepal-width": 3.0, "petal-length": 4.5, "petal-width": 1.5} +1 {"sepal-length": 5.0, "sepal-width": 3.4, "petal-length": 1.6, "petal-width": 0.4} +2 {"sepal-length": 5.0, "sepal-width": 3.3, "petal-length": 1.4, "petal-width": 0.2} +3 {"sepal-length": 5.7, "sepal-width": 2.8, "petal-length": 4.5, "petal-width": 1.3} +4 {"sepal-length": 6.4, "sepal-width": 3.1, "petal-length": 5.5, "petal-width": 1.8} +5 {"sepal-length": 7.9, "sepal-width": 3.8, "petal-length": 6.4, "petal-width": 2.0} +6 {"sepal-length": 5.9, "sepal-width": 3.2, "petal-length": 4.8, "petal-width": 1.8} +7 {"sepal-length": 6.7, "sepal-width": 2.5, "petal-length": 5.8, "petal-width": 1.8} +8 {"sepal-length": 6.7, "sepal-width": 3.1, "petal-length": 4.4, "petal-width": 1.4} +9 {"sepal-length": 6.3, "sepal-width": 2.5, "petal-length": 4.9, "petal-width": 1.5} +10 {"sepal-length": 6.1, "sepal-width": 2.9, "petal-length": 4.7, "petal-width": 1.4} +11 {"sepal-length": 6.3, "sepal-width": 3.3, "petal-length": 4.7, "petal-width": 1.6} +12 {"sepal-length": 6.7, "sepal-width": 3.1, "petal-length": 4.7, "petal-width": 1.5} +13 {"sepal-length": 6.2, "sepal-width": 2.8, 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+25 {"sepal-length": 4.4, "sepal-width": 2.9, "petal-length": 1.4, "petal-width": 0.2} +26 {"sepal-length": 4.9, "sepal-width": 3.0, "petal-length": 1.4, "petal-width": 0.2} +27 {"sepal-length": 5.4, "sepal-width": 3.4, "petal-length": 1.5, "petal-width": 0.4} +28 {"sepal-length": 5.8, "sepal-width": 2.7, "petal-length": 3.9, "petal-width": 1.2} +29 {"sepal-length": 5.6, "sepal-width": 2.5, "petal-length": 3.9, "petal-width": 1.1} +30 {"sepal-length": 5.1, "sepal-width": 3.5, "petal-length": 1.4, "petal-width": 0.3} +31 {"sepal-length": 5.6, "sepal-width": 2.7, "petal-length": 4.2, "petal-width": 1.3} +32 {"sepal-length": 5.1, "sepal-width": 3.5, "petal-length": 1.4, "petal-width": 0.2} +33 {"sepal-length": 6.4, "sepal-width": 2.7, "petal-length": 5.3, "petal-width": 1.9} +34 {"sepal-length": 5.8, "sepal-width": 4.0, "petal-length": 1.2, "petal-width": 0.2} +35 {"sepal-length": 5.2, "sepal-width": 3.4, "petal-length": 1.4, "petal-width": 0.2} +36 {"sepal-length": 7.6, "sepal-width": 3.0, "petal-length": 6.6, "petal-width": 2.1} +37 {"sepal-length": 5.8, "sepal-width": 2.7, "petal-length": 5.1, "petal-width": 1.9} +38 {"sepal-length": 6.0, "sepal-width": 2.2, "petal-length": 4.0, "petal-width": 1.0} +39 {"sepal-length": 7.7, "sepal-width": 3.0, "petal-length": 6.1, "petal-width": 2.3} +40 {"sepal-length": 5.1, "sepal-width": 3.7, "petal-length": 1.5, "petal-width": 0.4} +41 {"sepal-length": 6.1, "sepal-width": 2.6, "petal-length": 5.6, "petal-width": 1.4} +42 {"sepal-length": 6.7, "sepal-width": 3.1, "petal-length": 5.6, "petal-width": 2.4} +43 {"sepal-length": 7.7, "sepal-width": 3.8, "petal-length": 6.7, "petal-width": 2.2} +44 {"sepal-length": 5.1, "sepal-width": 3.3, "petal-length": 1.7, "petal-width": 0.5} +45 {"sepal-length": 6.3, "sepal-width": 2.8, "petal-length": 5.1, "petal-width": 1.5} +46 {"sepal-length": 5.0, "sepal-width": 2.0, "petal-length": 3.5, "petal-width": 1.0} +47 {"sepal-length": 5.1, "sepal-width": 3.8, "petal-length": 1.5, "petal-width": 0.3} +48 {"sepal-length": 4.9, "sepal-width": 3.1, "petal-length": 1.5, "petal-width": 0.1} +49 {"sepal-length": 6.1, "sepal-width": 3.0, "petal-length": 4.9, "petal-width": 1.8} +50 {"sepal-length": 6.4, "sepal-width": 2.8, "petal-length": 5.6, "petal-width": 2.1} +51 {"sepal-length": 6.5, "sepal-width": 3.0, "petal-length": 5.5, "petal-width": 1.8} +52 {"sepal-length": 6.1, "sepal-width": 2.8, "petal-length": 4.7, "petal-width": 1.2} +53 {"sepal-length": 6.1, "sepal-width": 2.8, "petal-length": 4.0, "petal-width": 1.3} +54 {"sepal-length": 4.9, "sepal-width": 3.1, "petal-length": 1.5, "petal-width": 0.1} +55 {"sepal-length": 6.8, "sepal-width": 2.8, "petal-length": 4.8, "petal-width": 1.4} +56 {"sepal-length": 6.3, "sepal-width": 2.7, "petal-length": 4.9, "petal-width": 1.8} +57 {"sepal-length": 4.6, "sepal-width": 3.2, "petal-length": 1.4, "petal-width": 0.2} +58 {"sepal-length": 6.3, "sepal-width": 3.4, "petal-length": 5.6, "petal-width": 2.4} +59 {"sepal-length": 5.7, "sepal-width": 4.4, "petal-length": 1.5, "petal-width": 0.4} +60 {"sepal-length": 6.4, "sepal-width": 2.9, "petal-length": 4.3, "petal-width": 1.3} +61 {"sepal-length": 7.2, "sepal-width": 3.6, "petal-length": 6.1, "petal-width": 2.5} +62 {"sepal-length": 5.8, "sepal-width": 2.7, "petal-length": 4.1, "petal-width": 1.0} +63 {"sepal-length": 6.0, "sepal-width": 3.0, "petal-length": 4.8, "petal-width": 1.8} +64 {"sepal-length": 4.7, "sepal-width": 3.2, "petal-length": 1.6, "petal-width": 0.2} +65 {"sepal-length": 6.9, "sepal-width": 3.2, "petal-length": 5.7, "petal-width": 2.3} +66 {"sepal-length": 6.4, "sepal-width": 3.2, "petal-length": 4.5, "petal-width": 1.5} +67 {"sepal-length": 6.9, "sepal-width": 3.1, "petal-length": 5.4, "petal-width": 2.1} +68 {"sepal-length": 5.2, "sepal-width": 3.5, "petal-length": 1.5, "petal-width": 0.2} +69 {"sepal-length": 5.3, "sepal-width": 3.7, "petal-length": 1.5, "petal-width": 0.2} +70 {"sepal-length": 5.5, "sepal-width": 2.4, "petal-length": 3.8, "petal-width": 1.1} +71 {"sepal-length": 4.8, "sepal-width": 3.4, "petal-length": 1.9, "petal-width": 0.2} +72 {"sepal-length": 5.7, "sepal-width": 2.8, "petal-length": 4.1, "petal-width": 1.3} +73 {"sepal-length": 4.9, "sepal-width": 2.4, "petal-length": 3.3, "petal-width": 1.0} +74 {"sepal-length": 6.2, "sepal-width": 2.2, "petal-length": 4.5, "petal-width": 1.5} +75 {"sepal-length": 6.7, "sepal-width": 3.3, "petal-length": 5.7, "petal-width": 2.5} +76 {"sepal-length": 6.1, "sepal-width": 3.0, "petal-length": 4.6, "petal-width": 1.4} +77 {"sepal-length": 4.6, "sepal-width": 3.6, "petal-length": 1.0, "petal-width": 0.2} +78 {"sepal-length": 7.0, "sepal-width": 3.2, "petal-length": 4.7, "petal-width": 1.4} +79 {"sepal-length": 6.6, "sepal-width": 2.9, "petal-length": 4.6, "petal-width": 1.3} +80 {"sepal-length": 5.4, "sepal-width": 3.7, "petal-length": 1.5, "petal-width": 0.2} +81 {"sepal-length": 4.8, "sepal-width": 3.0, "petal-length": 1.4, "petal-width": 0.3} +82 {"sepal-length": 7.2, "sepal-width": 3.0, "petal-length": 5.8, "petal-width": 1.6} +83 {"sepal-length": 7.1, "sepal-width": 3.0, "petal-length": 5.9, "petal-width": 2.1} +84 {"sepal-length": 6.9, "sepal-width": 3.1, "petal-length": 4.9, "petal-width": 1.5} +85 {"sepal-length": 4.8, "sepal-width": 3.0, "petal-length": 1.4, "petal-width": 0.1} +86 {"sepal-length": 7.3, "sepal-width": 2.9, "petal-length": 6.3, "petal-width": 1.8} +87 {"sepal-length": 6.0, "sepal-width": 2.7, "petal-length": 5.1, "petal-width": 1.6} +88 {"sepal-length": 6.8, "sepal-width": 3.2, "petal-length": 5.9, "petal-width": 2.3} +89 {"sepal-length": 4.6, "sepal-width": 3.1, "petal-length": 1.5, "petal-width": 0.2} +90 {"sepal-length": 4.8, "sepal-width": 3.1, "petal-length": 1.6, "petal-width": 0.2} +91 {"sepal-length": 5.0, "sepal-width": 2.3, "petal-length": 3.3, "petal-width": 1.0} +92 {"sepal-length": 6.9, "sepal-width": 3.1, "petal-length": 5.1, "petal-width": 2.3} +93 {"sepal-length": 5.7, "sepal-width": 3.0, "petal-length": 4.2, "petal-width": 1.2} +94 {"sepal-length": 5.1, "sepal-width": 3.8, "petal-length": 1.9, "petal-width": 0.4} +95 {"sepal-length": 6.0, "sepal-width": 2.9, "petal-length": 4.5, "petal-width": 1.5} +96 {"sepal-length": 4.8, "sepal-width": 3.4, "petal-length": 1.6, "petal-width": 0.2} +97 {"sepal-length": 5.2, "sepal-width": 4.1, "petal-length": 1.5, "petal-width": 0.1} +98 {"sepal-length": 5.6, "sepal-width": 2.9, "petal-length": 3.6, "petal-width": 1.3} +99 {"sepal-length": 5.8, "sepal-width": 2.6, "petal-length": 4.0, "petal-width": 1.2} diff --git a/creg/test_data/iris.trainresp b/creg/test_data/iris.trainresp new file mode 100644 index 00000000..d77bc6a2 --- /dev/null +++ b/creg/test_data/iris.trainresp @@ -0,0 +1,100 @@ +0 Iris-versicolor +1 Iris-setosa +2 Iris-setosa +3 Iris-versicolor +4 Iris-virginica +5 Iris-virginica +6 Iris-versicolor +7 Iris-virginica +8 Iris-versicolor +9 Iris-versicolor +10 Iris-versicolor +11 Iris-versicolor +12 Iris-versicolor +13 Iris-virginica +14 Iris-setosa +15 Iris-setosa +16 Iris-virginica +17 Iris-virginica +18 Iris-setosa +19 Iris-setosa +20 Iris-versicolor +21 Iris-virginica +22 Iris-virginica +23 Iris-setosa +24 Iris-virginica +25 Iris-setosa +26 Iris-setosa +27 Iris-setosa +28 Iris-versicolor +29 Iris-versicolor +30 Iris-setosa +31 Iris-versicolor +32 Iris-setosa +33 Iris-virginica +34 Iris-setosa +35 Iris-setosa +36 Iris-virginica +37 Iris-virginica +38 Iris-versicolor +39 Iris-virginica +40 Iris-setosa +41 Iris-virginica +42 Iris-virginica +43 Iris-virginica +44 Iris-setosa +45 Iris-virginica +46 Iris-versicolor +47 Iris-setosa +48 Iris-setosa +49 Iris-virginica +50 Iris-virginica +51 Iris-virginica +52 Iris-versicolor +53 Iris-versicolor +54 Iris-setosa +55 Iris-versicolor +56 Iris-virginica +57 Iris-setosa +58 Iris-virginica +59 Iris-setosa +60 Iris-versicolor +61 Iris-virginica +62 Iris-versicolor +63 Iris-virginica +64 Iris-setosa +65 Iris-virginica +66 Iris-versicolor +67 Iris-virginica +68 Iris-setosa +69 Iris-setosa +70 Iris-versicolor +71 Iris-setosa +72 Iris-versicolor +73 Iris-versicolor +74 Iris-versicolor +75 Iris-virginica +76 Iris-versicolor +77 Iris-setosa +78 Iris-versicolor +79 Iris-versicolor +80 Iris-setosa +81 Iris-setosa +82 Iris-virginica +83 Iris-virginica +84 Iris-versicolor +85 Iris-setosa +86 Iris-virginica +87 Iris-versicolor +88 Iris-virginica +89 Iris-setosa +90 Iris-setosa +91 Iris-versicolor +92 Iris-virginica +93 Iris-versicolor +94 Iris-setosa +95 Iris-versicolor +96 Iris-setosa +97 Iris-setosa +98 Iris-versicolor +99 Iris-versicolor diff --git a/training/liblbfgs/lbfgs++.h b/training/liblbfgs/lbfgs++.h index 342f9b0e..2b40c19b 100644 --- a/training/liblbfgs/lbfgs++.h +++ b/training/liblbfgs/lbfgs++.h @@ -16,28 +16,33 @@ template <typename Function> class LBFGS { public: - LBFGS(size_t n, // number of variables - const Function& f, // function to optimize - double l1_c = 0.0, // l1 penalty strength - size_t m = 10 // number of memory buffers - // TODO should use custom allocator here: + LBFGS(size_t n, // number of variables + const Function& f, // function to optimize + size_t m = 10, // number of memory buffers + double l1_c = 0.0, // l1 penalty strength + unsigned l1_start = 0, // l1 penalty starting index + double eps = 1e-5 // convergence epsilon + // TODO should use custom allocator here: ) : p_x(new std::vector<lbfgsfloatval_t>(n, 0.0)), owned(true), m_x(*p_x), func(f) { - Init(m, l1_c); + Init(m, l1_c, l1_start, eps); } // constructor where external vector storage for variables is used LBFGS(std::vector<lbfgsfloatval_t>* px, const Function& f, - double l1_c = 0.0, // l1 penalty strength - size_t m = 10 + size_t m = 10, // number of memory buffers + double l1_c = 0.0, // l1 penalty strength + unsigned l1_start = 0, // l1 penalty starting index + double eps = 1e-5 // convergence epsilon + // TODO should use custom allocator here: ) : p_x(px), owned(false), m_x(*p_x), func(f) { - Init(m, l1_c); + Init(m, l1_c, l1_start, eps); } ~LBFGS() { @@ -60,12 +65,14 @@ class LBFGS { } private: - void Init(size_t m, double l1_c) { + void Init(size_t m, double l1_c, unsigned l1_start, double eps) { lbfgs_parameter_init(¶m); param.m = m; + param.epsilon = eps; if (l1_c > 0.0) { param.linesearch = LBFGS_LINESEARCH_BACKTRACKING; - param.orthantwise_c = 1.0; + param.orthantwise_c = l1_c; + param.orthantwise_start = l1_start; } silence = false; } @@ -83,6 +90,7 @@ class LBFGS { lbfgsfloatval_t *g, const int n, const lbfgsfloatval_t step) { + (void) x; (void) n; (void) step; if (!silence) { ec++; std::cerr << '.'; } diff --git a/training/liblbfgs/ll_test.cc b/training/liblbfgs/ll_test.cc index 43c0f214..48bc0366 100644 --- a/training/liblbfgs/ll_test.cc +++ b/training/liblbfgs/ll_test.cc @@ -5,7 +5,7 @@ using namespace std; // Function must be lbfgsfloatval_t f(x.begin, x.end, g.begin) lbfgsfloatval_t func(const vector<lbfgsfloatval_t>& x, lbfgsfloatval_t* g) { - int i; + unsigned i; lbfgsfloatval_t fx = 0.0; for (i = 0;i < x.size();i += 2) { @@ -24,7 +24,7 @@ void Opt(F& f) { lbfgs.MinimizeFunction(); } -int main(int argc, char** argv) { +int main() { Opt(func); return 0; } diff --git a/utils/fast_sparse_vector.h b/utils/fast_sparse_vector.h index af832950..68caa704 100644 --- a/utils/fast_sparse_vector.h +++ b/utils/fast_sparse_vector.h @@ -7,8 +7,6 @@ // important: indexes are integers // important: iterators may return elements in any order -#include "config.h" - #include <cmath> #include <cstring> #include <climits> @@ -16,8 +14,9 @@ #include <cassert> #include <vector> -#include <boost/static_assert.hpp> +#include "config.h" +#include <boost/static_assert.hpp> #if HAVE_BOOST_ARCHIVE_TEXT_OARCHIVE_HPP #include <boost/serialization/map.hpp> #endif @@ -119,6 +118,17 @@ class FastSparseVector { std::memcpy(this, &other, sizeof(FastSparseVector)); if (is_remote_) data_.rbmap = new std::map<int, T>(*data_.rbmap); } + FastSparseVector(std::pair<int, T>* first, std::pair<int, T>* last) { + const ptrdiff_t n = last - first; + if (n <= LOCAL_MAX) { + is_remote_ = false; + local_size_ = n; + std::memcpy(data_.local, first, sizeof(std::pair<int, T>) * n); + } else { + is_remote_ = true; + data_.rbmap = new std::map<int, T>(first, last); + } + } void erase(int k) { if (is_remote_) { data_.rbmap->erase(k); |