integrated john's changes

1 files changed, 25 insertions, 318 deletions

diff --git a/vowpalwabbit/csoaa.cc b/vowpalwabbit/csoaa.cc
index fd202c24..df6b73c6 100644
--- a/vowpalwabbit/csoaa.cc
+++ b/vowpalwabbit/csoaa.cc
@@ -7,10 +7,9 @@ license as described in the file LICENSE.
 #include <math.h>
 #include <stdio.h>
 
-#include "csoaa.h"
+#include "cost_sensitive.h"
 #include "simple_label.h"
 #include "cache.h"
-#include "oaa.h"
 #include "v_hashmap.h"
 #include "parse_example.h"
 #include "vw.h"
@@ -19,295 +18,13 @@ using namespace std;
 
 using namespace LEARNER;
 
+using namespace COST_SENSITIVE;
+
 namespace CSOAA {
   struct csoaa{
     vw* all;
   };
 
-  void name_value(substring &s, v_array<substring>& name, float &v)
-  {
-    tokenize(':', s, name);
-    
-    switch (name.size()) {
-    case 0:
-    case 1:
-      v = 1.;
-      break;
-    case 2:
-      v = float_of_substring(name[1]);
-      if ( nanpattern(v))
-	{
-	  cerr << "error NaN value for: ";
-	  cerr.write(name[0].begin, name[0].end - name[0].begin);
-	  cerr << " terminating." << endl;
-	  throw exception();
-	}
-      break;
-    default:
-      cerr << "example with a wierd name.  What is '";
-      cerr.write(s.begin, s.end - s.begin);
-      cerr << "'?\n";
-    }
-  }
-
-  bool is_test_label(label* ld)
-  {
-    if (ld->costs.size() == 0)
-      return true;
-    for (unsigned int i=0; i<ld->costs.size(); i++)
-      if (FLT_MAX != ld->costs[i].x)
-        return false;
-    return true;
-  }
-  
-  char* bufread_label(label* ld, char* c, io_buf& cache)
-  {
-    size_t num = *(size_t *)c;
-    ld->costs.erase();
-    c += sizeof(size_t);
-    size_t total = sizeof(wclass)*num;
-    if (buf_read(cache, c, (int)total) < total) 
-      {
-        cout << "error in demarshal of cost data" << endl;
-        return c;
-      }
-    for (size_t i = 0; i<num; i++)
-      {
-        wclass temp = *(wclass *)c;
-        c += sizeof(wclass);
-        ld->costs.push_back(temp);
-      }
-  
-    return c;
-  }
-
-  size_t read_cached_label(shared_data*, void* v, io_buf& cache)
-  {
-    label* ld = (label*) v;
-    ld->costs.erase();
-    char *c;
-    size_t total = sizeof(size_t);
-    if (buf_read(cache, c, (int)total) < total) 
-      return 0;
-    c = bufread_label(ld,c, cache);
-  
-    return total;
-  }
-
-  float weight(void* v)
-  {
-    return 1.;
-  }
-
-  char* bufcache_label(label* ld, char* c)
-  {
-    *(size_t *)c = ld->costs.size();
-    c += sizeof(size_t);
-    for (unsigned int i = 0; i< ld->costs.size(); i++)
-      {
-        *(wclass *)c = ld->costs[i];
-        c += sizeof(wclass);
-      }
-    return c;
-  }
-
-  void cache_label(void* v, io_buf& cache)
-  {
-    char *c;
-    label* ld = (label*) v;
-    buf_write(cache, c, sizeof(size_t)+sizeof(wclass)*ld->costs.size());
-    bufcache_label(ld,c);
-  }
-
-  void default_label(void* v)
-  {
-    label* ld = (label*) v;
-    ld->costs.erase();
-  }
-
-  void delete_label(void* v)
-  {
-    label* ld = (label*)v;
-    ld->costs.delete_v();
-  }
-
-  void copy_label(void*&dst, void*src)
-  {
-    label*&ldD = (label*&)dst;
-    label* ldS = (label* )src;
-    copy_array(ldD->costs, ldS->costs);
-  }
-
-  bool substring_eq(substring ss, const char* str) {
-    size_t len_ss  = ss.end - ss.begin;
-    size_t len_str = strlen(str);
-    if (len_ss != len_str) return false;
-    return (strncmp(ss.begin, str, len_ss) == 0);
-  }
-
-  void parse_label(parser* p, shared_data* sd, void* v, v_array<substring>& words)
-  {
-    label* ld = (label*)v;
-
-    ld->costs.erase();
-    for (unsigned int i = 0; i < words.size(); i++) {
-      wclass f = {0.,0,0.,0.};
-      name_value(words[i], p->parse_name, f.x);
-      
-      if (p->parse_name.size() == 0)
-        cerr << "invalid cost: specification -- no names!" << endl;
-      else {
-        if (substring_eq(p->parse_name[0], "shared")) {
-          if (p->parse_name.size() == 1) {
-            f.x = -1;
-            f.weight_index = 0;
-          } else
-            cerr << "shared feature vectors should not have costs" << endl;
-        } else if (substring_eq(p->parse_name[0], "label")) {
-          if (p->parse_name.size() == 2) {
-            f.weight_index = (size_t)f.x;
-            f.x = -1;
-          } else
-            cerr << "label feature vectors must have label ids" << endl;
-        } else {
-          f.weight_index = 0;
-          if (p->parse_name.size() == 1 || p->parse_name.size() == 2 || p->parse_name.size() == 3) {
-            f.weight_index = (uint32_t)hashstring(p->parse_name[0], 0);
-            if (p->parse_name.size() == 1 && f.x >= 0)  // test examples are specified just by un-valued class #s
-              f.x = FLT_MAX;
-
-            if ((f.weight_index >= 1) && (f.weight_index <= sd->k) && (f.x >= 0)) {}  // normal example
-            else if ((f.weight_index >= 1) && (f.weight_index <= sd->k) && (f.x <= -1)) {}   // label definition
-            else if ((f.weight_index == 0) && (f.x <= -1)) {} // shared header
-            else
-              cerr << "invalid cost specification: " << f.weight_index << endl;
-          } else 
-            cerr << "malformed cost specification on '" << (p->parse_name[0].begin) << "'" << endl;
-        }
-        ld->costs.push_back(f);
-      }
-    }
-
-    if (words.size() == 0) {
-      if (sd->k != (uint32_t)-1) {
-        for (uint32_t i = 1; i <= sd->k; i++) {
-          wclass f = {FLT_MAX, i, 0., 0.};
-          ld->costs.push_back(f);
-        }
-      } else {
-        //cerr << "ldf test examples must have possible labels listed" << endl;
-        //throw exception();
-      }
-    }
-  }
-
-  void print_update(vw& all, bool is_test, example& ec)
-  {
-    if (all.sd->weighted_examples >= all.sd->dump_interval && !all.quiet && !all.bfgs)
-      {
-        char label_buf[32];
-        if (is_test)
-          strcpy(label_buf," unknown");
-        else
-          sprintf(label_buf," known");
-
-        if(!all.holdout_set_off && all.current_pass >= 1)
-        {
-          if(all.sd->holdout_sum_loss == 0. && all.sd->weighted_holdout_examples == 0.)
-            fprintf(stderr, " unknown   ");
-          else
-	    fprintf(stderr, "%-10.6f " , all.sd->holdout_sum_loss/all.sd->weighted_holdout_examples);
-
-          if(all.sd->holdout_sum_loss_since_last_dump == 0. && all.sd->weighted_holdout_examples_since_last_dump == 0.)
-            fprintf(stderr, " unknown   ");
-          else
-	    fprintf(stderr, "%-10.6f " , all.sd->holdout_sum_loss_since_last_dump/all.sd->weighted_holdout_examples_since_last_dump);
-        
-          fprintf(stderr, "%8ld %8.1f   %s %8lu %8lu h\n",
-                (long int)all.sd->example_number,
-                all.sd->weighted_examples,
-                label_buf,
-                (long unsigned int)ec.final_prediction,
-                (long unsigned int)ec.num_features);
-
-          all.sd->weighted_holdout_examples_since_last_dump = 0;
-          all.sd->holdout_sum_loss_since_last_dump = 0.0;
-        }
-        else
-          fprintf(stderr, "%-10.6f %-10.6f %8ld %8.1f   %s %8lu %8lu\n",
-                all.sd->sum_loss/all.sd->weighted_examples,
-                all.sd->sum_loss_since_last_dump / (all.sd->weighted_examples - all.sd->old_weighted_examples),
-                (long int)all.sd->example_number,
-                all.sd->weighted_examples,
-                label_buf,
-                (long unsigned int)ec.final_prediction,
-                (long unsigned int)ec.num_features);
-     
-        all.sd->sum_loss_since_last_dump = 0.0;
-        all.sd->old_weighted_examples = all.sd->weighted_examples;
-        VW::update_dump_interval(all);
-      }
-  }
-
-  void output_example(vw& all, example& ec)
-  {
-    label* ld = (label*)ec.ld;
-
-    float loss = 0.;
-    if (!is_test_label(ld))
-      {//need to compute exact loss
-        size_t pred = (size_t)ec.final_prediction;
-
-        float chosen_loss = FLT_MAX;
-        float min = FLT_MAX;
-        for (wclass *cl = ld->costs.begin; cl != ld->costs.end; cl ++) {
-          if (cl->weight_index == pred)
-            chosen_loss = cl->x;
-          if (cl->x < min)
-            min = cl->x;
-        }
-        if (chosen_loss == FLT_MAX)
-          cerr << "warning: csoaa predicted an invalid class" << endl;
-
-        loss = chosen_loss - min;
-      }
-
-    if(ec.test_only)
-      {
-        all.sd->weighted_holdout_examples += ec.global_weight;//test weight seen
-        all.sd->weighted_holdout_examples_since_last_dump += ec.global_weight;
-        all.sd->weighted_holdout_examples_since_last_pass += ec.global_weight;
-        all.sd->holdout_sum_loss += loss;
-        all.sd->holdout_sum_loss_since_last_dump += loss;
-        all.sd->holdout_sum_loss_since_last_pass += loss;//since last pass
-     }
-    else
-      {
-        all.sd->weighted_examples += 1.;
-        all.sd->total_features += ec.num_features;
-        all.sd->sum_loss += loss;
-        all.sd->sum_loss_since_last_dump += loss;    
-        all.sd->example_number++;
-      }
-
-    for (int* sink = all.final_prediction_sink.begin; sink != all.final_prediction_sink.end; sink++)
-      all.print((int)*sink, ec.final_prediction, 0, ec.tag);
-
-    if (all.raw_prediction > 0) {
-      string outputString;
-      stringstream outputStringStream(outputString);
-      for (unsigned int i = 0; i < ld->costs.size(); i++) {
-        wclass cl = ld->costs[i];
-        if (i > 0) outputStringStream << ' ';
-        outputStringStream << cl.weight_index << ':' << cl.partial_prediction;
-      }
-      //outputStringStream << endl;
-      all.print_text(all.raw_prediction, outputStringStream.str(), ec.tag);
-    }
-
-    print_update(all, is_test_label((label*)ec.ld), ec);
-  }
-
   template <bool is_learn>
   void predict_or_learn(csoaa& c, learner& base, example& ec) {
     vw* all = c.all;
@@ -382,16 +99,6 @@ namespace CSOAA {
     l->set_finish_example<csoaa,finish_example>();
     return l;
   }
-
-  bool example_is_test(example& ec)
-  {
-    v_array<CSOAA::wclass> costs = ((label*)ec.ld)->costs;
-    if (costs.size() == 0) return true;
-    for (size_t j=0; j<costs.size(); j++)
-      if (costs[j].x != FLT_MAX) return false;
-    return true;    
-  }
-
 }
 
 namespace CSOAA_AND_WAP_LDF {
@@ -419,7 +126,7 @@ namespace LabelDict {
   
   bool ec_is_label_definition(example& ec) // label defs look like "___:-1"
   {
-    v_array<CSOAA::wclass> costs = ((CSOAA::label*)ec.ld)->costs;
+    v_array<COST_SENSITIVE::wclass> costs = ((COST_SENSITIVE::label*)ec.ld)->costs;
     for (size_t j=0; j<costs.size(); j++)
       if (costs[j].x >= 0.) return false;
     if (ec.indices.size() == 0) return false;
@@ -430,7 +137,7 @@ namespace LabelDict {
 
   bool ec_is_example_header(example& ec)  // example headers look like "0:-1"
   {
-    v_array<CSOAA::wclass> costs = ((CSOAA::label*)ec.ld)->costs;
+    v_array<COST_SENSITIVE::wclass> costs = ((COST_SENSITIVE::label*)ec.ld)->costs;
     if (costs.size() != 1) return false;
     if (costs[0].weight_index != 0) return false;
     if (costs[0].x >= 0) return false;
@@ -549,9 +256,9 @@ namespace LabelDict {
   }
 }
 
-  inline bool cmp_wclass_ptr(const CSOAA::wclass* a, const CSOAA::wclass* b) { return a->x < b->x; }
+  inline bool cmp_wclass_ptr(const COST_SENSITIVE::wclass* a, const COST_SENSITIVE::wclass* b) { return a->x < b->x; }
 
-  void compute_wap_values(vector<CSOAA::wclass*> costs) {
+  void compute_wap_values(vector<COST_SENSITIVE::wclass*> costs) {
     std::sort(costs.begin(), costs.end(), cmp_wclass_ptr);
     costs[0]->wap_value = 0.;
     for (size_t i=1; i<costs.size(); i++)
@@ -622,7 +329,7 @@ namespace LabelDict {
 
   void make_single_prediction(vw& all, ldf& l, learner& base, example& ec, size_t*prediction, float*min_score, float*min_cost, float*max_cost) {
     label   *ld = (label*)ec.ld;
-    v_array<CSOAA::wclass> costs = ld->costs;
+    v_array<COST_SENSITIVE::wclass> costs = ld->costs;
     label_data simple_label;
 
     if (costs.size() == 0) {
@@ -667,14 +374,14 @@ namespace LabelDict {
   void do_actual_learning_wap(vw& all, ldf& l, learner& base, size_t start_K)
   {
     size_t K = l.ec_seq.size();
-    bool   isTest = CSOAA::example_is_test(*l.ec_seq[start_K]);
+    bool   isTest = COST_SENSITIVE::example_is_test(*l.ec_seq[start_K]);
     size_t prediction = 0;
     float  min_score = FLT_MAX;
 
     for (size_t k=start_K; k<K; k++) {
       example *ec = l.ec_seq.begin[k];
 
-      if (CSOAA::example_is_test(*ec) != isTest) {
+      if (COST_SENSITIVE::example_is_test(*ec) != isTest) {
         isTest = true;
         cerr << "warning: wap_ldf got mix of train/test data; assuming test" << endl;
       }
@@ -687,10 +394,10 @@ namespace LabelDict {
     }
 
     // do actual learning
-    vector<CSOAA::wclass*> all_costs;
+    vector<COST_SENSITIVE::wclass*> all_costs;
     if (is_learn && all.training && !isTest) {
       for (size_t k=start_K; k<K; k++) {
-        v_array<CSOAA::wclass> this_costs = ((label*)l.ec_seq.begin[k]->ld)->costs;
+        v_array<COST_SENSITIVE::wclass> this_costs = ((label*)l.ec_seq.begin[k]->ld)->costs;
         for (size_t j=0; j<this_costs.size(); j++)
           all_costs.push_back(&this_costs[j]);
       }
@@ -703,7 +410,7 @@ namespace LabelDict {
     for (size_t k1=start_K; k1<K; k1++) {
       example *ec1 = l.ec_seq.begin[k1];
       label   *ld1 = (label*)ec1->ld;
-      v_array<CSOAA::wclass> costs1 = ld1->costs;
+      v_array<COST_SENSITIVE::wclass> costs1 = ld1->costs;
       bool prediction_is_me = false;
       ec1->ld = &simple_label;
       float example_t1 = ec1->example_t;
@@ -716,7 +423,7 @@ namespace LabelDict {
           for (size_t k2=k1+1; k2<K; k2++) {
             example *ec2 = l.ec_seq.begin[k2];
             label   *ld2 = (label*)ec2->ld;
-            v_array<CSOAA::wclass> costs2 = ld2->costs;
+            v_array<COST_SENSITIVE::wclass> costs2 = ld2->costs;
 
             for (size_t j2=0; j2<costs2.size(); j2++) {
               if (costs2[j2].weight_index == (uint32_t)-1) continue;
@@ -759,7 +466,7 @@ namespace LabelDict {
   {
     size_t K = l.ec_seq.size();
     size_t prediction = 0;
-    bool   isTest = CSOAA::example_is_test(*l.ec_seq[start_K]);
+    bool   isTest = COST_SENSITIVE::example_is_test(*l.ec_seq[start_K]);
     float  min_score = FLT_MAX;
     float  min_cost  = FLT_MAX;
     float  max_cost  = -FLT_MAX;
@@ -768,7 +475,7 @@ namespace LabelDict {
     
     for (size_t k=start_K; k<K; k++) {
       example *ec = l.ec_seq.begin[k];
-      if (CSOAA::example_is_test(*ec) != isTest) {
+      if (COST_SENSITIVE::example_is_test(*ec) != isTest) {
         isTest = true;
         cerr << "warning: ldf got mix of train/test data; assuming test" << endl;
       }
@@ -786,7 +493,7 @@ namespace LabelDict {
     for (size_t k=start_K; k<K; k++) {
       example *ec = l.ec_seq.begin[k];
       label   *ld = (label*)ec->ld;
-      v_array<CSOAA::wclass> costs = ld->costs;
+      v_array<COST_SENSITIVE::wclass> costs = ld->costs;
 
       // learn
       label_data simple_label;
@@ -855,7 +562,7 @@ namespace LabelDict {
           features.push_back(fnew);
         }
 
-        v_array<CSOAA::wclass> costs = ((CSOAA::label*)l.ec_seq[i]->ld)->costs;
+        v_array<COST_SENSITIVE::wclass> costs = ((COST_SENSITIVE::label*)l.ec_seq[i]->ld)->costs;
         for (size_t j=0; j<costs.size(); j++) {
           size_t lab = costs[j].weight_index;
           LabelDict::set_label_features(l, lab, features);
@@ -886,7 +593,7 @@ namespace LabelDict {
   void output_example(vw& all, example& ec, bool& hit_loss)
   {
     label* ld = (label*)ec.ld;
-    v_array<CSOAA::wclass> costs = ld->costs;
+    v_array<COST_SENSITIVE::wclass> costs = ld->costs;
 
     if (example_is_newline(ec)) return;
     if (LabelDict::ec_is_example_header(ec)) return;
@@ -897,7 +604,7 @@ namespace LabelDict {
     float loss = 0.;
     size_t final_pred = (size_t)ec.final_prediction;
 
-    if (!CSOAA::example_is_test(ec)) {
+    if (!COST_SENSITIVE::example_is_test(ec)) {
       for (size_t j=0; j<costs.size(); j++) {
         if (hit_loss) break;
         if (final_pred == costs[j].weight_index) {
@@ -926,7 +633,7 @@ namespace LabelDict {
     }
     
 
-    CSOAA::print_update(all, CSOAA::example_is_test(ec), ec);
+    COST_SENSITIVE::print_update(all, COST_SENSITIVE::example_is_test(ec), ec);
   }
 
   void output_example_seq(vw& all, ldf& l)
@@ -968,7 +675,7 @@ namespace LabelDict {
     vw* all = l->all;
     l->base = &base;
 
-    if ((!all->training) || CSOAA::example_is_test(ec)) {
+    if ((!all->training) || COST_SENSITIVE::example_is_test(ec)) {
       size_t prediction = 0;
       float  min_score = FLT_MAX;
       make_single_prediction(*all, *l, base, ec, &prediction, &min_score, NULL, NULL);
@@ -992,7 +699,7 @@ namespace LabelDict {
       if (l->ec_seq.size() > 0)
         cerr << "warning: label definition encountered in data block -- ignoring data!" << endl;
     
-      if (!((!all->training) || CSOAA::example_is_test(ec))) {
+      if (!((!all->training) || COST_SENSITIVE::example_is_test(ec))) {
         l->ec_seq.erase();
         l->ec_seq.push_back(ec);
         do_actual_learning<is_learn>(*all, *l, base);
@@ -1057,7 +764,7 @@ namespace LabelDict {
     vw* all = l.all;
     l.base = &base;
 
-    bool is_test = CSOAA::example_is_test(ec) || !all->training;
+    bool is_test = COST_SENSITIVE::example_is_test(ec) || !all->training;
     
     if (is_test)
       make_single_prediction(*all, l, base, ec, NULL, NULL, NULL, NULL);
@@ -1130,7 +837,7 @@ namespace LabelDict {
       all.options_from_file.append(ldf_arg);
     }
 
-    all.p->lp = CSOAA::cs_label_parser;
+    all.p->lp = COST_SENSITIVE::cs_label_parser;
 
     all.sd->k = (uint32_t)-1;