various simplifications

11 files changed, 41 insertions, 56 deletions

diff --git a/vowpalwabbit/autolink.cc b/vowpalwabbit/autolink.cc
index 6d4f0106..7b3bebd8 100644
--- a/vowpalwabbit/autolink.cc
+++ b/vowpalwabbit/autolink.cc
@@ -1,8 +1,6 @@
 #include "reductions.h"
 #include "simple_label.h"
 
-using namespace LEARNER;
-
 namespace ALINK {
   const int autoconstant = 524267083;
   
@@ -11,8 +9,8 @@ namespace ALINK {
     uint32_t stride_shift;
   };
 
-  template <bool is_learn>
-  void predict_or_learn(autolink& b, base_learner& base, example& ec)
+  template <bool is_learn> 
+  void predict_or_learn(autolink& b, LEARNER::base_learner& base, example& ec)
   {
     base.predict(ec);
     float base_pred = ec.pred.scalar;
@@ -30,7 +28,6 @@ namespace ALINK {
 	}
     ec.total_sum_feat_sq += sum_sq;
 
-    // apply predict or learn
     if (is_learn)
       base.learn(ec);
     else
@@ -41,7 +38,7 @@ namespace ALINK {
     ec.total_sum_feat_sq -= sum_sq;
   }
 
-  base_learner* setup(vw& all, po::variables_map& vm)
+  LEARNER::base_learner* setup(vw& all, po::variables_map& vm)
   {
     autolink& data = calloc_or_die<autolink>();
     data.d = (uint32_t)vm["autolink"].as<size_t>();
@@ -49,7 +46,7 @@ namespace ALINK {
     
     *all.file_options << " --autolink " << data.d;
 
-    learner<autolink>& ret = init_learner(&data, all.l, predict_or_learn<true>, 
+    LEARNER::learner<autolink>& ret = init_learner(&data, all.l, predict_or_learn<true>, 
 					  predict_or_learn<false>);
     return make_base(ret);
   }
diff --git a/vowpalwabbit/binary.cc b/vowpalwabbit/binary.cc
index 0916dd6f..04810e26 100644
--- a/vowpalwabbit/binary.cc
+++ b/vowpalwabbit/binary.cc
@@ -1,13 +1,11 @@
+#include <float.h>
 #include "reductions.h"
 #include "multiclass.h"
 #include "simple_label.h"
 
-using namespace LEARNER;
-
 namespace BINARY {
-
   template <bool is_learn>
-  void predict_or_learn(char&, base_learner& base, example& ec) {
+  void predict_or_learn(char&, LEARNER::base_learner& base, example& ec) {
     if (is_learn)
       base.learn(ec);
     else
@@ -18,17 +16,22 @@ namespace BINARY {
     else
       ec.pred.scalar = -1;
 
-    if (ec.l.simple.label == ec.pred.scalar)
-      ec.loss = 0.;
-    else
-      ec.loss = ec.l.simple.weight;
+    if (ec.l.simple.label != FLT_MAX)
+      {
+	if (fabs(ec.l.simple.label) != 1.f)
+	  cout << "You are using a label not -1 or 1 with a loss function expecting that!" << endl;
+	else
+	  if (ec.l.simple.label == ec.pred.scalar)
+	    ec.loss = 0.;
+	  else
+	    ec.loss = ec.l.simple.weight; 
+      }
   }
 
-  base_learner* setup(vw& all, po::variables_map& vm)
-  {//parse and set arguments
-    all.sd->binary_label = true;
-    //Create new learner
-    learner<char>& ret = init_learner<char>(NULL, all.l, predict_or_learn<true>, predict_or_learn<false>);
+  LEARNER::base_learner* setup(vw& all, po::variables_map& vm)
+  {
+    LEARNER::learner<char>& ret = 
+      LEARNER::init_learner<char>(NULL, all.l, predict_or_learn<true>, predict_or_learn<false>);
     return make_base(ret);
   }
 }
diff --git a/vowpalwabbit/global_data.h b/vowpalwabbit/global_data.h
index fffe8b55..bdf76b46 100644
--- a/vowpalwabbit/global_data.h
+++ b/vowpalwabbit/global_data.h
@@ -154,7 +154,6 @@ struct shared_data {
   double holdout_sum_loss_since_last_pass;
   size_t holdout_best_pass; 
 
-  bool binary_label;
   uint32_t k;
 };
 
diff --git a/vowpalwabbit/kernel_svm.cc b/vowpalwabbit/kernel_svm.cc
index 607d90b6..9a88f17e 100644
--- a/vowpalwabbit/kernel_svm.cc
+++ b/vowpalwabbit/kernel_svm.cc
@@ -810,7 +810,7 @@ namespace KSVM
     string loss_function = "hinge";
     float loss_parameter = 0.0;
     delete all.loss;
-    all.loss = getLossFunction(&all, loss_function, (float)loss_parameter);
+    all.loss = getLossFunction(all, loss_function, (float)loss_parameter);
 
     svm_params& params = calloc_or_die<svm_params>();
     params.model = &calloc_or_die<svm_model>();
diff --git a/vowpalwabbit/log_multi.cc b/vowpalwabbit/log_multi.cc
index 19250a65..26f6b454 100644
--- a/vowpalwabbit/log_multi.cc
+++ b/vowpalwabbit/log_multi.cc
@@ -527,7 +527,7 @@ namespace LOG_MULTI
     string loss_function = "quantile"; 

     float loss_parameter = 0.5;

     delete(all.loss);

-    all.loss = getLossFunction(&all, loss_function, loss_parameter);

+    all.loss = getLossFunction(all, loss_function, loss_parameter);

 

     data.max_predictors = data.k - 1;

 

diff --git a/vowpalwabbit/loss_functions.cc b/vowpalwabbit/loss_functions.cc
index 4d67ae5e..6badc633 100644
--- a/vowpalwabbit/loss_functions.cc
+++ b/vowpalwabbit/loss_functions.cc
@@ -297,21 +297,18 @@ public:
   float tau;
 };
 
-loss_function* getLossFunction(void* a, string funcName, float function_parameter) {
-  vw* all=(vw*)a;
-  if(funcName.compare("squared") == 0 || funcName.compare("Huber") == 0) {
+loss_function* getLossFunction(vw& all, string funcName, float function_parameter) {
+  if(funcName.compare("squared") == 0 || funcName.compare("Huber") == 0) 
     return new squaredloss();
-  } else if(funcName.compare("classic") == 0){
+  else if(funcName.compare("classic") == 0)
     return new classic_squaredloss();
-  } else if(funcName.compare("hinge") == 0) {
-    all->sd->binary_label = true;
+  else if(funcName.compare("hinge") == 0) 
     return new hingeloss();
-  } else if(funcName.compare("logistic") == 0) {
-    if (all->set_minmax != noop_mm)
+  else if(funcName.compare("logistic") == 0) {
+    if (all.set_minmax != noop_mm)
       {
-	all->sd->min_label = -50;
-	all->sd->max_label = 50;
-	all->sd->binary_label = true;
+	all.sd->min_label = -50;
+	all.sd->max_label = 50;
       }
     return new logloss();
   } else if(funcName.compare("quantile") == 0 || funcName.compare("pinball") == 0 || funcName.compare("absolute") == 0) {
@@ -320,5 +317,4 @@ loss_function* getLossFunction(void* a, string funcName, float function_paramete
     cout << "Invalid loss function name: \'" << funcName << "\' Bailing!" << endl;
     throw exception();
   }
-  cout << "end getLossFunction" << endl;
 }
diff --git a/vowpalwabbit/loss_functions.h b/vowpalwabbit/loss_functions.h
index 421b3bfe..35b6f24b 100644
--- a/vowpalwabbit/loss_functions.h
+++ b/vowpalwabbit/loss_functions.h
@@ -8,8 +8,7 @@ license as described in the file LICENSE.
 #include "parse_primitives.h"
 
 struct shared_data;
-
-using namespace std;
+struct vw;
 
 class loss_function {
 
@@ -34,4 +33,4 @@ public :
 	virtual ~loss_function() {};
 };
 
-loss_function* getLossFunction(void*, string funcName, float function_parameter = 0);
+loss_function* getLossFunction(vw&, std::string funcName, float function_parameter = 0);
diff --git a/vowpalwabbit/nn.cc b/vowpalwabbit/nn.cc
index bf9bc020..bfab6009 100644
--- a/vowpalwabbit/nn.cc
+++ b/vowpalwabbit/nn.cc
@@ -356,7 +356,7 @@ CONVERSE: // That's right, I'm using goto.  So sue me.
                 << std::endl;
 
     n.finished_setup = false;
-    n.squared_loss = getLossFunction (0, "squared", 0);
+    n.squared_loss = getLossFunction (all, "squared", 0);
 
     n.xsubi = 0;
 
diff --git a/vowpalwabbit/parse_args.cc b/vowpalwabbit/parse_args.cc
index 9f5d071a..ef65345c 100644
--- a/vowpalwabbit/parse_args.cc
+++ b/vowpalwabbit/parse_args.cc
@@ -600,7 +600,7 @@ void parse_example_tweaks(vw& all, po::variables_map& vm)
   if(vm.count("quantile_tau"))
     loss_parameter = vm["quantile_tau"].as<float>();
 
-  all.loss = getLossFunction(&all, loss_function, (float)loss_parameter);
+  all.loss = getLossFunction(all, loss_function, (float)loss_parameter);
 
   if (all.l1_lambda < 0.) {
     cerr << "l1_lambda should be nonnegative: resetting from " << all.l1_lambda << " to 0" << endl;
diff --git a/vowpalwabbit/scorer.cc b/vowpalwabbit/scorer.cc
index e93eb84f..50645ed8 100644
--- a/vowpalwabbit/scorer.cc
+++ b/vowpalwabbit/scorer.cc
@@ -1,14 +1,11 @@
 #include <float.h>
-
 #include "reductions.h"
 
-using namespace LEARNER;
-
 namespace Scorer {
   struct scorer{ vw* all; };
 
   template <bool is_learn, float (*link)(float in)>
-  void predict_or_learn(scorer& s, base_learner& base, example& ec)
+  void predict_or_learn(scorer& s, LEARNER::base_learner& base, example& ec)
   {
     s.all->set_minmax(s.all->sd, ec.l.simple.label);
     
@@ -24,20 +21,17 @@ namespace Scorer {
   }
 
   // y = f(x) -> [0, 1]
-  float logistic(float in)
-  { return 1.f / (1.f + exp(- in)); }
+  float logistic(float in) { return 1.f / (1.f + exp(- in)); }
 
   // http://en.wikipedia.org/wiki/Generalized_logistic_curve
   // where the lower & upper asymptotes are -1 & 1 respectively
   // 'glf1' stands for 'Generalized Logistic Function with [-1,1] range'
   //    y = f(x) -> [-1, 1]
-  float glf1(float in)
-  { return 2.f / (1.f + exp(- in)) - 1.f; }
+  float glf1(float in) { return 2.f / (1.f + exp(- in)) - 1.f; }
 
-  float noop(float in)
-  { return in; }
+  float id(float in) { return in; }
 
-  base_learner* setup(vw& all, po::variables_map& vm)
+  LEARNER::base_learner* setup(vw& all, po::variables_map& vm)
   {
     scorer& s = calloc_or_die<scorer>();
     s.all = &all;
@@ -49,11 +43,11 @@ namespace Scorer {
 
     vm = add_options(all, link_opts);
 
-    learner<scorer>* l; 
+    LEARNER::learner<scorer>* l; 
 
     string link = vm["link"].as<string>();
     if (!vm.count("link") || link.compare("identity") == 0)
-      l = &init_learner(&s, all.l, predict_or_learn<true, noop>, predict_or_learn<false, noop>);
+      l = &init_learner(&s, all.l, predict_or_learn<true, id>, predict_or_learn<false, id>);
     else if (link.compare("logistic") == 0)
       {
 	*all.file_options << " --link=logistic ";
diff --git a/vowpalwabbit/simple_label.cc b/vowpalwabbit/simple_label.cc
index 3bf748de..150f95e9 100644
--- a/vowpalwabbit/simple_label.cc
+++ b/vowpalwabbit/simple_label.cc
@@ -96,9 +96,6 @@ void parse_simple_label(parser* p, shared_data* sd, void* v, v_array<substring>&
     cerr << "malformed example!\n";
     cerr << "words.size() = " << words.size() << endl;
   }
-  if (words.size() > 0 && sd->binary_label && fabs(ld->label) != 1.f)
-    cout << "You are using a label not -1 or 1 with a loss function expecting that!" << endl;
-
   count_label(ld->label);
 }