1 files changed, 97 insertions, 0 deletions
diff --git a/vowpalwabbit/vw_test.cc b/vowpalwabbit/vw_test.cc
new file mode 100644
index 00000000..734e148b
--- /dev/null
+++ b/vowpalwabbit/vw_test.cc
@@ -0,0 +1,97 @@
+/*
+Copyright (c) by respective owners including Yahoo!, Microsoft, and
+individual contributors. All rights reserved.  Released under a BSD
+license as described in the file LICENSE.
+ */
+
+#include <math.h>
+#include <iostream>
+#include <fstream>
+#include <float.h>
+#include <time.h>
+#ifdef _WIN32
+#include <WinSock2.h>
+#else
+#include <sys/socket.h>
+#include <arpa/inet.h>
+#endif
+#include <sys/timeb.h>
+#include "global_data.h"
+#include "parse_example.h"
+#include "parse_args.h"
+#include "accumulate.h"
+#include "vw.h"
+#include "searn.h"
+
+using namespace std;
+
+int main(int argc, char *argv[])
+{
+  vw *all = parse_args(argc, argv);
+  struct timeb t_start, t_end;
+  ftime(&t_start);
+  
+  if (!all->quiet && !all->bfgs && !all->searn)
+    {
+      const char * header_fmt = "%-10s %-10s %10s %11s %8s %8s %8s\n";
+      fprintf(stderr, header_fmt,
+	      "average", "since", "example", "example",
+	      "current", "current", "current");
+      fprintf(stderr, header_fmt,
+	      "loss", "last", "counter", "weight", "label", "predict", "features");
+      cerr.precision(5);
+    }
+
+  VW::start_parser(*all);
+
+  all->l.drive(all);
+
+  VW::end_parser(*all);
+  
+  ftime(&t_end);
+  double net_time = (int) (1000.0 * (t_end.time - t_start.time) + (t_end.millitm - t_start.millitm)); 
+  if(!all->quiet && all->span_server != "")
+    cerr<<"Net time taken by process = "<<net_time/(double)(1000)<<" seconds\n";
+
+  if(all->span_server != "") {
+    float loss = (float)all->sd->sum_loss;
+    all->sd->sum_loss = (double)accumulate_scalar(*all, all->span_server, loss);
+    float weighted_examples = (float)all->sd->weighted_examples;
+    all->sd->weighted_examples = (double)accumulate_scalar(*all, all->span_server, weighted_examples);
+    float weighted_labels = (float)all->sd->weighted_labels;
+    all->sd->weighted_labels = (double)accumulate_scalar(*all, all->span_server, weighted_labels);
+    float weighted_unlabeled_examples = (float)all->sd->weighted_unlabeled_examples;
+    all->sd->weighted_unlabeled_examples = (double)accumulate_scalar(*all, all->span_server, weighted_unlabeled_examples);
+    float example_number = (float)all->sd->example_number;
+    all->sd->example_number = (uint64_t)accumulate_scalar(*all, all->span_server, example_number);
+    float total_features = (float)all->sd->total_features;
+    all->sd->total_features = (uint64_t)accumulate_scalar(*all, all->span_server, total_features);
+  }
+
+  float weighted_labeled_examples = (float)(all->sd->weighted_examples - all->sd->weighted_unlabeled_examples);
+  float best_constant = (float)((all->sd->weighted_labels - all->initial_t) / weighted_labeled_examples);
+  float constant_loss = (best_constant*(1.0f - best_constant)*(1.0f - best_constant)
+			 + (1.0f - best_constant)*best_constant*best_constant);
+  
+  if (!all->quiet)
+    {
+      cerr.precision(4);
+      cerr << endl << "finished run";
+      cerr << endl << "number of examples = " << all->sd->example_number;
+      cerr << endl << "weighted example sum = " << all->sd->weighted_examples;
+      cerr << endl << "weighted label sum = " << all->sd->weighted_labels;
+      cerr << endl << "average loss = " << all->sd->sum_loss / all->sd->weighted_examples;
+      cerr << endl << "best constant = " << best_constant;
+      if (all->sd->min_label == 0. && all->sd->max_label == 1. && best_constant < 1. && best_constant > 0.)
+	cerr << endl << "best constant's loss = " << constant_loss;
+      cerr << endl << "total feature number = " << all->sd->total_features;
+      if (all->active_simulation)
+	cerr << endl << "total queries = " << all->sd->queries << endl;
+      cerr << endl;
+    }
+  
+  VW::finish(*all);
+  
+  return 0;
+}
+