13 files changed, 116 insertions, 0 deletions
diff --git a/dtrain/test/example/cdec.ini b/dtrain/test/example/cdec.ini
new file mode 100644
index 00000000..31a205c7
--- /dev/null
+++ b/dtrain/test/example/cdec.ini
@@ -0,0 +1,7 @@
+formalism=scfg
+add_pass_through_rules=true
+cubepruning_pop_limit=30
+scfg_max_span_limit=15
+feature_function=WordPenalty
+feature_function=KLanguageModel test/example/nc-wmt11.en.srilm.gz
+feature_function=RuleIdentityFeatures
diff --git a/dtrain/test/example/dtrain.ini b/dtrain/test/example/dtrain.ini
new file mode 100644
index 00000000..9b83193a
--- /dev/null
+++ b/dtrain/test/example/dtrain.ini
@@ -0,0 +1,14 @@
+decoder_config=test/example/cdec.ini
+k=100
+N=3
+gamma=0.00001
+epochs=2
+input=test/example/nc-1k-tabs.gz
+scorer=stupid_bleu
+output=-
+stop_after=10
+sample_from=kbest
+pair_sampling=108010
+select_weights=best
+print_weights=Glue WordPenalty LanguageModel LanguageModel_OOV PhraseModel_0 PhraseModel_1 PhraseModel_2 PhraseModel_3 PhraseModel_4 PassThrough
+tmp=/tmp
diff --git a/dtrain/test/example/nc-1k-tabs.gz b/dtrain/test/example/nc-1k-tabs.gz
new file mode 100644
index 00000000..45496cd8
--- /dev/null
+++ b/dtrain/test/example/nc-1k-tabs.gz
diff --git a/dtrain/test/example/nc-1k.gz b/dtrain/test/example/nc-1k.gz
new file mode 100644
index 00000000..f638a166
--- /dev/null
+++ b/dtrain/test/example/nc-1k.gz
diff --git a/dtrain/test/example/nc-wmt11.en.srilm.gz b/dtrain/test/example/nc-wmt11.en.srilm.gz
new file mode 100644
index 00000000..7ce81057
--- /dev/null
+++ b/dtrain/test/example/nc-wmt11.en.srilm.gz
diff --git a/dtrain/test/log_reg_dyer/bin_class.cc b/dtrain/test/log_reg_dyer/bin_class.cc
new file mode 100644
index 00000000..19bcde25
--- /dev/null
+++ b/dtrain/test/log_reg_dyer/bin_class.cc
@@ -0,0 +1,4 @@
+#include "bin_class.h"
+
+Objective::~Objective() {}
+
diff --git a/dtrain/test/log_reg_dyer/bin_class.h b/dtrain/test/log_reg_dyer/bin_class.h
new file mode 100644
index 00000000..3466109a
--- /dev/null
+++ b/dtrain/test/log_reg_dyer/bin_class.h
@@ -0,0 +1,22 @@
+#ifndef _BIN_CLASS_H_
+#define _BIN_CLASS_H_
+
+#include <vector>
+#include "sparse_vector.h"
+
+struct TrainingInstance {
+  // TODO add other info? loss for MIRA-type updates?
+  SparseVector<double> x_feature_map;
+  bool y;
+};
+
+struct Objective {
+  virtual ~Objective();
+
+  // returns f(x) and f'(x)
+  virtual double ObjectiveAndGradient(const SparseVector<double>& x,
+                  const std::vector<TrainingInstance>& training_instances,
+                  SparseVector<double>* g) const = 0;
+};
+
+#endif
diff --git a/dtrain/test/log_reg_dyer/log_reg.cc b/dtrain/test/log_reg_dyer/log_reg.cc
new file mode 100644
index 00000000..ec2331fe
--- /dev/null
+++ b/dtrain/test/log_reg_dyer/log_reg.cc
@@ -0,0 +1,39 @@
+#include "log_reg.h"
+
+#include <vector>
+#include <cmath>
+
+#include "sparse_vector.h"
+
+using namespace std;
+
+double LogisticRegression::ObjectiveAndGradient(const SparseVector<double>& x,
+                              const vector<TrainingInstance>& training_instances,
+                              SparseVector<double>* g) const {
+  double cll = 0;
+  for (int i = 0; i < training_instances.size(); ++i) {
+    const double dotprod = training_instances[i].x_feature_map.dot(x); // TODO no bias, if bias, add x[0]
+    double lp_false = dotprod;
+    double lp_true = -dotprod;
+    if (0 < lp_true) {
+      lp_true += log1p(exp(-lp_true));
+      lp_false = log1p(exp(lp_false));
+    } else {
+      lp_true = log1p(exp(lp_true));
+      lp_false += log1p(exp(-lp_false));
+    }
+    lp_true *= -1;
+    lp_false *= -1;
+    if (training_instances[i].y) {  // true label
+      cll -= lp_true;
+      (*g) -= training_instances[i].x_feature_map * exp(lp_false);
+      // (*g)[0] -= exp(lp_false); // bias
+    } else {                  // false label
+      cll -= lp_false;
+      (*g) += training_instances[i].x_feature_map * exp(lp_true);
+      // g += corpus[i].second * exp(lp_true);
+    }
+  }
+  return cll;
+}
+
diff --git a/dtrain/test/log_reg_dyer/log_reg.h b/dtrain/test/log_reg_dyer/log_reg.h
new file mode 100644
index 00000000..ecc560b8
--- /dev/null
+++ b/dtrain/test/log_reg_dyer/log_reg.h
@@ -0,0 +1,14 @@
+#ifndef _LOG_REG_H_
+#define _LOG_REG_H_
+
+#include <vector>
+#include "sparse_vector.h"
+#include "bin_class.h"
+
+struct LogisticRegression : public Objective {
+  double ObjectiveAndGradient(const SparseVector<double>& x,
+                              const std::vector<TrainingInstance>& training_instances,
+                              SparseVector<double>* g) const;
+};
+
+#endif
diff --git a/dtrain/test/test.in b/dtrain/test/test.in
new file mode 100644
index 00000000..4f53335e
--- /dev/null
+++ b/dtrain/test/test.in
@@ -0,0 +1,3 @@
+0	vorrichtung	means	[X] ||| vorrichtung ||| apparatus ||| LogP=0 ||| 0-0 __NEXT_RULE__ [X] ||| vorrichtung ||| means ||| LogP=-100 ||| 0-0
+1	Test	test	[X] ||| Test ||| test ||| LogP=0 ||| 0-0 __NEXT_RULE__ [X] ||| Test ||| xxx ||| LogP=-100 ||| 0-0
+2	kaputt	broken	
diff --git a/dtrain/test/toy/cdec.ini b/dtrain/test/toy/cdec.ini
new file mode 100644
index 00000000..98b02d44
--- /dev/null
+++ b/dtrain/test/toy/cdec.ini
@@ -0,0 +1,2 @@
+formalism=scfg
+add_pass_through_rules=true
diff --git a/dtrain/test/toy/dtrain.ini b/dtrain/test/toy/dtrain.ini
new file mode 100644
index 00000000..5bfa5b2d
--- /dev/null
+++ b/dtrain/test/toy/dtrain.ini
@@ -0,0 +1,9 @@
+decoder_config=test/toy/cdec.ini
+k=4
+N=3
+epochs=2
+input=test/toy/in
+scorer=stupid_bleu
+sample_from=forest
+output=-
+print_weights=logp use_shell use_house PassThrough
diff --git a/dtrain/test/toy/in b/dtrain/test/toy/in
new file mode 100644
index 00000000..d7b7d080
--- /dev/null
+++ b/dtrain/test/toy/in
@@ -0,0 +1,2 @@
+0	ich sah ein kleines haus	i saw a little house	[S] ||| [NP,1] [VP,2] ||| [1] [2] ||| logp=0	[NP] ||| ich ||| i ||| logp=0	[NP] ||| ein [NN,1] ||| a [1] ||| logp=0	[NN] ||| [JJ,1] haus ||| [1] house ||| logp=0 use_house=1	[NN] ||| [JJ,1] haus ||| [1] shell ||| logp=0 use_shell=1	[JJ] ||| kleines ||| small ||| logp=0	[JJ] ||| kleines ||| little ||| logp=0	[JJ] ||| grosses ||| big ||| logp=0	[JJ] ||| grosses ||| large ||| logp=0	[VP] ||| [V,1] [NP,2] ||| [1] [2] ||| logp=0	[V] ||| sah ||| saw ||| logp=0	[V] ||| fand ||| found ||| logp=0
+1	ich fand ein grosses haus	i found a large house	[S] ||| [NP,1] [VP,2] ||| [1] [2] ||| logp=0	[NP] ||| ich ||| i ||| logp=0	[NP] ||| ein [NN,1] ||| a [1] ||| logp=0	[NN] ||| [JJ,1] haus ||| [1] house ||| logp=0 use_house=1	[NN] ||| [JJ,1] haus ||| [1] shell ||| logp=0 use_shell=1	[JJ] ||| kleines ||| small ||| logp=0	[JJ] ||| kleines ||| little ||| logp=0	[JJ] ||| grosses ||| big ||| logp=0	[JJ] ||| grosses ||| large ||| logp=0	[VP] ||| [V,1] [NP,2] ||| [1] [2] ||| logp=0	[V] ||| sah ||| saw ||| logp=0	[V] ||| fand ||| found ||| logp=0