major restructure of the training code

1 files changed, 117 insertions, 0 deletions

diff --git a/training/utils/lbfgs_test.cc b/training/utils/lbfgs_test.cc
new file mode 100644
index 00000000..9678e788
--- /dev/null
+++ b/training/utils/lbfgs_test.cc
@@ -0,0 +1,117 @@
+#include <cassert>
+#include <iostream>
+#include <sstream>
+#include <cmath>
+#include "lbfgs.h"
+#include "sparse_vector.h"
+#include "fdict.h"
+
+using namespace std;
+
+double TestOptimizer() {
+  cerr << "TESTING NON-PERSISTENT OPTIMIZER\n";
+
+  // f(x,y) = 4x1^2 + x1*x2 + x2^2 + x3^2 + 6x3 + 5
+  // df/dx1 = 8*x1 + x2
+  // df/dx2 = 2*x2 + x1
+  // df/dx3 = 2*x3 + 6
+  double x[3];
+  double g[3];
+  scitbx::lbfgs::minimizer<double> opt(3);
+  scitbx::lbfgs::traditional_convergence_test<double> converged(3);
+  x[0] = 8;
+  x[1] = 8;
+  x[2] = 8;
+  double obj = 0;
+  do {
+    g[0] = 8 * x[0] + x[1];
+    g[1] = 2 * x[1] + x[0];
+    g[2] = 2 * x[2] + 6;
+    obj = 4 * x[0]*x[0] + x[0] * x[1] + x[1]*x[1] + x[2]*x[2] + 6 * x[2] + 5;
+    opt.run(x, obj, g);
+    if (!opt.requests_f_and_g()) {
+      if (converged(x,g)) break;
+      opt.run(x, obj, g);
+    }
+    cerr << x[0] << " " << x[1] << " " << x[2] << endl;
+    cerr << "   obj=" << obj << "\td/dx1=" << g[0] << " d/dx2=" << g[1] << " d/dx3=" << g[2] << endl;
+    cerr << opt << endl;
+  } while (true);
+  return obj;
+}
+
+double TestPersistentOptimizer() {
+  cerr << "\nTESTING PERSISTENT OPTIMIZER\n";
+  // f(x,y) = 4x1^2 + x1*x2 + x2^2 + x3^2 + 6x3 + 5
+  // df/dx1 = 8*x1 + x2
+  // df/dx2 = 2*x2 + x1
+  // df/dx3 = 2*x3 + 6
+  double x[3];
+  double g[3];
+  scitbx::lbfgs::traditional_convergence_test<double> converged(3);
+  x[0] = 8;
+  x[1] = 8;
+  x[2] = 8;
+  double obj = 0;
+  string state;
+  do {
+    g[0] = 8 * x[0] + x[1];
+    g[1] = 2 * x[1] + x[0];
+    g[2] = 2 * x[2] + 6;
+    obj = 4 * x[0]*x[0] + x[0] * x[1] + x[1]*x[1] + x[2]*x[2] + 6 * x[2] + 5;
+
+    {
+      scitbx::lbfgs::minimizer<double> opt(3);
+      if (state.size() > 0) {
+        istringstream is(state, ios::binary);
+        opt.deserialize(&is);
+      }
+      opt.run(x, obj, g);
+      ostringstream os(ios::binary); opt.serialize(&os); state = os.str();
+    }
+
+    cerr << x[0] << " " << x[1] << " " << x[2] << endl;
+    cerr << "   obj=" << obj << "\td/dx1=" << g[0] << " d/dx2=" << g[1] << " d/dx3=" << g[2] << endl;
+  } while (!converged(x, g));
+  return obj;
+}
+
+void TestSparseVector() {
+  cerr << "Testing SparseVector<double> serialization.\n";
+  int f1 = FD::Convert("Feature_1");
+  int f2 = FD::Convert("Feature_2");
+  FD::Convert("LanguageModel");
+  int f4 = FD::Convert("SomeFeature");
+  int f5 = FD::Convert("SomeOtherFeature");
+  SparseVector<double> g;
+  g.set_value(f2, log(0.5));
+  g.set_value(f4, log(0.125));
+  g.set_value(f1, 0);
+  g.set_value(f5, 23.777);
+  ostringstream os;
+  double iobj = 1.5;
+  B64::Encode(iobj, g, &os);
+  cerr << iobj << "\t" << g << endl;
+  string data = os.str();
+  cout << data << endl;
+  SparseVector<double> v;
+  double obj;
+  bool decode_b64 = B64::Decode(&obj, &v, &data[0], data.size());
+  cerr << obj << "\t" << v << endl;
+  assert(decode_b64);
+  assert(obj == iobj);
+  assert(g.size() == v.size());
+}
+
+int main() {
+  double o1 = TestOptimizer();
+  double o2 = TestPersistentOptimizer();
+  if (fabs(o1 - o2) > 1e-5) {
+    cerr << "OPTIMIZERS PERFORMED DIFFERENTLY!\n" << o1 << " vs. " << o2 << endl;
+    return 1;
+  }
+  TestSparseVector();
+  cerr << "SUCCESS\n";
+  return 0;
+}
+