Fixed issue #8. Segmentation fault when using the __repr__ method

bob/learn/libsvm/machine.cpp

@@ -444,11 +444,11 @@ PyObject* PyBobLearnLibsvmMachine_Repr(PyBobLearnLibsvmMachineObject* self) {
    * <bob.learn.libsvm.Machine float64@(3, 2)>
    */
 
-  auto shape = make_safe(PyObject_GetAttrString((PyObject*)self, "shape"));
-  auto shape_str = make_safe(PyObject_Str(shape.get()));
+  PyObject* shape = Py_BuildValue("(nn)", self->cxx->inputSize(),
+      self->cxx->outputSize());
 
   PyObject* retval = PyUnicode_FromFormat("<%s float64@%U>",
-      Py_TYPE(self)->tp_name, shape_str.get());
+      Py_TYPE(self)->tp_name, PyObject_Unicode(shape));
 
 #if PYTHON_VERSION_HEX < 0x03000000
   if (!retval) return 0;

bob/learn/libsvm/test_machine.py

@@ -79,6 +79,7 @@ def test_can_load():
   assert -1 in machine.labels
   assert +1 in machine.labels
   assert abs(machine.gamma - 0.0769231) < 1e-6
+  assert type(machine.__repr__()) is str
 
 def test_can_save():
 
@@ -252,6 +253,7 @@ def test_correctness_iris():
   assert numpy.array_equal(pred_labels, real_labels)
   assert numpy.all(abs(numpy.vstack(pred_probs) - numpy.vstack(real_probs)) < 1e-6)
   
+
 @nose.tools.raises(RuntimeError)
 def test_correctness_inputsize_exceeds():