Started to bind GMMMachine

bob/learn/misc/gmm_machine.cpp

+/**
+ * @author Tiago de Freitas Pereira <tiago.pereira@idiap.ch>
+ * @date Wed 11 Dec 18:01:00 2014
+ *
+ * @brief Python API for bob::learn::em
+ *
+ * Copyright (C) 2011-2014 Idiap Research Institute, Martigny, Switzerland
+ */
+
+#include "main.h"
+
+/******************************************************************/
+/************ Constructor Section *********************************/
+/******************************************************************/
+
+static auto GMMMachine_doc = bob::extension::ClassDoc(
+  BOB_EXT_MODULE_PREFIX ".GMMMachine",
+  "This class implements a multivariate diagonal Gaussian distribution.",
+  "See Section 2.3.9 of Bishop, \"Pattern recognition and machine learning\", 2006"
+).add_constructor(
+  bob::extension::FunctionDoc(
+    "__init__",
+    "A container for GMM statistics.",
+    "",
+    true
+  )
+  .add_prototype("n_gaussians,n_inputs","")
+  .add_prototype("other","")
+  .add_prototype("hdf5","")
+  .add_prototype("","")
+
+  .add_parameter("n_gaussians", "int", "Number of gaussians")
+  .add_parameter("n_inputs", "int", "Dimension of the feature vector")
+  .add_parameter("other", ":py:class:`bob.learn.misc.GMMMachine`", "A GMMMachine object to be copied.")
+  .add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for reading")
+
+);
+
+
+static int PyBobLearnMiscGMMMachine_init_number(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+
+  char** kwlist = GMMMachine_doc.kwlist(0);
+  int n_inputs    = 1;
+  int n_gaussians = 1;
+  //Parsing the input argments
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "ii", kwlist, &n_gaussians, &n_inputs))
+    return -1;
+
+  if(n_gaussians < 0){
+    PyErr_Format(PyExc_TypeError, "gaussians argument must be greater than or equal to zero");
+    GMMMachine_doc.print_usage();
+    return -1;
+  }
+
+  if(n_inputs < 0){
+    PyErr_Format(PyExc_TypeError, "input argument must be greater than or equal to zero");
+    GMMMachine_doc.print_usage();
+    return -1;
+   }
+
+  self->cxx.reset(new bob::learn::misc::GMMMachine(n_gaussians, n_inputs));
+  return 0;
+}
+
+
+static int PyBobLearnMiscGMMMachine_init_copy(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+
+  char** kwlist = GMMMachine_doc.kwlist(1);
+  PyBobLearnMiscGMMMachineObject* tt;
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!", kwlist, &PyBobLearnMiscGMMMachine_Type, &tt)){
+    GMMMachine_doc.print_usage();
+    return -1;
+  }
+
+  self->cxx.reset(new bob::learn::misc::GMMMachine(*tt->cxx));
+  return 0;
+}
+
+
+static int PyBobLearnMiscGMMMachine_init_hdf5(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+
+  char** kwlist = GMMMachine_doc.kwlist(2);
+
+  PyBobIoHDF5FileObject* config = 0;
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobIoHDF5File_Converter, &config)){
+    GMMMachine_doc.print_usage();
+    return -1;
+  }
+
+  self->cxx.reset(new bob::learn::misc::GMMMachine(*(config->f)));
+
+  return 0;
+}
+
+
+
+static int PyBobLearnMiscGMMMachine_init(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+  BOB_TRY
+
+  // get the number of command line arguments
+  int nargs = (args?PyTuple_Size(args):0) + (kwargs?PyDict_Size(kwargs):0);
+  
+  switch (nargs) {
+
+    case 0: //default initializer ()
+      self->cxx.reset(new bob::learn::misc::GMMMachine());
+      return 0;
+
+    case 1:{
+      //Reading the input argument
+      PyObject* arg = 0;
+      if (PyTuple_Size(args))
+        arg = PyTuple_GET_ITEM(args, 0);
+      else {
+        PyObject* tmp = PyDict_Values(kwargs);
+        auto tmp_ = make_safe(tmp);
+        arg = PyList_GET_ITEM(tmp, 0);
+      }
+
+      // If the constructor input is Gaussian object
+     if (PyBobLearnMiscGMMMachine_Check(arg))
+       return PyBobLearnMiscGMMMachine_init_copy(self, args, kwargs);
+      // If the constructor input is a HDF5
+     else if (PyBobIoHDF5File_Check(arg))
+       return PyBobLearnMiscGMMMachine_init_hdf5(self, args, kwargs);
+    }
+    case 2:
+      return PyBobLearnMiscGMMMachine_init_number(self, args, kwargs);
+    default:
+      PyErr_Format(PyExc_RuntimeError, "number of arguments mismatch - %s requires 0, 1 or 2 arguments, but you provided %d (see help)", Py_TYPE(self)->tp_name, nargs);
+      GMMMachine_doc.print_usage();
+      return -1;
+  }
+  BOB_CATCH_MEMBER("cannot create GMMMachine", 0)
+  return 0;
+}
+
+
+
+static void PyBobLearnMiscGMMMachine_delete(PyBobLearnMiscGMMMachineObject* self) {
+  self->cxx.reset();
+  Py_TYPE(self)->tp_free((PyObject*)self);
+}
+
+static PyObject* PyBobLearnMiscGMMMachine_RichCompare(PyBobLearnMiscGMMMachineObject* self, PyObject* other, int op) {
+  BOB_TRY
+
+  if (!PyBobLearnMiscGMMMachine_Check(other)) {
+    PyErr_Format(PyExc_TypeError, "cannot compare `%s' with `%s'", Py_TYPE(self)->tp_name, Py_TYPE(other)->tp_name);
+    return 0;
+  }
+  auto other_ = reinterpret_cast<PyBobLearnMiscGMMMachineObject*>(other);
+  switch (op) {
+    case Py_EQ:
+      if (*self->cxx==*other_->cxx) Py_RETURN_TRUE; else Py_RETURN_FALSE;
+    case Py_NE:
+      if (*self->cxx==*other_->cxx) Py_RETURN_FALSE; else Py_RETURN_TRUE;
+    default:
+      Py_INCREF(Py_NotImplemented);
+      return Py_NotImplemented;
+  }
+  BOB_CATCH_MEMBER("cannot compare GMMMachine objects", 0)
+}
+
+int PyBobLearnMiscGMMMachine_Check(PyObject* o) {
+  return PyObject_IsInstance(o, reinterpret_cast<PyObject*>(&PyBobLearnMiscGMMMachine_Type));
+}
+
+
+/******************************************************************/
+/************ Variables Section ***********************************/
+/******************************************************************/
+
+/***** shape *****/
+static auto shape = bob::extension::VariableDoc(
+  "shape",
+  "(int,int)",
+  "A tuple that represents the number of gaussians and dimensionality of each Gaussian ``(n_gaussians, dim)``.",
+  ""
+);
+PyObject* PyBobLearnMiscGMMMachine_getShape(PyBobLearnMiscGMMMachineObject* self, void*) {
+  BOB_TRY
+  return Py_BuildValue("(i,i)", self->cxx->getNGaussians(), self->cxx->getNInputs());
+  BOB_CATCH_MEMBER("shape could not be read", 0)
+}
+
+
+
+static PyGetSetDef PyBobLearnMiscGMMMachine_getseters[] = { 
+  {
+   shape.name(),
+   (getter)PyBobLearnMiscGMMMachine_getShape,
+   0,
+   shape.doc(),
+   0
+  },
+
+  {0}  // Sentinel
+};
+
+
+/******************************************************************/
+/************ Functions Section ***********************************/
+/******************************************************************/
+
+
+/*** save ***/
+static auto save = bob::extension::FunctionDoc(
+  "save",
+  "Save the configuration of the GMMMachine to a given HDF5 file"
+)
+.add_prototype("hdf5")
+.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for writing");
+static PyObject* PyBobLearnMiscGMMMachine_Save(PyBobLearnMiscGMMMachineObject* self,  PyObject* args, PyObject* kwargs) {
+
+  BOB_TRY
+  
+  // get list of arguments
+  char** kwlist = save.kwlist(0);  
+  PyBobIoHDF5FileObject* hdf5;
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, PyBobIoHDF5File_Converter, &hdf5)) return 0;
+
+  auto hdf5_ = make_safe(hdf5);
+  self->cxx->save(*hdf5->f);
+
+  BOB_CATCH_MEMBER("cannot save the data", 0)
+  Py_RETURN_NONE;
+}
+
+/*** load ***/
+static auto load = bob::extension::FunctionDoc(
+  "load",
+  "Load the configuration of the GMMMachine to a given HDF5 file"
+)
+.add_prototype("hdf5")
+.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for reading");
+static PyObject* PyBobLearnMiscGMMMachine_Load(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+  BOB_TRY
+  
+  char** kwlist = load.kwlist(0);  
+  PyBobIoHDF5FileObject* hdf5;
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, PyBobIoHDF5File_Converter, &hdf5)) return 0;
+  
+  auto hdf5_ = make_safe(hdf5);  
+  self->cxx->load(*hdf5->f);
+
+  BOB_CATCH_MEMBER("cannot load the data", 0)
+  Py_RETURN_NONE;
+}
+
+
+/*** is_similar_to ***/
+static auto is_similar_to = bob::extension::FunctionDoc(
+  "is_similar_to",
+  
+  "Compares this GMMMachine with the ``other`` one to be approximately the same.",
+  "The optional values ``r_epsilon`` and ``a_epsilon`` refer to the "
+  "relative and absolute precision for the ``weights``, ``biases`` "
+  "and any other values internal to this machine."
+)
+.add_prototype("other, [r_epsilon], [a_epsilon]","output")
+.add_parameter("other", ":py:class:`bob.learn.misc.GMMMachine`", "A GMMMachine object to be compared.")
+.add_parameter("r_epsilon", "float", "Relative precision.")
+.add_parameter("a_epsilon", "float", "Absolute precision.")
+.add_return("output","bool","True if it is similar, otherwise false.");
+static PyObject* PyBobLearnMiscGMMMachine_IsSimilarTo(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwds) {
+
+  /* Parses input arguments in a single shot */
+  char** kwlist = is_similar_to.kwlist(0);
+
+  //PyObject* other = 0;
+  PyBobLearnMiscGMMMachineObject* other = 0;
+  double r_epsilon = 1.e-5;
+  double a_epsilon = 1.e-8;
+
+  if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|dd", kwlist,
+        &PyBobLearnMiscGMMMachine_Type, &other,
+        &r_epsilon, &a_epsilon)){
+
+        is_similar_to.print_usage(); 
+        return 0;        
+  }
+
+  if (self->cxx->is_similar_to(*other->cxx, r_epsilon, a_epsilon))
+    Py_RETURN_TRUE;
+  else
+    Py_RETURN_FALSE;
+}
+
+
+/*** resize ***/
+static auto resize = bob::extension::FunctionDoc(
+  "resize",
+  "Allocates space for the statistics and resets to zero.",
+  0,
+  true
+)
+.add_prototype("n_gaussians,n_inputs")
+.add_parameter("n_gaussians", "int", "Number of gaussians")
+.add_parameter("n_inputs", "int", "Dimensionality of the feature vector");
+static PyObject* PyBobLearnMiscGMMMachine_resize(PyBobLearnMiscGMMMachineObject* self, PyObject* args, PyObject* kwargs) {
+  BOB_TRY
+
+  /* Parses input arguments in a single shot */
+  char** kwlist = resize.kwlist(0);
+
+  int n_gaussians = 0;
+  int n_inputs = 0;
+
+  if (!PyArg_ParseTupleAndKeywords(args, kwargs, "ii", kwlist, &n_gaussians, &n_inputs)) Py_RETURN_NONE;
+
+  if (n_gaussians <= 0){
+    PyErr_Format(PyExc_TypeError, "n_gaussians must be greater than zero");
+    resize.print_usage();
+    return 0;
+  }
+  if (n_inputs <= 0){
+    PyErr_Format(PyExc_TypeError, "n_inputs must be greater than zero");
+    resize.print_usage();
+    return 0;
+  }
+
+  self->cxx->resize(n_gaussians, n_inputs);
+
+  BOB_CATCH_MEMBER("cannot perform the resize method", 0)
+
+  Py_RETURN_NONE;
+}
+
+
+
+static PyMethodDef PyBobLearnMiscGMMMachine_methods[] = {
+  {
+    save.name(),
+    (PyCFunction)PyBobLearnMiscGMMMachine_Save,
+    METH_VARARGS|METH_KEYWORDS,
+    save.doc()
+  },
+  {
+    load.name(),
+    (PyCFunction)PyBobLearnMiscGMMMachine_Load,
+    METH_VARARGS|METH_KEYWORDS,
+    load.doc()
+  },
+  {
+    is_similar_to.name(),
+    (PyCFunction)PyBobLearnMiscGMMMachine_IsSimilarTo,
+    METH_VARARGS|METH_KEYWORDS,
+    is_similar_to.doc()
+  },
+  {
+    resize.name(),
+    (PyCFunction)PyBobLearnMiscGMMMachine_resize,
+    METH_VARARGS|METH_KEYWORDS,
+    resize.doc()
+  },
+  {0} /* Sentinel */
+};
+
+
+/******************************************************************/
+/************ Module Section **************************************/
+/******************************************************************/
+
+// Define the Gaussian type struct; will be initialized later
+PyTypeObject PyBobLearnMiscGMMMachine_Type = {
+  PyVarObject_HEAD_INIT(0,0)
+  0
+};
+
+bool init_BobLearnMiscGMMMachine(PyObject* module)
+{
+  // initialize the type struct
+  PyBobLearnMiscGMMMachine_Type.tp_name = GMMMachine_doc.name();
+  PyBobLearnMiscGMMMachine_Type.tp_basicsize = sizeof(PyBobLearnMiscGMMMachineObject);
+  PyBobLearnMiscGMMMachine_Type.tp_flags = Py_TPFLAGS_DEFAULT;
+  PyBobLearnMiscGMMMachine_Type.tp_doc = GMMMachine_doc.doc();
+
+  // set the functions
+  PyBobLearnMiscGMMMachine_Type.tp_new = PyType_GenericNew;
+  PyBobLearnMiscGMMMachine_Type.tp_init = reinterpret_cast<initproc>(PyBobLearnMiscGMMMachine_init);
+  PyBobLearnMiscGMMMachine_Type.tp_dealloc = reinterpret_cast<destructor>(PyBobLearnMiscGMMMachine_delete);
+  PyBobLearnMiscGMMMachine_Type.tp_richcompare = reinterpret_cast<richcmpfunc>(PyBobLearnMiscGMMMachine_RichCompare);
+  PyBobLearnMiscGMMMachine_Type.tp_methods = PyBobLearnMiscGMMMachine_methods;
+  PyBobLearnMiscGMMMachine_Type.tp_getset = PyBobLearnMiscGMMMachine_getseters;
+  PyBobLearnMiscGMMMachine_Type.tp_call = 0;
+
+
+  // check that everything is fine
+  if (PyType_Ready(&PyBobLearnMiscGMMMachine_Type) < 0) return false;
+
+  // add the type to the module
+  Py_INCREF(&PyBobLearnMiscGMMMachine_Type);
+  return PyModule_AddObject(module, "GMMMachine", (PyObject*)&PyBobLearnMiscGMMMachine_Type) >= 0;
+}
+

bob/learn/misc/main.cpp

@@ -42,6 +42,7 @@ static PyObject* create_module (void) {
   if (PyModule_AddStringConstant(module, "__version__", BOB_EXT_MODULE_VERSION) < 0) return 0;
   if (!init_BobLearnMiscGaussian(module)) return 0;
   if (!init_BobLearnMiscGMMStats(module)) return 0;
+  if (!init_BobLearnMiscGMMMachine(module)) return 0;  
 
   static void* PyBobLearnMisc_API[PyBobLearnMisc_API_pointers];
 

bob/learn/misc/main.h

@@ -19,6 +19,7 @@
 
 #include <bob.learn.misc/Gaussian.h>
 #include <bob.learn.misc/GMMStats.h>
+#include <bob.learn.misc/GMMMachine.h>
 
 
 #if PY_VERSION_HEX >= 0x03000000
@@ -81,5 +82,16 @@ bool init_BobLearnMiscGMMStats(PyObject* module);
 int PyBobLearnMiscGMMStats_Check(PyObject* o);
 
 
+// GMMMachine
+typedef struct {
+  PyObject_HEAD
+  boost::shared_ptr<bob::learn::misc::GMMMachine> cxx;
+} PyBobLearnMiscGMMMachineObject;
+
+extern PyTypeObject PyBobLearnMiscGMMMachine_Type;
+bool init_BobLearnMiscGMMMachine(PyObject* module);
+int PyBobLearnMiscGMMMachine_Check(PyObject* o);
+
+
 
 #endif // BOB_LEARN_EM_MAIN_H

setup.py

@@ -55,7 +55,7 @@ setup(
       Library("bob.learn.misc.bob_learn_misc",
         [
           "bob/learn/misc/cpp/Gaussian.cpp",
-          #"bob/learn/misc/cpp/GMMMachine.cpp",
+          "bob/learn/misc/cpp/GMMMachine.cpp",
           "bob/learn/misc/cpp/GMMStats.cpp",
           #"bob/learn/misc/cpp/IVectorMachine.cpp",
           #"bob/learn/misc/cpp/JFAMachine.cpp",
@@ -102,6 +102,7 @@ setup(
         [
           "bob/learn/misc/gaussian.cpp",
           "bob/learn/misc/gmm_stats.cpp",
+          "bob/learn/misc/gmm_machine.cpp",
 
           "bob/learn/misc/main.cpp",
         ],