From 8bcad55d9889b0bb6498a3d891a63d16b72e9d45 Mon Sep 17 00:00:00 2001
From: Tiago Freitas Pereira <tiagofrepereira@gmail.com>
Date: Thu, 11 Dec 2014 16:53:46 +0100
Subject: [PATCH] Modifications in the load and save bind in order to support
keyword arguments
---
bob/learn/misc/gmm_stats.cpp | 162 ++++++++++++++++++-----------------
1 file changed, 84 insertions(+), 78 deletions(-)
diff --git a/bob/learn/misc/gmm_stats.cpp b/bob/learn/misc/gmm_stats.cpp
index a5c7e5b..9a9b754 100644
--- a/bob/learn/misc/gmm_stats.cpp
+++ b/bob/learn/misc/gmm_stats.cpp
@@ -15,12 +15,11 @@
static auto GMMStats_doc = bob::extension::ClassDoc(
BOB_EXT_MODULE_PREFIX ".GMMStats",
- "A container for GMM statistics.\n",
- "With respect to Reynolds, \"Speaker Verification Using Adapted "
- "Gaussian Mixture Models\", DSP, 2000:\n"
- "Eq (8) is n(i)\n"
- "Eq (9) is sumPx(i) / n(i)\n"
- "Eq (10) is sumPxx(i) / n(i)\n"
+ "A container for GMM statistics",
+ "With respect to [Reynolds2000]_ the class computes: \n\n"
+ "* Eq (8) is :math:`n_i=\\sum\\limits_{t=1}^T Pr(i | x_t)`\n\n"
+ "* Eq (9) is :math:`sumPx=E_i(x)=\\frac{1}{n(i)}\\sum\\limits_{t=1}^T Pr(i | x_t)x_t`\n\n"
+ "* Eq (10) is :math:`sumPxx=E_i(x^2)=\\frac{1}{n(i)}\\sum\\limits_{t=1}^T Pr(i | x_t)x_t^2`\n\n"
).add_constructor(
bob::extension::FunctionDoc(
"__init__",
@@ -52,11 +51,13 @@ static int PyBobLearnMiscGMMStats_init_number(PyBobLearnMiscGMMStatsObject* self
if(n_gaussians < 0){
PyErr_Format(PyExc_TypeError, "gaussians argument must be greater than or equal to zero");
+ GMMStats_doc.print_usage();
return -1;
}
if(n_inputs < 0){
PyErr_Format(PyExc_TypeError, "input argument must be greater than or equal to zero");
+ GMMStats_doc.print_usage();
return -1;
}
@@ -69,7 +70,10 @@ static int PyBobLearnMiscGMMStats_init_copy(PyBobLearnMiscGMMStatsObject* self,
char** kwlist = GMMStats_doc.kwlist(1);
PyBobLearnMiscGMMStatsObject* tt;
- if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!", kwlist, &PyBobLearnMiscGMMStats_Type, &tt)) return -1;
+ if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O!", kwlist, &PyBobLearnMiscGMMStats_Type, &tt)){
+ GMMStats_doc.print_usage();
+ return -1;
+ }
self->cxx.reset(new bob::learn::misc::GMMStats(*tt->cxx));
return 0;
@@ -81,21 +85,13 @@ static int PyBobLearnMiscGMMStats_init_hdf5(PyBobLearnMiscGMMStatsObject* self,
char** kwlist = GMMStats_doc.kwlist(2);
PyBobIoHDF5FileObject* config = 0;
- if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobIoHDF5File_Converter, &config))
- return -1;
-
- try {
- self->cxx.reset(new bob::learn::misc::GMMStats(*(config->f)));
- }
- catch (std::exception& ex) {
- PyErr_SetString(PyExc_RuntimeError, ex.what());
- return -1;
- }
- catch (...) {
- PyErr_Format(PyExc_RuntimeError, "cannot create new object of type `%s' - unknown exception thrown", Py_TYPE(self)->tp_name);
+ if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, &PyBobIoHDF5File_Converter, &config)){
+ GMMStats_doc.print_usage();
return -1;
}
+ self->cxx.reset(new bob::learn::misc::GMMStats(*(config->f)));
+
return 0;
}
@@ -105,12 +101,13 @@ static int PyBobLearnMiscGMMStats_init(PyBobLearnMiscGMMStatsObject* self, PyObj
BOB_TRY
// get the number of command line arguments
- Py_ssize_t nargs = (args?PyTuple_Size(args):0) + (kwargs?PyDict_Size(kwargs):0);
+ 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::GMMStats());
+ return 0;
case 1:{
//Reading the input argument
@@ -133,7 +130,8 @@ static int PyBobLearnMiscGMMStats_init(PyBobLearnMiscGMMStatsObject* self, PyObj
case 2:
return PyBobLearnMiscGMMStats_init_number(self, args, kwargs);
default:
- PyErr_Format(PyExc_RuntimeError, "number of arguments mismatch - %s requires 0, 1 or 2 arguments, but you provided %" PY_FORMAT_SIZE_T "d (see help)", Py_TYPE(self)->tp_name, nargs);
+ 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);
+ GMMStats_doc.print_usage();
return -1;
}
BOB_CATCH_MEMBER("cannot create GMMStats", 0)
@@ -179,8 +177,8 @@ int PyBobLearnMiscGMMStats_Check(PyObject* o) {
/***** n *****/
static auto n = bob::extension::VariableDoc(
"n",
- "array_like <double, 1D> ",
- "For each Gaussian, the accumulated sum of responsibilities, i.e. the sum of P(gaussian_i|x)"
+ "array_like <double, 1D>",
+ "For each Gaussian, the accumulated sum of responsibilities, i.e. the sum of :math:`P(gaussian_i|x)`"
);
PyObject* PyBobLearnMiscGMMStats_getN(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
@@ -260,8 +258,8 @@ int PyBobLearnMiscGMMStats_setSum_pxx(PyBobLearnMiscGMMStatsObject* self, PyObje
/***** t *****/
static auto t = bob::extension::VariableDoc(
"t",
- "int ",
- "The accumulated number of samples"
+ "int",
+ "The number of samples"
);
PyObject* PyBobLearnMiscGMMStats_getT(PyBobLearnMiscGMMStatsObject* self, void*){
BOB_TRY
@@ -312,6 +310,21 @@ int PyBobLearnMiscGMMStats_setLog_likelihood(PyBobLearnMiscGMMStatsObject* self,
}
+/***** 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* PyBobLearnMiscGMMStats_getShape(PyBobLearnMiscGMMStatsObject* self, void*) {
+ BOB_TRY
+ return Py_BuildValue("(i,i)", self->cxx->sumPx.shape()[0], self->cxx->sumPx.shape()[1]);
+ BOB_CATCH_MEMBER("shape could not be read", 0)
+}
+
+
+
static PyGetSetDef PyBobLearnMiscGMMStats_getseters[] = {
{
n.name(),
@@ -347,8 +360,16 @@ static PyGetSetDef PyBobLearnMiscGMMStats_getseters[] = {
(setter)PyBobLearnMiscGMMStats_setLog_likelihood,
log_likelihood.doc(),
0
+ },
+ {
+ shape.name(),
+ (getter)PyBobLearnMiscGMMStats_getShape,
+ 0,
+ shape.doc(),
+ 0
},
+
{0} // Sentinel
};
@@ -364,31 +385,20 @@ static auto save = bob::extension::FunctionDoc(
"Save the configuration of the GMMStats 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* PyBobLearnMiscGMMStats_Save(PyBobLearnMiscGMMStatsObject* self, PyObject* arg) {
+.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for writing");
+static PyObject* PyBobLearnMiscGMMStats_Save(PyBobLearnMiscGMMStatsObject* self, PyObject* args, PyObject* kwargs) {
+ BOB_TRY
+
// get list of arguments
- if (!PyBobIoHDF5File_Check(arg)) {
- PyErr_Format(PyExc_TypeError, "`%s' cannot write itself to `%s', only to an HDF5 file", Py_TYPE(self)->tp_name, Py_TYPE(arg)->tp_name);
- return 0;
- }
+ char** kwlist = save.kwlist(0);
+ PyBobIoHDF5FileObject* hdf5;
+ if (!PyArg_ParseTupleAndKeywords(args, kwargs, "O&", kwlist, PyBobIoHDF5File_Converter, &hdf5)) return 0;
- auto hdf5 = reinterpret_cast<PyBobIoHDF5FileObject*>(arg);
-
- try {
- self->cxx->save(*hdf5->f);
- }
- catch (std::exception& e) {
- PyErr_SetString(PyExc_RuntimeError, e.what());
- return 0;
- }
- catch (...) {
- PyErr_Format(PyExc_RuntimeError, "`%s' cannot write data to file `%s' (at group `%s'): unknown exception caught", Py_TYPE(self)->tp_name,
- hdf5->f->filename().c_str(), hdf5->f->cwd().c_str());
- return 0;
- }
+ auto hdf5_ = make_safe(hdf5);
+ self->cxx->save(*hdf5->f);
+ BOB_CATCH_MEMBER("cannot save the data", 0)
Py_RETURN_NONE;
}
@@ -399,27 +409,17 @@ static auto load = bob::extension::FunctionDoc(
)
.add_prototype("hdf5")
.add_parameter("hdf5", ":py:class:`bob.io.base.HDF5File`", "An HDF5 file open for reading");
-static PyObject* PyBobLearnMiscGMMStats_Load(PyBobLearnMiscGMMStatsObject* self, PyObject* f) {
-
- if (!PyBobIoHDF5File_Check(f)) {
- PyErr_Format(PyExc_TypeError, "`%s' cannot load itself from `%s', only from an HDF5 file", Py_TYPE(self)->tp_name, Py_TYPE(f)->tp_name);
- return 0;
- }
-
- auto h5f = reinterpret_cast<PyBobIoHDF5FileObject*>(f);
+static PyObject* PyBobLearnMiscGMMStats_Load(PyBobLearnMiscGMMStatsObject* 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);
- try {
- self->cxx->load(*h5f->f);
- }
- catch (std::exception& e) {
- PyErr_SetString(PyExc_RuntimeError, e.what());
- return 0;
- }
- catch (...) {
- PyErr_Format(PyExc_RuntimeError, "cannot read data from file `%s' (at group `%s'): unknown exception caught", h5f->f->filename().c_str(),
- h5f->f->cwd().c_str());
- return 0;
- }
+ BOB_CATCH_MEMBER("cannot load the data", 0)
Py_RETURN_NONE;
}
@@ -429,14 +429,14 @@ static auto is_similar_to = bob::extension::FunctionDoc(
"is_similar_to",
"Compares this GMMStats 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``"
+ "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.GMMStats`", "A GMMStats object to be compared.")
-.add_parameter("[r_epsilon]", "float", "Relative precision.")
-.add_parameter("[a_epsilon]", "float", "Absolute precision.")
+.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* PyBobLearnMiscGMMStats_IsSimilarTo(PyBobLearnMiscGMMStatsObject* self, PyObject* args, PyObject* kwds) {
@@ -450,9 +450,11 @@ static PyObject* PyBobLearnMiscGMMStats_IsSimilarTo(PyBobLearnMiscGMMStatsObject
if (!PyArg_ParseTupleAndKeywords(args, kwds, "O!|dd", kwlist,
&PyBobLearnMiscGMMStats_Type, &other,
- &r_epsilon, &a_epsilon)) return 0;
+ &r_epsilon, &a_epsilon)){
- //auto other_ = reinterpret_cast<PyBobLearnMiscGMMStatsObject*>(other);
+ is_similar_to.print_usage();
+ return 0;
+ }
if (self->cxx->is_similar_to(*other->cxx, r_epsilon, a_epsilon))
Py_RETURN_TRUE;
@@ -464,9 +466,11 @@ static PyObject* PyBobLearnMiscGMMStats_IsSimilarTo(PyBobLearnMiscGMMStatsObject
/*** resize ***/
static auto resize = bob::extension::FunctionDoc(
"resize",
- " Allocates space for the statistics and resets to zero."
+ "Allocates space for the statistics and resets to zero.",
+ 0,
+ true
)
-.add_prototype("n_gaussians,n_inputs","")
+.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* PyBobLearnMiscGMMStats_resize(PyBobLearnMiscGMMStatsObject* self, PyObject* args, PyObject* kwargs) {
@@ -482,10 +486,12 @@ static PyObject* PyBobLearnMiscGMMStats_resize(PyBobLearnMiscGMMStatsObject* sel
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;
}
@@ -503,7 +509,7 @@ static auto init = bob::extension::FunctionDoc(
"init",
" Resets statistics to zero."
)
-.add_prototype("","");
+.add_prototype("");
static PyObject* PyBobLearnMiscGMMStats_init_method(PyBobLearnMiscGMMStatsObject* self) {
BOB_TRY
@@ -520,13 +526,13 @@ static PyMethodDef PyBobLearnMiscGMMStats_methods[] = {
{
save.name(),
(PyCFunction)PyBobLearnMiscGMMStats_Save,
- METH_O,
+ METH_VARARGS|METH_KEYWORDS,
save.doc()
},
{
load.name(),
(PyCFunction)PyBobLearnMiscGMMStats_Load,
- METH_O,
+ METH_VARARGS|METH_KEYWORDS,
load.doc()
},
{
@@ -601,7 +607,7 @@ bool init_BobLearnMiscGMMStats(PyObject* module)
PyBobLearnMiscGMMStats_Type.tp_richcompare = reinterpret_cast<richcmpfunc>(PyBobLearnMiscGMMStats_RichCompare);
PyBobLearnMiscGMMStats_Type.tp_methods = PyBobLearnMiscGMMStats_methods;
PyBobLearnMiscGMMStats_Type.tp_getset = PyBobLearnMiscGMMStats_getseters;
- //PyBobLearnMiscGMMStats_Type.tp_call = reinterpret_cast<ternaryfunc>(PyBobLearnMiscGMMStats_loglikelihood);
+ PyBobLearnMiscGMMStats_Type.tp_call = 0;
PyBobLearnMiscGMMStats_Type.tp_as_number = &PyBobLearnMiscGMMStats_operators;
//set operators
--
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