From 713e8842036872198407f54c499f6afb93d0599b Mon Sep 17 00:00:00 2001
From: Manuel Guenther <manuel.guenther@idiap.ch>
Date: Mon, 1 Sep 2014 20:59:26 +0200
Subject: [PATCH] Fixed newly introduced bob.core.random bindings
---
bob/learn/misc/old/ivector_trainer.cc | 2 +-
bob/learn/misc/old/jfa_trainer.cc | 4 ++--
bob/learn/misc/old/kmeans_trainer.cc | 4 ++--
bob/learn/misc/old/plda_trainer.cc | 2 +-
bob/learn/misc/test_jfa_trainer.py | 11 ++++++-----
bob/learn/misc/test_kmeans_trainer.py | 5 ++---
6 files changed, 14 insertions(+), 14 deletions(-)
diff --git a/bob/learn/misc/old/ivector_trainer.cc b/bob/learn/misc/old/ivector_trainer.cc
index d98ed50..8b964a8 100644
--- a/bob/learn/misc/old/ivector_trainer.cc
+++ b/bob/learn/misc/old/ivector_trainer.cc
@@ -88,7 +88,7 @@ static boost::python::object ITB_getRng(EMTrainerIVectorBase& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
#include <boost/make_shared.hpp>
diff --git a/bob/learn/misc/old/jfa_trainer.cc b/bob/learn/misc/old/jfa_trainer.cc
index 18d0299..a5966e2 100644
--- a/bob/learn/misc/old/jfa_trainer.cc
+++ b/bob/learn/misc/old/jfa_trainer.cc
@@ -316,13 +316,13 @@ static boost::python::object isv_getRng(bob::learn::misc::ISVTrainer& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
static boost::python::object jfa_getRng(bob::learn::misc::JFATrainer& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
#include <boost/make_shared.hpp>
diff --git a/bob/learn/misc/old/kmeans_trainer.cc b/bob/learn/misc/old/kmeans_trainer.cc
index 3a5838a..4ef008b 100644
--- a/bob/learn/misc/old/kmeans_trainer.cc
+++ b/bob/learn/misc/old/kmeans_trainer.cc
@@ -62,13 +62,13 @@ static boost::python::object KMTB_getRng(EMTrainerKMeansBase& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
static boost::python::object KMT_getRng(bob::learn::misc::KMeansTrainer& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
#include <boost/make_shared.hpp>
diff --git a/bob/learn/misc/old/plda_trainer.cc b/bob/learn/misc/old/plda_trainer.cc
index 1c31059..a9a9de3 100644
--- a/bob/learn/misc/old/plda_trainer.cc
+++ b/bob/learn/misc/old/plda_trainer.cc
@@ -98,7 +98,7 @@ static boost::python::object TB_getRng(EMTrainerPLDA& self){
// create new object
PyObject* o = PyBoostMt19937_Type.tp_alloc(&PyBoostMt19937_Type,0);
reinterpret_cast<PyBoostMt19937Object*>(o)->rng = self.getRng().get();
- return boost::python::object(boost::python::handle<>(o));
+ return boost::python::object(boost::python::handle<>(boost::python::borrowed(o)));
}
#include <boost/make_shared.hpp>
diff --git a/bob/learn/misc/test_jfa_trainer.py b/bob/learn/misc/test_jfa_trainer.py
index 5de6a46..7c3f4d4 100644
--- a/bob/learn/misc/test_jfa_trainer.py
+++ b/bob/learn/misc/test_jfa_trainer.py
@@ -11,10 +11,11 @@
import numpy
import numpy.linalg
+import bob.core.random
+
from . import GMMStats, GMMMachine, JFABase, JFAMachine, ISVBase, ISVMachine, \
JFATrainer, ISVTrainer
-from . import mt19937 as old_mt19937
def equals(x, y, epsilon):
return (abs(x - y) < epsilon).all()
@@ -266,7 +267,7 @@ def test_JFATrainInitialize():
## JFA
jb = JFABase(ubm, 2, 2)
# first round
- rng = old_mt19937(0)
+ rng = bob.core.random.mt19937(0)
jt = JFATrainer(10)
jt.rng = rng
jt.initialize(jb, TRAINING_STATS)
@@ -275,7 +276,7 @@ def test_JFATrainInitialize():
d1 = jb.d
# second round
- rng = old_mt19937(0)
+ rng = bob.core.random.mt19937(0)
jt.rng = rng
jt.initialize(jb, TRAINING_STATS)
u2 = jb.u
@@ -299,7 +300,7 @@ def test_ISVTrainInitialize():
## ISV
ib = ISVBase(ubm, 2)
# first round
- rng = old_mt19937(0)
+ rng = bob.core.random.mt19937(0)
it = ISVTrainer(10)
it.rng = rng
it.initialize(ib, TRAINING_STATS)
@@ -307,7 +308,7 @@ def test_ISVTrainInitialize():
d1 = ib.d
# second round
- rng = old_mt19937(0)
+ rng = bob.core.random.mt19937(0)
it.rng = rng
it.initialize(ib, TRAINING_STATS)
u2 = ib.u
diff --git a/bob/learn/misc/test_kmeans_trainer.py b/bob/learn/misc/test_kmeans_trainer.py
index 8d47cf0..9cf2ad3 100644
--- a/bob/learn/misc/test_kmeans_trainer.py
+++ b/bob/learn/misc/test_kmeans_trainer.py
@@ -15,7 +15,6 @@ from bob.io.base.test_utils import datafile
from . import KMeansMachine, KMeansTrainer
-from . import mt19937 as old_mt19937
def equals(x, y, epsilon):
return (abs(x - y) < epsilon).all()
@@ -74,7 +73,7 @@ if hasattr(KMeansTrainer, 'KMEANS_PLUS_PLUS'):
# C++ implementation
machine = KMeansMachine(dim_c, dim_d)
trainer = KMeansTrainer()
- trainer.rng = old_mt19937(seed)
+ trainer.rng = bob.core.random.mt19937(seed)
trainer.initialization_method = KMeansTrainer.KMEANS_PLUS_PLUS
trainer.initialize(machine, data)
@@ -92,7 +91,7 @@ def test_kmeans_noduplicate():
# Defines machine and trainer
machine = KMeansMachine(dim_c, dim_d)
trainer = KMeansTrainer()
- trainer.rng = old_mt19937(seed)
+ trainer.rng = bob.core.random.mt19937(seed)
trainer.initialization_method = KMeansTrainer.RANDOM_NO_DUPLICATE
trainer.initialize(machine, data)
# Makes sure that the two initial mean vectors selected are different
--
GitLab