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Matthias Mayr
limbo
Commits
4f9f45e0
Commit
4f9f45e0
authored
Dec 19, 2017
by
Konstantinos Chatzilygeroudis
Browse files
Added gradient checks for the mean functions
parent
79f5ae19
Changes
2
Hide whitespace changes
Inline
Sidebyside
src/tests/test_mean.cpp
0 → 100644
View file @
4f9f45e0
// Copyright Inria May 2015
// This project has received funding from the European Research Council (ERC) under
// the European Union's Horizon 2020 research and innovation programme (grant
// agreement No 637972)  see http://www.resibots.eu
//
// Contributor(s):
//  JeanBaptiste Mouret (jeanbaptiste.mouret@inria.fr)
//  Antoine Cully (antoinecully@gmail.com)
//  Kontantinos Chatzilygeroudis (konstantinos.chatzilygeroudis@inria.fr)
//  Federico Allocati (fede.allocati@gmail.com)
//  Vaios Papaspyros (b.papaspyros@gmail.com)
//  Roberto Rama (bertoski@gmail.com)
//
// This software is a computer library whose purpose is to optimize continuous,
// blackbox functions. It mainly implements Gaussian processes and Bayesian
// optimization.
// Main repository: http://github.com/resibots/limbo
// Documentation: http://www.resibots.eu/limbo
//
// This software is governed by the CeCILLC license under French law and
// abiding by the rules of distribution of free software. You can use,
// modify and/ or redistribute the software under the terms of the CeCILLC
// license as circulated by CEA, CNRS and INRIA at the following URL
// "http://www.cecill.info".
//
// As a counterpart to the access to the source code and rights to copy,
// modify and redistribute granted by the license, users are provided only
// with a limited warranty and the software's author, the holder of the
// economic rights, and the successive licensors have only limited
// liability.
//
// In this respect, the user's attention is drawn to the risks associated
// with loading, using, modifying and/or developing or reproducing the
// software by the user in light of its specific status of free software,
// that may mean that it is complicated to manipulate, and that also
// therefore means that it is reserved for developers and experienced
// professionals having indepth computer knowledge. Users are therefore
// encouraged to load and test the software's suitability as regards their
// requirements in conditions enabling the security of their systems and/or
// data to be ensured and, more generally, to use and operate it in the
// same conditions as regards security.
//
// The fact that you are presently reading this means that you have had
// knowledge of the CeCILLC license and that you accept its terms.
//
#define BOOST_TEST_DYN_LINK
#define BOOST_TEST_MODULE test_mean
#include
<iostream>
#include
<boost/test/unit_test.hpp>
#include
<limbo/mean/constant.hpp>
#include
<limbo/mean/function_ard.hpp>
#include
<limbo/tools/macros.hpp>
#include
<limbo/tools/random_generator.hpp>
using
namespace
limbo
;
struct
Params
{
struct
mean_constant
{
BO_PARAM
(
double
,
constant
,
1
);
};
};
// Check gradient via finite differences method
template
<
typename
Mean
>
std
::
tuple
<
double
,
Eigen
::
MatrixXd
,
Eigen
::
MatrixXd
>
check_grad
(
const
Mean
&
mean
,
const
Eigen
::
VectorXd
&
x
,
const
Eigen
::
VectorXd
&
v
,
double
e
=
1e4
)
{
Eigen
::
MatrixXd
analytic_result
,
finite_diff_result
;
Mean
me
=
mean
;
me
.
set_h_params
(
x
);
analytic_result
=
me
.
grad
(
v
,
v
);
finite_diff_result
=
Eigen
::
MatrixXd
::
Zero
(
v
.
size
(),
x
.
size
());
for
(
int
j
=
0
;
j
<
x
.
size
();
j
++
)
{
Eigen
::
VectorXd
test1
=
x
,
test2
=
x
;
test1
[
j
]
=
e
;
test2
[
j
]
+=
e
;
Mean
m1
=
mean
;
m1
.
set_h_params
(
test1
);
Mean
m2
=
mean
;
m2
.
set_h_params
(
test2
);
Eigen
::
VectorXd
res1
=
m1
(
v
,
v
);
Eigen
::
VectorXd
res2
=
m2
(
v
,
v
);
finite_diff_result
.
col
(
j
)
=
(
res2

res1
).
array
()
/
(
2.0
*
e
);
}
return
std
::
make_tuple
((
analytic_result

finite_diff_result
).
norm
(),
analytic_result
,
finite_diff_result
);
}
template
<
typename
Mean
>
void
check_mean
(
size_t
N
,
size_t
K
)
{
Mean
mean
(
N
);
for
(
size_t
i
=
0
;
i
<
K
;
i
++
)
{
Eigen
::
VectorXd
hp
=
tools
::
random_vector
(
mean
.
h_params_size
()).
array
()
*
10.

5.
;
double
error
;
Eigen
::
MatrixXd
analytic
,
finite_diff
;
Eigen
::
VectorXd
v
=
tools
::
random_vector
(
N
).
array
()
*
10.

5.
;
std
::
tie
(
error
,
analytic
,
finite_diff
)
=
check_grad
(
mean
,
hp
,
v
);
// std::cout << error << ": " << analytic.transpose() << " vs " << finite_diff.transpose() << std::endl;
BOOST_CHECK
(
error
<
1e6
);
}
}
BOOST_AUTO_TEST_CASE
(
test_mean_constant
)
{
for
(
int
i
=
1
;
i
<
10
;
i
++
)
{
check_mean
<
mean
::
Constant
<
Params
>>
(
i
,
100
);
}
}
BOOST_AUTO_TEST_CASE
(
test_mean_function_ard
)
{
for
(
int
i
=
1
;
i
<
10
;
i
++
)
{
check_mean
<
mean
::
FunctionARD
<
Params
,
mean
::
Constant
<
Params
>>>
(
i
,
100
);
}
}
src/tests/wscript
View file @
4f9f45e0
...
...
@@ 68,6 +68,12 @@ def build(bld):
target
=
'test_kernel'
,
uselib
=
'BOOST EIGEN TBB'
,
use
=
'limbo'
)
bld
.
program
(
features
=
'cxx test'
,
source
=
'test_mean.cpp'
,
includes
=
'. .. ../../'
,
target
=
'test_mean'
,
uselib
=
'BOOST EIGEN TBB'
,
use
=
'limbo'
)
bld
.
program
(
features
=
'cxx test'
,
source
=
'test_init_functions.cpp'
,
includes
=
'. .. ../../'
,
...
...
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