1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
|
/**
* @file pop_cmaes_test.cpp
* @author Benjami Parellada
*
* Tests for the POP_CMAES class, including IPOP CMA-ES and BIPOP CMA-ES.
*
* ensmallen is free software; you may redistribute it and/or modify it under
* the terms of the 3-clause BSD license. You should have received a copy of
* the 3-clause BSD license along with ensmallen. If not, see
* http://www.opensource.org/licenses/BSD-3-Clause for more information.
*/
#if defined(ENS_USE_COOT)
#include <armadillo>
#include <bandicoot>
#endif
#include <ensmallen.hpp>
#include "catch.hpp"
#include "test_function_tools.hpp"
#include "test_types.hpp"
using namespace ens;
using namespace ens::test;
// We can't test CMA-ES on low-precision floating point types because it uses
// chol() internally---which is not supported for low-precision.
/**
* Run IPOP-CMA-ES on the Rastrigin function and check whether the optimizer
* converges to the expected solution within tolerance limits.
*/
TEMPLATE_TEST_CASE("IPOP_CMAES_RastriginFunction", "[POPCMAES]", ENS_TEST_TYPES)
{
RastriginFunction f(2);
BoundaryBoxConstraint<TestType> b(-10, 10);
IPOP_CMAES<FullSelection, BoundaryBoxConstraint<TestType>> ipopcmaes(
15, // lambda
b, // transformationPolicy
32, // batchSize
10000, // maxIterations
Tolerances<TestType>::Obj, // tolerance
FullSelection(), // selectionPolicy
1.0, // stepSize
2.0, // populationFactor
3, // maxRestarts
1e6 // maxFunctionEvaluations
);
TestType initialPoint = f.GetInitialPoint<TestType>();
TestType expectedResult = f.GetFinalPoint<TestType>();
MultipleTrialOptimizerTest(f, ipopcmaes, initialPoint, expectedResult,
Tolerances<TestType>::LargeCoord, f.GetFinalObjective(),
Tolerances<TestType>::LargeObj, 5);
}
/**
* Run IPOP-CMA-ES on the Rosenbrock function and check whether the optimizer
* converges to the expected solution within tolerance limits.
*/
TEMPLATE_TEST_CASE("BIPOP_CMAES_RosenbrockFunction", "[POPCMAES]",
ENS_FULLPREC_TEST_TYPES)
{
BoundaryBoxConstraint<TestType> b(0, 2);
BIPOP_CMAES<FullSelection, BoundaryBoxConstraint<TestType>> bipopcmaes(
15, // lambda
b, // transformationPolicy
32, // batchSize
10000, // maxIterations
Tolerances<TestType>::Obj, // tolerance
FullSelection(), // selectionPolicy
0.25, // stepSize
1.5, // populationFactor
7, // maxRestarts
1e6 // maxFunctionEvaluations
);
FunctionTest<RosenbrockFunction, TestType>(bipopcmaes,
10 * Tolerances<TestType>::LargeObj,
10 * Tolerances<TestType>::LargeCoord,
3);
}
/**
* Run IPOP-CMA-ES with the full selection policy on logistic regression and
* make sure the results are acceptable.
*/
TEMPLATE_TEST_CASE("IPOP_CMAES_LogisticRegressionFunction", "[POPCMAES]",
ENS_FULLPREC_CPU_TEST_TYPES)
{
BoundaryBoxConstraint<TestType> b(-10, 10);
IPOP_CMAES<FullSelection, BoundaryBoxConstraint<TestType>> cmaes(
0, b, 32, 1000, 1e-3, FullSelection(), 0.6, 2.0, 7, 1e7);
LogisticRegressionFunctionTest<TestType>(cmaes,
Tolerances<TestType>::LRTrainAcc, Tolerances<TestType>::LRTestAcc, 5);
}
/**
* Run BIPOP-CMA-ES with the random selection policy on logistic regression and
* make sure the results are acceptable.
*/
TEMPLATE_TEST_CASE("BIPOP_CMAESLogisticRegressionFunction", "[POPCMAES]",
ENS_FULLPREC_CPU_TEST_TYPES)
{
BoundaryBoxConstraint<TestType> b(-10, 10);
BIPOP_CMAES<FullSelection, BoundaryBoxConstraint<TestType>> cmaes(
0, b, 32, 1000, 1e-3, FullSelection(), 0.6, 2.0, 7, 1e7);
LogisticRegressionFunctionTest<TestType>(cmaes,
Tolerances<TestType>::LRTrainAcc, Tolerances<TestType>::LRTestAcc, 5);
}
|
