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Switched the svm_nu_trainer object's kernel cache from using

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the type of scalar used by the user supplied kernel to just always
use float.

--HG--
extra : convert_revision : svn%3Afdd8eb12-d10e-0410-9acb-85c331704f74/trunk%402976
This commit is contained in:
Davis King 2009-03-30 00:28:57 +00:00
parent 9a8ed037f4
commit aba529b38b
1 changed files with 13 additions and 7 deletions
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20
dlib/svm/svm.h
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@ -136,7 +136,9 @@ namespace dlib
> >
class kernel_matrix_cache class kernel_matrix_cache
{ {
typedef typename K::scalar_type scalar_type; public:
typedef float scalar_type;
//typedef typename K::scalar_type scalar_type;
typedef typename K::sample_type sample_type; typedef typename K::sample_type sample_type;
typedef typename K::mem_manager_type mem_manager_type; typedef typename K::mem_manager_type mem_manager_type;
@ -1076,6 +1078,7 @@ namespace dlib
scalar_vector_type alpha; scalar_vector_type alpha;
kernel_matrix_cache<K, in_sample_vector_type, in_scalar_vector_type> Q(x,y,kernel_function,cache_size); kernel_matrix_cache<K, in_sample_vector_type, in_scalar_vector_type> Q(x,y,kernel_function,cache_size);
typedef typename kernel_matrix_cache<K, in_sample_vector_type, in_scalar_vector_type>::scalar_type cache_type;
alpha.set_size(x.nr()); alpha.set_size(x.nr());
df.set_size(x.nr()); df.set_size(x.nr());
@ -1090,7 +1093,7 @@ namespace dlib
{ {
if (alpha(r) != 0) if (alpha(r) != 0)
{ {
const scalar_type* Q_r = Q.col(r); const cache_type* Q_r = Q.col(r);
for (long c = 0; c < alpha.nr(); ++c) for (long c = 0; c < alpha.nr(); ++c)
{ {
df(c) += alpha(r)*Q_r[c]; df(c) += alpha(r)*Q_r[c];
@ -1111,8 +1114,8 @@ namespace dlib
scalar_type delta_alpha_i = alpha(i) - old_alpha_i; scalar_type delta_alpha_i = alpha(i) - old_alpha_i;
scalar_type delta_alpha_j = alpha(j) - old_alpha_j; scalar_type delta_alpha_j = alpha(j) - old_alpha_j;
const scalar_type* Q_i = Q.col(i); const cache_type* Q_i = Q.col(i);
const scalar_type* Q_j = Q.col(j); const cache_type* Q_j = Q.col(j);
for(long k = 0; k < df.nr(); ++k) for(long k = 0; k < df.nr(); ++k)
df(k) += Q_i[k]*delta_alpha_i + Q_j[k]*delta_alpha_j; df(k) += Q_i[k]*delta_alpha_i + Q_j[k]*delta_alpha_j;
@ -1257,6 +1260,9 @@ namespace dlib
long in = -1; long in = -1;
long jn = -1; long jn = -1;
typedef typename kernel_matrix_cache<K, sample_vector_type, scalar_vector_type2>::scalar_type cache_type;
scalar_type ip_val = -numeric_limits<scalar_type>::infinity(); scalar_type ip_val = -numeric_limits<scalar_type>::infinity();
scalar_type jp_val = numeric_limits<scalar_type>::infinity(); scalar_type jp_val = numeric_limits<scalar_type>::infinity();
scalar_type in_val = -numeric_limits<scalar_type>::infinity(); scalar_type in_val = -numeric_limits<scalar_type>::infinity();
@ -1297,9 +1303,9 @@ namespace dlib
// As a speed hack, pull out pointers to the columns of the // As a speed hack, pull out pointers to the columns of the
// kernel matrix we will be using below rather than accessing // kernel matrix we will be using below rather than accessing
// them through the Q(r,c) syntax. // them through the Q(r,c) syntax.
const scalar_type* Q_ip = 0; const cache_type* Q_ip = 0;
const scalar_type* Q_in = 0; const cache_type* Q_in = 0;
const scalar_type* Q_diag = Q.diag(); const cache_type* Q_diag = Q.diag();
if (ip != -1) if (ip != -1)
Q_ip = Q.col(ip); Q_ip = Q.col(ip);
if (in != -1) if (in != -1)