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#include "example.h"
#include "simple_label.h"
#include "gd.h"
#include "float.h"
#include "reductions.h"
using namespace LEARNER;
namespace PRINT
{
struct print{
vw* all;
};
void print_feature(vw& all, float value, float& weight)
{
size_t index = &weight - all.reg.weight_vector;
cout << index;
if (value != 1.)
cout << ":" << value;
cout << " ";
}
void learn(print& p, learner& base, example& ec)
{
label_data* ld = (label_data*)ec.ld;
if (ld->label != FLT_MAX)
{
cout << ld->label << " ";
if (ld->weight != 1 || ld->initial != 0)
{
cout << ld->weight << " ";
if (ld->initial != 0)
cout << ld->initial << " ";
}
}
if (ec.tag.size() > 0)
{
cout << '\'';
cout.write(ec.tag.begin, ec.tag.size());
}
cout << "| ";
GD::foreach_feature<vw, print_feature>(*(p.all), ec, *p.all);
cout << endl;
}
learner* setup(vw& all)
{
print* p = (print*)calloc_or_die(1, sizeof(print));
p->all = &all;
size_t length = ((size_t)1) << all.num_bits;
all.reg.weight_mask = (length << all.reg.stride_shift) - 1;
all.reg.stride_shift = 0;
learner* ret = new learner(p, 1);
ret->set_learn<print,learn>();
ret->set_predict<print,learn>();
return ret;
}
}
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