#include <stdio.h>
#include <vector>
#include <string>
#include <math.h>
#include "mnist_common.h"
float accuracy(
const array& predicted,
const array& target)
{
return 100 * count<float>(predicted == target) / target.
elements();
}
{
const int feat_len = train.
dims(1);
const int num_train = train.
dims(0);
const int num_test = test.
dims(0);
array dist = constant(0, num_train, num_test);
for (int ii = 0; ii < feat_len; ii++) {
array train_i = train(span, ii);
array test_i = test (span, ii).
T();
array train_tiled = tile(train_i, 1, num_test);
array test_tiled = tile( test_i, num_train, 1 );
dist = dist + abs(train_tiled - test_tiled);
}
return dist;
}
{
array dist = distance(train_feats, test_feats);
return train_labels(idx);
}
int num_classes, int num_models, int sample_size)
{
int num_train = train_feats.
dims(0);
int num_test = test_feats.
dims(0);
for (int i = 0; i < num_models; i++) {
array train_labels_ii = train_labels(ii);
array labels_ii = knn(train_feats_ii, test_feats, train_labels_ii);
array lidx = labels_ii * num_test + off;
labels_all(lidx) = labels_all(lidx) + 1;
}
max(val, labels, labels_all, 1);
return labels;
}
void bagging_demo(bool console, int perc)
{
array train_images, train_labels;
array test_images, test_labels;
int num_train, num_test, num_classes;
float frac = (float)(perc) / 100.0;
setup_mnist<false>(&num_classes, &num_train, &num_test,
train_images, test_images,
train_labels, test_labels, frac);
int feature_length = train_images.
elements() / num_train;
array train_feats =
moddims(train_images, feature_length, num_train).
T();
array test_feats =
moddims(test_images , feature_length, num_test ).
T();
int num_models = 10;
int sample_size = 1000;
timer::start();
array res_labels = bagging(train_feats, test_feats, train_labels,
num_classes, num_models, sample_size);
double test_time = timer::stop();
printf("Accuracy on testing data: %2.2f\n",
accuracy(res_labels , test_labels));
printf("Prediction time: %4.4f\n", test_time);
if (false && !console) {
display_results<false>(test_images, res_labels, test_labels.
T(), 20);
}
}
int main(int argc, char** argv)
{
int device = argc > 1 ? atoi(argv[1]) : 0;
bool console = argc > 2 ? argv[2][0] == '-' : false;
int perc = argc > 3 ? atoi(argv[3]) : 60;
try {
bagging_demo(console, perc);
std::cerr << ae.
what() << std::endl;
}
return 0;
}
A multi dimensional data container.
Definition array.h:27
Definition exception.h:20
virtual const char * what() const
Definition exception.h:34
seq is used to create seq for indexing af::array
Definition seq.h:46
AFAPI array floor(const array &in)
C++ Interface for flooring an array of numbers.
array constant(T val, const dim4 &dims, const dtype ty=(af_dtype) dtype_traits< T >::ctype)
AFAPI array randu(const dim4 &dims, const dtype ty=f32)
AFAPI void setDevice(const int device)
Sets the current device.
AFAPI array lookup(const array &in, const array &idx, const int dim=-1)
Lookup the values of input array based on index.
AFAPI array moddims(const array &in, const unsigned ndims, const dim_t *const dims)
dim4 dims() const
Get dimensions of the array.
void eval() const
Evaluate any JIT expressions to generate data for the array.
array T() const
Get the transposed the array.
dim_t elements() const
get the number of elements in array
AFAPI array max(const array &in, const int dim=-1)
C++ Interface for maximum values in an array.
AFAPI array min(const array &in, const int dim=-1)
C++ Interface for minimum values in an array.
Definition algorithm.h:15