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Andre Martins 2016-09-14 08:43:58 +01:00
commit 76cda34544
4 changed files with 28 additions and 113 deletions
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96
marian/.project
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@ -26,99 +26,9 @@
</natures>
<linkedResources>
<link>
<name>CMakeLists.txt</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/CMakeLists.txt</locationURI>
</link>
<link>
<name>compile_time_crc32.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/compile_time_crc32.h</locationURI>
</link>
<link>
<name>definitions.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/definitions.h</locationURI>
</link>
<link>
<name>exception.cpp</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/exception.cpp</locationURI>
</link>
<link>
<name>exception.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/exception.h</locationURI>
</link>
<link>
<name>expression_operators.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/expression_operators.h</locationURI>
</link>
<link>
<name>expressions.cu</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/expressions.cu</locationURI>
</link>
<link>
<name>expressions.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/expressions.h</locationURI>
</link>
<link>
<name>graph.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/graph.h</locationURI>
</link>
<link>
<name>graph_operators.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/graph_operators.h</locationURI>
</link>
<link>
<name>keywords.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/keywords.h</locationURI>
</link>
<link>
<name>marian.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/marian.h</locationURI>
</link>
<link>
<name>mnist.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/mnist.h</locationURI>
</link>
<link>
<name>tensor.cu</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/tensor.cu</locationURI>
</link>
<link>
<name>tensor.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/tensor.h</locationURI>
</link>
<link>
<name>tensor_operators.cu</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/tensor_operators.cu</locationURI>
</link>
<link>
<name>tensor_operators.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/tensor_operators.h</locationURI>
</link>
<link>
<name>test.cu</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/test.cu</locationURI>
</link>
<link>
<name>thrust_functions.h</name>
<type>1</type>
<locationURI>PARENT-1-PROJECT_LOC/src/thrust_functions.h</locationURI>
<name>src</name>
<type>2</type>
<locationURI>PARENT-1-PROJECT_LOC/src</locationURI>
</link>
</linkedResources>
</projectDescription>

12
src/mnist.h
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@ -11,8 +11,6 @@ namespace mnist {
typedef unsigned char uchar;
const size_t IMAGE_SIZE = 784;
const size_t LABEL_SIZE = 10;
const size_t IMAGE_MAGIC_NUMBER = 2051;
const size_t LABEL_MAGIC_NUMBER = 2049;
@ -23,7 +21,7 @@ auto reverseInt = [](int i) {
return ((int)c1 << 24) + ((int)c2 << 16) + ((int)c3 << 8) + c4;
};
std::vector<float> ReadImages(const std::string& full_path, int& number_of_images) {
std::vector<float> ReadImages(const std::string& full_path, int& number_of_images, int imgSize) {
std::ifstream file(full_path);
if (! file.is_open())
@ -42,9 +40,9 @@ std::vector<float> ReadImages(const std::string& full_path, int& number_of_image
file.read((char *)&n_rows, sizeof(n_rows)), n_rows = reverseInt(n_rows);
file.read((char *)&n_cols, sizeof(n_cols)), n_cols = reverseInt(n_cols);
assert(n_rows * n_cols == IMAGE_SIZE);
assert(n_rows * n_cols == imgSize);
int n = number_of_images * IMAGE_SIZE;
int n = number_of_images * imgSize;
std::vector<float> _dataset(n);
for (int i = 0; i < n; i++) {
@ -55,7 +53,7 @@ std::vector<float> ReadImages(const std::string& full_path, int& number_of_image
return _dataset;
}
std::vector<float> ReadLabels(const std::string& full_path, int& number_of_labels) {
std::vector<float> ReadLabels(const std::string& full_path, int& number_of_labels, int label_size) {
std::ifstream file(full_path);
if (! file.is_open())
@ -70,7 +68,7 @@ std::vector<float> ReadLabels(const std::string& full_path, int& number_of_label
file.read((char *)&number_of_labels, sizeof(number_of_labels)), number_of_labels = reverseInt(number_of_labels);
int n = number_of_labels * LABEL_SIZE;
int n = number_of_labels * label_size;
std::vector<float> _dataset(n, 0.0f);
for (int i = 0; i < number_of_labels; i++) {

2
src/tensor.h
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@ -155,7 +155,7 @@ class TensorImpl {
void set(const std::vector<Float> &values) {
size_t totSize = std::accumulate(shape().begin(), shape().end(),
1, std::multiplies<int>());
std::cerr << "totSize=" << totSize << " " << values.size() << std::endl;
std::cerr << "tensor size=" << totSize << " vector size=" << values.size() << std::endl;
assert(totSize == values.size());
thrust::copy(values.begin(), values.end(), data_.begin());
}

31
src/test.cu
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@ -12,31 +12,38 @@ int main(int argc, char** argv) {
using namespace marian;
using namespace keywords;
const size_t IMAGE_SIZE = 784;
const size_t LABEL_SIZE = 10;
Expr x = input(shape={whatevs, 784}, name="X");
Expr y = input(shape={whatevs, 10}, name="Y");
Expr x = input(shape={whatevs, IMAGE_SIZE}, name="X");
Expr y = input(shape={whatevs, LABEL_SIZE}, name="Y");
Expr w = param(shape={784, 10}, name="W0");
Expr b = param(shape={1, 10}, name="b0");
Expr w = param(shape={IMAGE_SIZE, LABEL_SIZE}, name="W0");
Expr b = param(shape={1, LABEL_SIZE}, name="b0");
auto scores = dot(x, w) + b;
auto lr = softmax_fast(scores, axis=1, name="pred");
auto graph = -mean(sum(y * log(lr), axis=1), axis=0, name="cost");
cerr << "lr=" << lr.Debug() << endl;
Tensor tx({500, 784}, 1);
Tensor ty({500, 10}, 1);
#if 0
int numImg, imgSize;
vector<float> images = datasets::mnist::ReadImages("../examples/mnist/t10k-images-idx3-ubyte", numImg, imgSize);
vector<int> labels = datasets::mnist::ReadLabels("../examples/mnist/t10k-labels-idx1-ubyte");
int numofdata;
vector<float> images = datasets::mnist::ReadImages("../examples/mnist/t10k-images-idx3-ubyte", numofdata, IMAGE_SIZE);
vector<float> labels = datasets::mnist::ReadLabels("../examples/mnist/t10k-labels-idx1-ubyte", numofdata, LABEL_SIZE);
cerr << "images=" << images.size() << " labels=" << labels.size() << endl;
cerr << "numofdata=" << numofdata << endl;
Tensor tx({numofdata, IMAGE_SIZE}, 1);
Tensor ty({numofdata, LABEL_SIZE}, 1);
tx.Load(images);
//ty.Load(labels);
ty.Load(labels);
cerr << "tx=" << tx.Debug() << endl;
cerr << "ty=" << ty.Debug() << endl;
#else
Tensor tx({500, 784}, 1);
Tensor ty({500, 10}, 1);
#endif
x = tx;