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This commit is contained in:
Hieu Hoang 2016-09-14 16:25:58 +02:00
parent a573eecf5c
commit f0f0dbe9ee
3 changed files with 42 additions and 31 deletions
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6
src/tensor.cu
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@ -80,12 +80,12 @@ void Tensor::Load(const std::string &path)
}
strm.close();
Load(hostData);
Load(hostData.begin(), hostData.begin());
}
void Tensor::Load(const std::vector<float> &values)
void Tensor::Load(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end)
{
pimpl_->set(values);
pimpl_->set(begin, end);
}
}

10
src/tensor.h
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@ -158,11 +158,11 @@ class TensorImpl {
thrust::fill(data_.begin(), data_.end(), value);
}
void set(const std::vector<Float> &values) {
void set(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end) {
size_t totSize = GetTotalSize(shape());
std::cerr << "tensor size=" << totSize << " vector size=" << values.size() << std::endl;
assert(totSize == values.size());
thrust::copy(values.begin(), values.end(), data_.begin());
//std::cerr << "tensor size=" << totSize << " vector size=" << values.size() << std::endl;
//assert(totSize == values.size());
thrust::copy(begin, end, data_.begin());
}
std::string Debug() const
@ -275,7 +275,7 @@ class Tensor {
}
void Load(const std::string &path);
void Load(const std::vector<float> &values);
void Load(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end);
};

57
src/test.cu
View File

@ -12,6 +12,7 @@ int main(int argc, char** argv) {
using namespace marian;
using namespace keywords;
const size_t BATCH_SIZE = 500;
const size_t IMAGE_SIZE = 784;
const size_t LABEL_SIZE = 10;
@ -31,41 +32,51 @@ int main(int argc, char** argv) {
//vector<float> labels = datasets::mnist::ReadLabels("../examples/mnist/t10k-labels-idx1-ubyte", numofdata, LABEL_SIZE);
vector<float> images = datasets::mnist::ReadImages("../examples/mnist/train-images-idx3-ubyte", numofdata, IMAGE_SIZE);
vector<float> labels = datasets::mnist::ReadLabels("../examples/mnist/train-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);
size_t startInd = 0;
size_t startIndData = 0;
while (startInd < numofdata) {
size_t batchSize = (startInd + BATCH_SIZE < numofdata) ? BATCH_SIZE : numofdata - startInd;
cerr << "startInd=" << startInd
<< " startIndData=" << startIndData
<< " batchSize=" << batchSize << endl;
tx.Load(images);
ty.Load(labels);
Tensor tx({numofdata, IMAGE_SIZE}, 1);
Tensor ty({numofdata, LABEL_SIZE}, 1);
//cerr << "tx=" << Debug(tx.shape()) << endl;
//cerr << "ty=" << Debug(ty.shape()) << endl;
tx.Load(images.begin() + startIndData, images.begin() + startIndData + batchSize * IMAGE_SIZE);
ty.Load(labels.begin() + startInd, labels.begin() + startInd + batchSize);
x = tx;
y = ty;
//cerr << "tx=" << Debug(tx.shape()) << endl;
//cerr << "ty=" << Debug(ty.shape()) << endl;
cerr << "x=" << Debug(x.val().shape()) << endl;
cerr << "y=" << Debug(y.val().shape()) << endl;
x = tx;
y = ty;
cerr << "x=" << Debug(x.val().shape()) << endl;
cerr << "y=" << Debug(y.val().shape()) << endl;
graph.forward(500);
graph.forward(batchSize);
cerr << "w=" << Debug(w.val().shape()) << endl;
cerr << "b=" << Debug(b.val().shape()) << endl;
std::cerr << "z: " << Debug(z.val().shape()) << endl;
std::cerr << "lr: " << Debug(lr.val().shape()) << endl;
std::cerr << "Log-likelihood: " << Debug(graph.val().shape()) << endl ;
cerr << "w=" << Debug(w.val().shape()) << endl;
cerr << "b=" << Debug(b.val().shape()) << endl;
std::cerr << "z: " << Debug(z.val().shape()) << endl;
std::cerr << "lr: " << Debug(lr.val().shape()) << endl;
std::cerr << "Log-likelihood: " << Debug(graph.val().shape()) << endl ;
//std::cerr << "scores=" << scores.val().Debug() << endl;
std::cerr << "lr=" << lr.val().Debug() << endl;
//std::cerr << "scores=" << scores.val().Debug() << endl;
std::cerr << "lr=" << lr.val().Debug() << endl;
graph.backward();
//std::cerr << graph["pred"].val()[0] << std::endl;
graph.backward();
//std::cerr << graph["pred"].val()[0] << std::endl;
startInd += batchSize;
startIndData += batchSize * IMAGE_SIZE;
}
// XOR