marian-nmt/marian
1
1
Fork 0
mirror of https://github.com/marian-nmt/marian.git synced 2024-11-04 14:04:24 +03:00
Code Issues Packages Projects Releases Wiki Activity

Validation on 2-layer Keras model

Browse Source
This commit is contained in:
Maximiliana Behnke 2016-09-15 17:41:58 +02:00
parent 4a1ab1f5b4
commit eba5b46225
1 changed files with 36 additions and 15 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

51
src/validate_mnist_batch.cu
View File

@ -21,22 +21,38 @@ int main(int argc, char** argv) {
std::cerr << "\tDone." << std::endl;
std::cerr << "Loading model params...";
NpzConverter converter("../scripts/test_model/model.npz");
NpzConverter converter("../scripts/test_model_multi/model.npz");
std::vector<float> wData;
Shape wShape;
converter.Load("weights", wData, wShape);
std::vector<float> wData1;
Shape wShape1;
converter.Load("weights1", wData1, wShape1);
std::vector<float> bData1;
Shape bShape1;
converter.Load("bias1", bData1, bShape1);
std::vector<float> wData2;
Shape wShape2;
converter.Load("weights2", wData2, wShape2);
std::vector<float> bData2;
Shape bShape2;
converter.Load("bias2", bData2, bShape2);
std::vector<float> bData;
Shape bShape;
converter.Load("bias", bData, bShape);
auto initW = [wData](Tensor t) {
t.set(wData);
auto initW1 = [wData1](Tensor t) {
t.set(wData1);
};
auto initB = [bData](Tensor t) {
t.set(bData);
auto initB1 = [bData1](Tensor t) {
t.set(bData1);
};
auto initW2 = [wData2](Tensor t) {
t.set(wData2);
};
auto initB2 = [bData2](Tensor t) {
t.set(bData2);
};
std::cerr << "\tDone." << std::endl;
@ -45,11 +61,15 @@ int main(int argc, char** argv) {
auto x = input(shape={whatevs, IMAGE_SIZE}, name="X");
auto y = input(shape={whatevs, LABEL_SIZE}, name="Y");
auto w = param(shape={IMAGE_SIZE, LABEL_SIZE}, name="W0", init=initW);
auto b = param(shape={1, LABEL_SIZE}, name="b0", init=initB);
auto w1 = param(shape={IMAGE_SIZE, 100}, name="W0", init=initW1);
auto b1 = param(shape={1, 100}, name="b0", init=initB1);
auto w2 = param(shape={100, LABEL_SIZE}, name="W1", init=initW2);
auto b2 = param(shape={1, LABEL_SIZE}, name="b1", init=initB2);
std::cerr << "Building model...";
auto predict = softmax(dot(x, w) + b, axis=1, name="pred");
auto layer1 = tanh(dot(x, w1) + b1);
auto layer2 = softmax(dot(layer1, w2) + b2, axis=1, name="layer2");
auto predict = layer2;
std::cerr << "Done." << std::endl;
@ -77,6 +97,7 @@ int main(int argc, char** argv) {
if (testLabels[startId * LABEL_SIZE + i + j]) correct = j;
if (results[i + j] > results[i + predicted]) predicted = j;
}
/*std::cerr << "CORRECT: " << correct << " PREDICTED: " << predicted << std::endl;*/
acc += (correct == predicted);
}