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Validation on 2-layer Keras model

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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
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51
src/validate_mnist_batch.cu
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@ -21,22 +21,38 @@ int main(int argc, char** argv) {
std::cerr << "\tDone." << std::endl; std::cerr << "\tDone." << std::endl;
std::cerr << "Loading model params..."; std::cerr << "Loading model params...";
NpzConverter converter("../scripts/test_model/model.npz"); NpzConverter converter("../scripts/test_model_multi/model.npz");
std::vector<float> wData; std::vector<float> wData1;
Shape wShape; Shape wShape1;
converter.Load("weights", wData, wShape); 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; auto initW1 = [wData1](Tensor t) {
Shape bShape; t.set(wData1);
converter.Load("bias", bData, bShape);
auto initW = [wData](Tensor t) {
t.set(wData);
}; };
auto initB = [bData](Tensor t) { auto initB1 = [bData1](Tensor t) {
t.set(bData); t.set(bData1);
};
auto initW2 = [wData2](Tensor t) {
t.set(wData2);
};
auto initB2 = [bData2](Tensor t) {
t.set(bData2);
}; };
std::cerr << "\tDone." << std::endl; 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 x = input(shape={whatevs, IMAGE_SIZE}, name="X");
auto y = input(shape={whatevs, LABEL_SIZE}, name="Y"); auto y = input(shape={whatevs, LABEL_SIZE}, name="Y");
auto w = param(shape={IMAGE_SIZE, LABEL_SIZE}, name="W0", init=initW); auto w1 = param(shape={IMAGE_SIZE, 100}, name="W0", init=initW1);
auto b = param(shape={1, LABEL_SIZE}, name="b0", init=initB); 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..."; 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; 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 (testLabels[startId * LABEL_SIZE + i + j]) correct = j;
if (results[i + j] > results[i + predicted]) predicted = j; if (results[i + j] > results[i + predicted]) predicted = j;
} }
/*std::cerr << "CORRECT: " << correct << " PREDICTED: " << predicted << std::endl;*/
acc += (correct == predicted); acc += (correct == predicted);
} }