Mathis/CUDANet
1
0
Fork 0
mirror of https://github.com/lordmathis/CUDANet.git synced 2025-11-06 17:54:27 +00:00
Code Issues Packages Projects Releases Wiki Activity

Add toplevel CUDANet namespace

Browse Source
This commit is contained in:
Matúš Námešný
2024-03-17 16:08:53 +01:00
parent dc86cddeb7
commit 0c22fac64e
19 changed files with 183 additions and 149 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
test/layers/test_dense.cu
View File

@@ -8,17 +8,17 @@
class DenseLayerTest : public ::testing::Test {
protected:
Layers::Dense commonTestSetup(
int inputSize,
int outputSize,
std::vector<float>& input,
float* weights,
float* biases,
float*& d_input,
Layers::Activation activation
CUDANet::Layers::Dense commonTestSetup(
int inputSize,
int outputSize,
std::vector<float>& input,
float* weights,
float* biases,
float*& d_input,
CUDANet::Layers::Activation activation
) {
// Create Dense layer
Layers::Dense denseLayer(inputSize, outputSize, activation);
CUDANet::Layers::Dense denseLayer(inputSize, outputSize, activation);
// Set weights and biases
denseLayer.setWeights(weights);
@@ -52,8 +52,8 @@ TEST_F(DenseLayerTest, Init) {
int inputSize = i;
int outputSize = j;
Layers::Dense denseLayer(
inputSize, outputSize, Layers::Activation::SIGMOID
CUDANet::Layers::Dense denseLayer(
inputSize, outputSize, CUDANet::Layers::Activation::SIGMOID
);
}
}
@@ -73,8 +73,8 @@ TEST_F(DenseLayerTest, setWeights) {
};
// clang-format on
Layers::Dense denseLayer(
inputSize, outputSize, Layers::Activation::SIGMOID
CUDANet::Layers::Dense denseLayer(
inputSize, outputSize, CUDANet::Layers::Activation::SIGMOID
);
denseLayer.setWeights(weights.data());
@@ -99,9 +99,9 @@ TEST_F(DenseLayerTest, ForwardUnitWeightMatrixLinear) {
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
CUDANet::Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights.data(), biases.data(), d_input,
Layers::Activation::NONE
CUDANet::Layers::Activation::NONE
);
d_output = denseLayer.forward(d_input);
@@ -140,9 +140,9 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrixRelu) {
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
CUDANet::Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights.data(), biases.data(), d_input,
Layers::Activation::RELU
CUDANet::Layers::Activation::RELU
);
d_output = denseLayer.forward(d_input);
@@ -185,9 +185,9 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrixSigmoid) {
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
CUDANet::Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights.data(), biases.data(), d_input,
Layers::Activation::SIGMOID
CUDANet::Layers::Activation::SIGMOID
);
d_output = denseLayer.forward(d_input);