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Add toplevel CUDANet namespace

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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
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78
test/layers/test_conv2d.cu
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@@ -7,20 +7,20 @@
class Conv2dTest : public ::testing::Test {
protected:
Layers::Conv2d commonTestSetup(
int inputSize,
int inputChannels,
int kernelSize,
int stride,
Layers::Padding padding,
int numFilters,
Layers::Activation activation,
std::vector<float>& input,
float* kernels,
float*& d_input
CUDANet::Layers::Conv2d commonTestSetup(
int inputSize,
int inputChannels,
int kernelSize,
int stride,
CUDANet::Layers::Padding padding,
int numFilters,
CUDANet::Layers::Activation activation,
std::vector<float>& input,
float* kernels,
float*& d_input
) {
// Create Conv2d layer
Layers::Conv2d conv2d(
CUDANet::Layers::Conv2d conv2d(
inputSize, inputChannels, kernelSize, stride, padding, numFilters,
activation
);
@@ -53,13 +53,13 @@ class Conv2dTest : public ::testing::Test {
};
TEST_F(Conv2dTest, SimpleTest) {
int inputSize = 4;
int inputChannels = 1;
int kernelSize = 2;
int stride = 1;
Layers::Padding padding = Layers::Padding::VALID;
int numFilters = 1;
Layers::Activation activation = Layers::Activation::NONE;
int inputSize = 4;
int inputChannels = 1;
int kernelSize = 2;
int stride = 1;
CUDANet::Layers::Padding padding = CUDANet::Layers::Padding::VALID;
int numFilters = 1;
CUDANet::Layers::Activation activation = CUDANet::Layers::Activation::NONE;
std::vector<float> input = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f,
7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f,
@@ -74,7 +74,7 @@ TEST_F(Conv2dTest, SimpleTest) {
float* d_input;
float* d_output;
Layers::Conv2d conv2d = commonTestSetup(
CUDANet::Layers::Conv2d conv2d = commonTestSetup(
inputSize, inputChannels, kernelSize, stride, padding, numFilters,
activation, input, kernels.data(), d_input
);
@@ -102,13 +102,13 @@ TEST_F(Conv2dTest, SimpleTest) {
}
TEST_F(Conv2dTest, PaddedTest) {
int inputSize = 5;
int inputChannels = 3;
int kernelSize = 3;
int stride = 1;
Layers::Padding padding = Layers::Padding::SAME;
int numFilters = 2;
Layers::Activation activation = Layers::Activation::NONE;
int inputSize = 5;
int inputChannels = 3;
int kernelSize = 3;
int stride = 1;
CUDANet::Layers::Padding padding = CUDANet::Layers::Padding::SAME;
int numFilters = 2;
CUDANet::Layers::Activation activation = CUDANet::Layers::Activation::NONE;
// clang-format off
std::vector<float> input = {
@@ -163,7 +163,7 @@ TEST_F(Conv2dTest, PaddedTest) {
float* d_input;
float* d_output;
Layers::Conv2d conv2d = commonTestSetup(
CUDANet::Layers::Conv2d conv2d = commonTestSetup(
inputSize, inputChannels, kernelSize, stride, padding, numFilters,
activation, input, kernels.data(), d_input
);
@@ -177,7 +177,8 @@ TEST_F(Conv2dTest, PaddedTest) {
);
cudaMemcpy(
output.data(), d_output,
sizeof(float) * conv2d.getOutputSize() * conv2d.getOutputSize() * numFilters,
sizeof(float) * conv2d.getOutputSize() * conv2d.getOutputSize() *
numFilters,
cudaMemcpyDeviceToHost
);
@@ -202,13 +203,13 @@ TEST_F(Conv2dTest, PaddedTest) {
}
TEST_F(Conv2dTest, StridedPaddedConvolution) {
int inputSize = 5;
int inputChannels = 2;
int kernelSize = 3;
int stride = 2;
int numFilters = 2;
Layers::Padding padding = Layers::Padding::SAME;
Layers::Activation activation = Layers::Activation::RELU;
int inputSize = 5;
int inputChannels = 2;
int kernelSize = 3;
int stride = 2;
int numFilters = 2;
CUDANet::Layers::Padding padding = CUDANet::Layers::Padding::SAME;
CUDANet::Layers::Activation activation = CUDANet::Layers::Activation::RELU;
// clang-format off
std::vector<float> input = {
@@ -248,7 +249,7 @@ TEST_F(Conv2dTest, StridedPaddedConvolution) {
float* d_input;
float* d_output;
Layers::Conv2d conv2d = commonTestSetup(
CUDANet::Layers::Conv2d conv2d = commonTestSetup(
inputSize, inputChannels, kernelSize, stride, padding, numFilters,
activation, input, kernels.data(), d_input
);
@@ -262,7 +263,8 @@ TEST_F(Conv2dTest, StridedPaddedConvolution) {
);
cudaMemcpy(
output.data(), d_output,
sizeof(float) * conv2d.getOutputSize() * conv2d.getOutputSize() * numFilters,
sizeof(float) * conv2d.getOutputSize() * conv2d.getOutputSize() *
numFilters,
cudaMemcpyDeviceToHost
);