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Fix unit weight matrix test

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This commit is contained in:
Matúš Námešný
2024-02-19 22:27:21 +01:00
parent 02fc9e4e8b
commit dbc206d18c
1 changed files with 65 additions and 25 deletions
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90
test/layers/test_dense.cpp
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@@ -6,20 +6,45 @@
class DenseLayerTest : public CublasTestFixture {
protected:
};
Layers::Dense commonTestSetup(int inputSize, int outputSize, std::vector<float>& input, std::vector<std::vector<float>>& weights, std::vector<float>& biases, float*& d_input, float*& d_output) {
// Create Dense layer
Layers::Dense denseLayer(inputSize, outputSize, cublasHandle);
// Set weights and biases
denseLayer.setWeights(weights);
denseLayer.setBiases(biases);
TEST_F(DenseLayerTest, Forward) {
// Allocate device memory
cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * input.size());
EXPECT_EQ(cudaStatus, cudaSuccess);
cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * outputSize);
EXPECT_EQ(cudaStatus, cudaSuccess);
// Copy input to device
cublasStatus = cublasSetVector(input.size(), sizeof(float), input.data(), 1, d_input, 1);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
return denseLayer;
}
void commonTestTeardown(float* d_input, float* d_output) {
// Free device memory
cudaFree(d_input);
cudaFree(d_output);
}
cudaError_t cudaStatus;
cublasStatus_t cublasStatus;
};
TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
int inputSize = 3;
int outputSize = 3;
Layers::Dense denseLayer(inputSize, outputSize, cublasHandle);
std::vector<float> input = {1.0f, 2.0f, 3.0f};
// Initialize a weight matrix
std::vector<std::vector<float>> weights(inputSize, std::vector<float>(outputSize, 0.0f));
for (int i = 0; i < inputSize; ++i) {
for (int j = 0; j < outputSize; ++j) {
@@ -28,32 +53,15 @@ TEST_F(DenseLayerTest, Forward) {
}
}
}
// Set the weights
denseLayer.setWeights(weights);
// Initialize and set a bias vector
std::vector<float> biases(outputSize, 1.0f);
denseLayer.setBiases(biases);
std::vector<float> input = {1.0f, 2.0f, 3.0f};
std::vector<float> output(outputSize);
float* d_input;
float* d_output;
cudaStatus =cudaMalloc((void**)&d_input, sizeof(float) * input.size());
EXPECT_EQ(cudaStatus, cudaSuccess);
cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * outputSize);
EXPECT_EQ(cudaStatus, cudaSuccess);
cublasStatus =cublasSetVector(input.size(), sizeof(float), input.data(), 1, d_input, 1);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
// Perform forward pass
Layers::Dense denseLayer = commonTestSetup(inputSize, outputSize, input, weights, biases, d_input, d_output);
denseLayer.forward(d_input, d_output);
std::vector<float> output(outputSize);
cublasStatus = cublasGetVector(outputSize, sizeof(float), d_output, 1, output.data(), 1);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
@@ -62,6 +70,38 @@ TEST_F(DenseLayerTest, Forward) {
EXPECT_FLOAT_EQ(output[1], 3.0f);
EXPECT_FLOAT_EQ(output[2], 4.0f);
cudaFree(d_input);
cudaFree(d_output);
commonTestTeardown(d_input, d_output);
}
TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
int inputSize = 5;
int outputSize = 4;
std::vector<float> input = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f};
std::vector<std::vector<float>> weights = {
{0.5f, 1.0f, 0.2f, 0.8f},
{1.2f, 0.3f, 1.5f, 0.4f},
{0.7f, 1.8f, 0.9f, 0.1f},
{0.4f, 2.0f, 0.6f, 1.1f},
{1.3f, 0.5f, 0.0f, 1.7f}
};
std::vector<float> biases = {0.2f, 0.5f, 0.7f, 1.1f};
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(inputSize, outputSize, input, weights, biases, d_input, d_output);
denseLayer.forward(d_input, d_output);
std::vector<float> output(outputSize);
cublasStatus = cublasGetVector(outputSize, sizeof(float), d_output, 1, output.data(), 1);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
std::vector<float> expectedOutput = {3.4f, 4.4f, 5.6f, 7.4f};
for (int i = 0; i < outputSize; ++i) {
EXPECT_NEAR(output[i], expectedOutput[i], 1e-4); // Allow small tolerance for floating-point comparison
}
commonTestTeardown(d_input, d_output);
}