Add dense sigmoid test

This commit is contained in:
2024-02-27 21:48:08 +01:00
parent 9747abe53e
commit 19ee20ea66

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@@ -17,10 +17,13 @@ class DenseLayerTest : public CublasTestFixture {
std::vector<std::vector<float>>& weights,
std::vector<float>& biases,
float*& d_input,
float*& d_output
float*& d_output,
std::string activation
) {
// Create Dense layer
Layers::Dense denseLayer(inputSize, outputSize, "linear", cublasHandle);
Layers::Dense denseLayer(
inputSize, outputSize, activation, cublasHandle
);
// Set weights and biases
denseLayer.setWeights(weights);
@@ -61,7 +64,7 @@ TEST_F(DenseLayerTest, Init) {
// std::cout << "Dense layer: input size = " << inputSize << ",
// output size = " << outputSize << std::endl;
Layers::Dense denseLayer(
inputSize, outputSize, "linear", cublasHandle
inputSize, outputSize, "sigmoid", cublasHandle
);
}
}
@@ -79,12 +82,12 @@ TEST_F(DenseLayerTest, setWeights) {
{1.3f, 0.5f, 0.0f, 1.7f}
};
Layers::Dense denseLayer(inputSize, outputSize, "linear", cublasHandle);
Layers::Dense denseLayer(inputSize, outputSize, "sigmoid", cublasHandle);
denseLayer.setWeights(weights);
}
TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
TEST_F(DenseLayerTest, ForwardUnitWeightMatrixLinear) {
int inputSize = 3;
int outputSize = 3;
@@ -106,7 +109,8 @@ TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights, biases, d_input, d_output
inputSize, outputSize, input, weights, biases, d_input, d_output,
"linear"
);
denseLayer.forward(d_input, d_output);
@@ -124,7 +128,7 @@ TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
commonTestTeardown(d_input, d_output);
}
TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
TEST_F(DenseLayerTest, ForwardRandomWeightMatrixRelu) {
int inputSize = 5;
int outputSize = 4;
@@ -142,7 +146,7 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights, biases, d_input, d_output
inputSize, outputSize, input, weights, biases, d_input, d_output, "relu"
);
denseLayer.forward(d_input, d_output);
@@ -153,7 +157,10 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
std::vector<float> expectedOutput = {10.4f, 13.0f, 8.9f, 9.3f};
// weights * inputs = 13.1, 17.5, 8.3, 14.8
// + biases = 13.3, 18, 9, 15.9
std::vector<float> expectedOutput = {13.3f, 18.0f, 9.0f, 15.9f};
for (int i = 0; i < outputSize; ++i) {
EXPECT_NEAR(
output[i], expectedOutput[i], 1e-4
@@ -162,3 +169,50 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
commonTestTeardown(d_input, d_output);
}
TEST_F(DenseLayerTest, ForwardRandomWeightMatrixSigmoid) {
int inputSize = 5;
int outputSize = 4;
std::vector<float> input = {0.1f, 0.2f, 0.3f, 0.4f, 0.5f};
std::vector<std::vector<float>> weights = {
{0.8f, 0.7f, 0.7f, 0.3f, 0.8f},
{0.1f, 0.4f, 0.8f, 0.0f, 0.2f},
{0.2f, 0.5f, 0.7f, 0.3f, 0.0f},
{0.1f, 0.7f, 0.6f, 1.0f, 0.4f}
};
std::vector<float> biases = {0.1f, 0.2f, 0.3f, 0.4f};
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights, biases, d_input, d_output,
"sigmoid"
);
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);
// weights * input = 0.95, 0.43, 0.45, 0.93
// + biases = 1.05, 0.63, 0.75, 1.33
// sigmoid = 0.740775, 0.652489, 0.679179, 0.790841
std::vector<float> expectedOutput = {
0.740775f, 0.652489f, 0.679179f, 0.790841f
};
for (int i = 0; i < outputSize; ++i) {
EXPECT_NEAR(
output[i], expectedOutput[i], 1e-5
);
}
commonTestTeardown(d_input, d_output);
}