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Format source code using clang-format

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This commit is contained in:
Matúš Námešný
2024-02-27 18:51:22 +01:00
parent fb454de053
commit 48ba09b28d
12 changed files with 229 additions and 138 deletions
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75
test/layers/test_dense.cu
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@@ -1,14 +1,24 @@
#include "gtest/gtest.h"
#include <cuda_runtime_api.h>
#include <driver_types.h>
#include <iostream>
#include "activations.cuh"
#include "dense.cuh"
#include "gtest/gtest.h"
#include "test_cublas_fixture.cuh"
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) {
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, "linear", cublasHandle);
@@ -24,7 +34,9 @@ protected:
EXPECT_EQ(cudaStatus, cudaSuccess);
// Copy input to device
cublasStatus = cublasSetVector(input.size(), sizeof(float), input.data(), 1, d_input, 1);
cublasStatus = cublasSetVector(
input.size(), sizeof(float), input.data(), 1, d_input, 1
);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
return denseLayer;
@@ -36,28 +48,27 @@ protected:
cudaFree(d_output);
}
cudaError_t cudaStatus;
cudaError_t cudaStatus;
cublasStatus_t cublasStatus;
};
TEST_F(DenseLayerTest, Init) {
for (int i = 1; i < 100; ++i) {
for (int j = 1; j < 100; ++j) {
int inputSize = i;
int inputSize = i;
int outputSize = j;
// std::cout << "Dense layer: input size = " << inputSize << ", output size = " << outputSize << std::endl;
Layers::Dense denseLayer(inputSize, outputSize, "linear", cublasHandle);
}
// std::cout << "Dense layer: input size = " << inputSize << ",
// output size = " << outputSize << std::endl;
Layers::Dense denseLayer(
inputSize, outputSize, "linear", cublasHandle
);
}
}
}
TEST_F(DenseLayerTest, setWeights) {
int inputSize = 4;
int inputSize = 4;
int outputSize = 5;
std::vector<std::vector<float>> weights = {
@@ -71,17 +82,17 @@ TEST_F(DenseLayerTest, setWeights) {
Layers::Dense denseLayer(inputSize, outputSize, "linear", cublasHandle);
denseLayer.setWeights(weights);
}
TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
int inputSize = 3;
int inputSize = 3;
int outputSize = 3;
std::vector<float> input = {1.0f, 2.0f, 3.0f};
std::vector<std::vector<float>> weights(inputSize, std::vector<float>(outputSize, 0.0f));
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) {
if (i == j) {
@@ -94,11 +105,15 @@ TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
float* d_input;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(inputSize, outputSize, input, weights, biases, d_input, 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);
cublasStatus = cublasGetVector(
outputSize, sizeof(float), d_output, 1, output.data(), 1
);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
// Check if the output is a zero vector
@@ -110,7 +125,7 @@ TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
}
TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
int inputSize = 5;
int inputSize = 5;
int outputSize = 4;
std::vector<float> input = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f};
@@ -120,23 +135,29 @@ TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
{1.0f, 0.3f, 1.8f, 2.0f, 0.5f},
{0.2f, 1.5f, 0.9f, 0.6f, 0.0f},
{0.8f, 0.4f, 0.1f, 1.1f, 1.7f}
};
};
std::vector<float> biases = {0.2f, 0.5f, 0.7f, 1.1f};
float* d_input;
float* d_output;
float* d_output;
Layers::Dense denseLayer = commonTestSetup(
inputSize, outputSize, input, weights, biases, d_input, 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);
cublasStatus = cublasGetVector(
outputSize, sizeof(float), d_output, 1, output.data(), 1
);
EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
std::vector<float> expectedOutput = {10.4f, 13.0f, 8.9f, 9.3f};
for (int i = 0; i < outputSize; ++i) {
EXPECT_NEAR(output[i], expectedOutput[i], 1e-4); // Allow small tolerance for floating-point comparison
EXPECT_NEAR(
output[i], expectedOutput[i], 1e-4
); // Allow small tolerance for floating-point comparison
}
commonTestTeardown(d_input, d_output);