Mathis/CUDANet
1
0
Fork 0
mirror of https://github.com/lordmathis/CUDANet.git synced 2025-11-06 01:34:22 +00:00
Code Issues Packages Projects Releases Wiki Activity

Improve test dense

Browse Source
This commit is contained in:
Matúš Námešný
2024-02-18 13:12:49 +01:00
parent ee1a8cc6e6
commit 4b6fff9bfd
2 changed files with 53 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
src/layers/dense.cpp
View File

@@ -45,14 +45,12 @@ void Layers::Dense::initializeBiases() {
} }
} }
void Layers::Dense::forward(const float* input, float* output) { void Layers::Dense::forward(const float* d_input, float* d_output) {
// Perform matrix multiplication: output = weights * input + biases
const float alpha = 1.0f; const float alpha = 1.0f;
const float beta = 1.0f; const float beta = 1.0f;
cublasSgemv(cublasHandle, CUBLAS_OP_N, inputSize, outputSize, &alpha, d_weights, inputSize, input, 1, &beta, output, 1);
// Add biases cublasSgemv(cublasHandle, CUBLAS_OP_N, inputSize, outputSize, &alpha, d_weights, inputSize, d_input, 1, &beta, d_output, 1);
cublasSaxpy(cublasHandle, outputSize, &alpha, d_biases, 1, output, 1); cublasSaxpy(cublasHandle, outputSize, &alpha, d_biases, 1, d_output, 1);
} }
void Layers::Dense::toCuda() { void Layers::Dense::toCuda() {

57
test/layers/test_dense.cpp
View File

@@ -1,4 +1,6 @@
#include "gtest/gtest.h" #include "gtest/gtest.h"
#include <cuda_runtime_api.h>
#include <driver_types.h>
#include "dense.h" #include "dense.h"
#include "test_cublas_fixture.h" #include "test_cublas_fixture.h"
@@ -9,16 +11,57 @@ protected:
TEST_F(DenseLayerTest, Forward) { TEST_F(DenseLayerTest, Forward) {
Layers::Dense denseLayer(3, 2, cublasHandle); cudaError_t cudaStatus;
cublasStatus_t cublasStatus;
// Create input and output arrays int inputSize = 3;
float input[3] = {1.0f, 2.0f, 3.0f}; int outputSize = 3;
float output[2] = {0.0f, 0.0f};
Layers::Dense denseLayer(inputSize, outputSize, cublasHandle);
// 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) {
if (i == j) {
weights[i][j] = 1.0f;
}
}
}
// 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 // Perform forward pass
denseLayer.forward(input, output); denseLayer.forward(d_input, d_output);
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 // Check if the output is a zero vector
EXPECT_FLOAT_EQ(output[0], 0.0f); EXPECT_FLOAT_EQ(output[0], 2.0f);
EXPECT_FLOAT_EQ(output[1], 0.0f); EXPECT_FLOAT_EQ(output[1], 3.0f);
EXPECT_FLOAT_EQ(output[2], 4.0f);
cudaFree(d_input);
cudaFree(d_output);
} }