Start dense layer implementation

src/layers/dense.cpp

@@ -0,0 +1,54 @@
+#include "dense.h"
+#include <cublas_v2.h>
+
+
+Layers::Dense::Dense(int inputSize, int outputSize, cublasHandle_t cublasHandle)
+    : inputSize(inputSize), outputSize(outputSize), cublasHandle(cublasHandle) {
+
+    // Allocate memory for weights and biases
+    weights.resize(inputSize * outputSize);
+    biases.resize(outputSize);
+
+    // Initialize weights and biases (you may customize this part)
+    initializeWeights();
+    initializeBiases();
+
+    // Allocate GPU memory for weights and biases
+    cudaMalloc((void**)&d_weights, sizeof(float) * weights.size());
+    cudaMalloc((void**)&d_biases, sizeof(float) * biases.size());
+
+    // Copy weights and biases to GPU
+    cudaMemcpy(d_weights, weights.data(), sizeof(float) * weights.size(), cudaMemcpyHostToDevice);
+    cudaMemcpy(d_biases, biases.data(), sizeof(float) * biases.size(), cudaMemcpyHostToDevice);
+}
+
+Layers::Dense::~Dense() {
+    // Free GPU memory
+    cudaFree(d_weights);
+    cudaFree(d_biases);
+}
+
+void Layers::Dense::initializeWeights() {
+    
+    float range = sqrt((float) 6/(inputSize + outputSize));
+
+    for (float& weight : weights) {
+        weight = static_cast<float>(rand()) / RAND_MAX * 2.0 * range - range;
+    }
+}
+
+void Layers::Dense::initializeBiases() {
+    for (float& bias : biases) {
+        bias = static_cast<float>(rand()) / RAND_MAX * 2.0f - 1.0f;
+    }
+}
+
+void Layers::Dense::forward(const float* input, float* output) {
+    // Perform matrix multiplication: output = weights * input + biases
+    const float alpha = 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
+    cublasSaxpy(cublasHandle, outputSize, &alpha, d_biases, 1, output, 1);
+}