Rename files to .cu and fix IDX2C usage

src/layers/dense.cu

@@ -0,0 +1,83 @@
+#include "dense.h"
+#include "cuda_helper.h"
+#include <cstdlib>
+#include <cuda_runtime.h>
+#include <cublas_v2.h>
+#include <cstdio>
+#include <iostream>
+
+Layers::Dense::Dense(int inputSize, int outputSize, cublasHandle_t cublasHandle)
+    : inputSize(inputSize), outputSize(outputSize), cublasHandle(cublasHandle) {
+
+    // Allocate memory for weights and biases
+    weights.resize(outputSize * inputSize);
+    biases.resize(outputSize);
+
+    initializeWeights();
+    initializeBiases();
+
+    d_weights = nullptr;
+    d_biases = nullptr;
+
+    // Allocate GPU memory for weights and biases
+    CUDA_CHECK(cudaMalloc((void**)&d_weights, sizeof(float) * inputSize * outputSize));
+    CUDA_CHECK(cudaMalloc((void**)&d_biases, sizeof(float) * outputSize));
+
+    toCuda();
+}
+
+Layers::Dense::~Dense() {
+    // Free GPU memory
+    cudaFree(d_weights);
+    cudaFree(d_biases);
+}
+
+void Layers::Dense::initializeWeights() {
+
+    for (int j = 0; j < inputSize; ++j) {
+        for (int i = 0; i < outputSize; ++i) {
+            int idx = IDX2C(i, j, outputSize);
+            weights[idx] = 0.0f;
+        }
+    }
+}
+
+void Layers::Dense::initializeBiases() {
+    std::fill(biases.begin(), biases.end(), 0.0f);
+}
+
+void Layers::Dense::forward(const float* d_input, float* d_output) {
+    const float alpha = 1.0f;
+    const float beta = 1.0f;
+
+    CUBLAS_CHECK(cublasSgemv(cublasHandle, CUBLAS_OP_N, inputSize, outputSize, &alpha, d_weights, inputSize, d_input, 1, &beta, d_output, 1));
+    CUBLAS_CHECK(cublasSaxpy(cublasHandle, outputSize, &alpha, d_biases, 1, d_output, 1));
+}
+
+void Layers::Dense::toCuda() {
+    CUBLAS_CHECK(cublasSetMatrix(outputSize, inputSize, sizeof(float), weights.data(), outputSize, d_weights, outputSize));
+    CUBLAS_CHECK(cublasSetVector(biases.size(), sizeof(float), biases.data(), 1, d_biases, 1));
+}
+
+void Layers::Dense::setWeights(const std::vector<std::vector<float>>& weights_input) {
+    int numWeights = inputSize * outputSize;
+
+    if (weights.size() != numWeights) {
+        std::cerr << "Invalid number of weights" << std::endl;
+        exit(EXIT_FAILURE);
+    }
+
+    for (int j = 0; j < inputSize; ++j) {
+        for (int i = 0; i < outputSize; ++i) {
+            int idx = IDX2C(i, j, outputSize);
+            weights[idx] = weights_input[i][j];
+        }
+    }
+
+    toCuda();
+}
+
+void Layers::Dense::setBiases(const std::vector<float>& biases_input) {
+    std::copy(biases_input.begin(), biases_input.end(), biases.begin());
+    toCuda();
+}