Migrate conv2d layer

src/backends/cuda/layers/conv2d.cu

@@ -0,0 +1,73 @@
+#include <vector>
+
+#include "activation.hpp"
+#include "conv2d.hpp"
+#include "convolution.cuh"
+#include "cuda_helper.cuh"
+#include "layer.hpp"
+#include "matmul.cuh"
+#include "vector.cuh"
+
+using namespace CUDANet::Layers;
+
+void Conv2d::initCUDA() {
+    d_output = nullptr;
+    CUDA_CHECK(cudaMalloc(
+        (void**)&d_output,
+        sizeof(float) * outputSize.first * outputSize.second * numFilters
+    ));
+
+    d_weights = nullptr;
+    CUDA_CHECK(cudaMalloc(
+        (void**)&d_weights, sizeof(float) * kernelSize.first *
+                                kernelSize.second * inputChannels * numFilters
+    ));
+
+    d_biases = nullptr;
+    CUDA_CHECK(cudaMalloc((void**)&d_biases, sizeof(float) * numFilters));
+}
+
+void Conv2d::delCUDA() {
+    cudaFree(d_output);
+    cudaFree(d_weights);
+    cudaFree(d_biases);
+}
+
+void Conv2d::toCuda() {
+    CUDA_CHECK(cudaMemcpy(
+        d_weights, weights.data(),
+        sizeof(float) * kernelSize.first * kernelSize.second * inputChannels *
+            numFilters,
+        cudaMemcpyHostToDevice
+    ));
+
+    CUDA_CHECK(cudaMemcpy(
+        d_biases, biases.data(), sizeof(float) * numFilters,
+        cudaMemcpyHostToDevice
+    ));
+}
+
+float* Conv2d::forwardCUDA(const float* d_input) {
+    // Convolve
+    dim3 block(8, 8, 8);
+    dim3 grid(
+        (outputSize.first + block.x - 1) / block.x,
+        (outputSize.second + block.y - 1) / block.y,
+        (numFilters + block.z - 1) / block.z
+    );
+
+    CUDANet::Utils::clear(d_output, outputSize.first * outputSize.second * numFilters);
+
+    Kernels::convolution<<<grid, block>>>(
+        d_input, d_weights, d_biases, d_output, inputSize, inputChannels,
+        paddingSize, kernelSize, stride, numFilters, outputSize
+    );
+    CUDA_CHECK(cudaGetLastError());
+
+    // Apply activation
+    activation->activate(d_output);
+
+    CUDA_CHECK(cudaDeviceSynchronize());
+
+    return d_output;
+}