Implement concat layer

include/layers/concat.cuh

@@ -0,0 +1,45 @@
+#ifndef CUDANET_CONCAT_LAYER_H
+#define CUDANET_CONCAT_LAYER_H
+
+#include <ilayer.cuh>
+
+namespace CUDANet::Layers {
+
+/**
+ * @brief Concatenate layers
+ *
+ */
+class Concat {
+  public:
+    /**
+     * @brief Create a new Concat layer
+     * 
+     * @param layers Layers to concatenate
+     */
+    Concat(const unsigned int inputASize, const unsigned int inputBSize);
+
+    /**
+     * @brief Destroy the Concat layer
+     * 
+     */
+    ~Concat();
+
+    /**
+     * @brief Forward pass of the concat layer
+     *
+     * @param d_input_A Device pointer to the first input
+     * @param d_input_B Device pointer to the second input
+     * @return Device pointer to the output
+     */
+    float* forward(const float* d_input_A, const float* d_input_B);
+
+  private:
+    unsigned int inputASize;
+    unsigned int inputBSize;
+
+    float* d_output;
+};
+
+}  // namespace CUDANet::Layers
+
+#endif  // CUDANET_CONCAT_LAYER_H

include/layers/ilayer.cuh

@@ -64,18 +64,6 @@ class ILayer {
      * @brief Copy the weights and biases to the device
      */
     virtual void toCuda() = 0;
-
-    int inputSize;
-    int outputSize;
-
-    float* d_output;
-
-    float* d_weights;
-    float* d_biases;
-
-    std::vector<float> weights;
-    std::vector<float> biases;
-
 };
 
 }  // namespace CUDANet::Layers

include/layers/input.cuh

@@ -9,7 +9,7 @@ namespace CUDANet::Layers {
  * @brief Input layer, just copies the input to the device
  *
  */
-class Input : public ILayer {
+class Input {
   public:
     /**
      * @brief Create a new Input layer
@@ -32,15 +32,7 @@ class Input : public ILayer {
      */
     float* forward(const float* input);
 
-    void setWeights(const float* weights);
-    void setBiases(const float* biases);
-
   private:
-    void initializeWeights();
-    void initializeBiases();
-
-    void toCuda();
-
     int    inputSize;
     float* d_output;
 };