Migrate concat layer

include/backend.hpp

@@ -84,6 +84,12 @@ class Backend {
         CUDANet::Tensor& running_var,
         CUDANet::Tensor& epsilon
     ) = 0;
+
+    virtual CUDANet::Tensor& concat(
+        CUDANet::Tensor& input_a,
+        CUDANet::Tensor& input_b,
+        CUDANet::Tensor& output
+    ) = 0;
 };
 
 }  // namespace CUDANet

include/backend/cuda.cuh

@@ -80,6 +80,12 @@ class CUDA : public Backend {
         CUDANet::Tensor& running_var,
         CUDANet::Tensor& epsilon
     ) override;
+
+    CUDANet::Tensor& concat(
+        CUDANet::Tensor& input_a,
+        CUDANet::Tensor& input_b,
+        CUDANet::Tensor& output
+    ) override;
 };
 
 }  // namespace CUDANet::Backend

include/layers/concat.hpp

@@ -1,5 +1,4 @@
-#ifndef CUDANET_CONCAT_LAYER_H
+#pragma once
-#define CUDANET_CONCAT_LAYER_H
 
 #include "layer.hpp"
 
@@ -11,47 +10,24 @@ namespace CUDANet::Layers {
  */
 class Concat {
   public:
-    /**
-     * @brief Create a new Concat layer
-     *
-     * @param inputASize Size of the first input
-     * @param inputBSize Size of the second input
-     */
-    Concat(const int inputASize, const int inputBSize);
 
-    /**
+    Concat(const CUDANet::Shape a_shape, const CUDANet::Shape b_shape, CUDANet::Backend *backend);
-     * @brief Destroy the Concat layer
+
-     *
-     */
     ~Concat();
 
-    /**
+    CUDANet::Tensor& forward(CUDANet::Tensor& input_a, CUDANet::Tensor& input_b);
-     * @brief Concatenates the two inputs
-     *
-     * @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);
 
-    int getOutputSize();
+    CUDANet::Shape output_shape();
 
   private:
-    int inputASize;
+    CUDANet::Shape a_shape;
-    int inputBSize;
+    CUDANet::Shape b_shape;
 
-    float* forwardCPU(const float* input_A, const float* input_B);
+    CUDANet::Shape out_shape;
+    CUDANet::Tensor output;
 
-#ifdef USE_CUDA
+    CUDANet::Backend *backend;
-    float* d_output;
-    float* forwardCUDA(const float* d_input_A, const float* d_input_B);
-
-    void initCUDA();
-    void delCUDA();
-#endif
 };
 
 }  // namespace CUDANet::Layers
 
-#endif  // CUDANET_CONCAT_LAYER_H

include/layers/conv2d.hpp

@@ -1,8 +1,5 @@
 #pragma once
 
-#include <vector>
-
-#include "activation.hpp"
 #include "layer.hpp"
 
 namespace CUDANet::Layers {

include/layers/dense.hpp

@@ -1,7 +1,5 @@
 #pragma once
 
-#include <vector>
-
 #include "backend.hpp"
 #include "layer.hpp"
 

include/shape.hpp

@@ -21,6 +21,30 @@ class InvalidShapeException : public std::runtime_error {
                   actual
               )
           ) {}
+
+    InvalidShapeException(
+        const std::string& message,
+        const Shape&       shape_a,
+        const Shape&       shape_b
+    )
+        : std::runtime_error(
+              std::format(
+                  "{}. Shape A: [{}], Shape B: [{}]",
+                  message,
+                  format_shape(shape_a),
+                  format_shape(shape_b)
+              )
+          ) {}
+
+  private:
+    static std::string format_shape(const Shape& shape) {
+        std::string result;
+        for (size_t i = 0; i < shape.size(); ++i) {
+            if (i > 0) result += ", ";
+            result += std::to_string(shape[i]);
+        }
+        return result;
+    }
 };
 
 }  // namespace CUDANet

src/backends/cuda/layer_ops.cu

@@ -211,4 +211,24 @@ CUDANet::Tensor& CUDA::batch_norm(
         );
         CUDA_CHECK(cudaGetLastError());
     }
+}
+
+CUDANet::Tensor& CUDA::concat(
+    CUDANet::Tensor& input_a,
+    CUDANet::Tensor& input_b,
+    CUDANet::Tensor& output
+) {
+    CUDA_CHECK(cudaMemcpy(
+        output.data<float>(), input_a.data<float>(), input_a.size(),
+        cudaMemcpyDeviceToDevice
+    ));
+
+    CUDA_CHECK(cudaMemcpy(
+        output.data<float>() + input_a.numel(), input_b.data<float>(), input_b.size(),
+        cudaMemcpyDeviceToDevice
+    ));
+
+    CUDA_CHECK(cudaDeviceSynchronize());
+
+    return output;
 }

src/backends/cuda/layers/concat.cu

@@ -1,31 +0,0 @@
-#include "concat.hpp"
-#include "cuda_helper.cuh"
-
-using namespace CUDANet::Layers;
-
-void Concat::initCUDA() {
-    d_output = nullptr;
-    CUDA_CHECK(
-        cudaMalloc((void**)&d_output, sizeof(float) * (inputASize + inputBSize))
-    );
-}
-
-void Concat::delCUDA() {
-    cudaFree(d_output);
-}
-
-float* Concat::forwardCUDA(const float* d_input_A, const float* d_input_B) {
-    CUDA_CHECK(cudaMemcpy(
-        d_output, d_input_A, sizeof(float) * inputASize,
-        cudaMemcpyDeviceToDevice
-    ));
-
-    CUDA_CHECK(cudaMemcpy(
-        d_output + inputASize, d_input_B, sizeof(float) * inputBSize,
-        cudaMemcpyDeviceToDevice
-    ));
-
-    CUDA_CHECK(cudaDeviceSynchronize());
-
-    return d_output;
-}

src/layers/concat.cpp

@@ -1,34 +1,32 @@
-#include <stdexcept>
-
 #include "concat.hpp"
 
 using namespace CUDANet::Layers;
 
-Concat::Concat(const int inputASize, const int inputBSize)
+Concat::Concat(const CUDANet::Shape a_shape, const CUDANet::Shape b_shape, CUDANet::Backend *backend)
-    : inputASize(inputASize), inputBSize(inputBSize) {
+    : a_shape(a_shape), b_shape(b_shape), backend(backend) {
-#ifdef USE_CUDA
+    if (a_shape[0] != b_shape[0] || a_shape[1] != b_shape[1]) {
-    initCUDA();
+        throw InvalidShapeException(
-#endif
+            "Concat requires matching batch and height dimensions", a_shape,
+            b_shape
+        );
+    }
+
+    out_shape = {a_shape[0], a_shape[1], a_shape[2] + b_shape[2]};
+    output = CUDANet::Tensor(out_shape, CUDANet::DType::FLOAT32, backend);
 }
 
-Concat::~Concat() {
+Concat::~Concat() {}
-#ifdef USE_CUDA
+
-    delCUDA();
+CUDANet::Tensor& Concat::forward(CUDANet::Tensor& input_a, CUDANet::Tensor& input_b) {
-#endif
+    output.zero();
+    backend->concat(
+        input_a,
+        input_b,
+        output
+    );
+    return output;
 }
 
-float* Concat::forwardCPU(const float* input_A, const float* input_B) {
+CUDANet::Shape Concat::output_shape() {
-    throw std::logic_error("Not implemented");
+    return out_shape;
-}
+}
-
-float* Concat::forward(const float* input_A, const float* input_B) {
-#ifdef USE_CUDA
-    return forwardCUDA(input_A, input_B);
-#else
-    return forwardCPU(input_A, input_B);
-#endif
-}
-
-int Concat::getOutputSize() {
-    return inputASize + inputBSize;
-};