Implement concat layer

test/CMakeLists.txt

@@ -3,10 +3,11 @@ include_directories(${GTEST_INCLUDE_DIRS})
 
 add_executable(test_main 
     EXCLUDE_FROM_ALL
-    layers/test_dense.cu
-    layers/test_conv2d.cu
-    layers/test_input.cu
     layers/test_activation.cu
+    layers/test_concat.cu
+    layers/test_conv2d.cu
+    layers/test_dense.cu
+    layers/test_input.cu
     kernels/test_activation_functions.cu
     kernels/test_padding.cu
     kernels/test_matmul.cu

test/layers/test_concat.cu

@@ -0,0 +1,37 @@
+#include "concat.cuh"
+#include <gtest/gtest.h>
+#include <cuda_runtime.h>
+#include <vector>
+
+TEST(ConcatLayerTest, Init) {
+    std::vector<float> inputA = {0.573f, 0.619f, 0.732f, 0.055f, 0.243f};
+    std::vector<float> inputB = {0.123f, 0.321f, 0.456f, 0.789f, 0.654f, 0.123f};
+
+    CUDANet::Layers::Concat concat(5, 6);   
+
+    float* d_inputA;
+    float* d_inputB;
+    cudaMalloc((void**)&d_inputA, sizeof(float) * 5);
+    cudaMalloc((void**)&d_inputB, sizeof(float) * 6);
+    cudaMemcpy(
+        d_inputA, inputA.data(), sizeof(float) * 5, cudaMemcpyHostToDevice
+    );
+    cudaMemcpy(
+        d_inputB, inputB.data(), sizeof(float) * 6, cudaMemcpyHostToDevice
+    );
+
+    float* d_output = concat.forward(d_inputA, d_inputB);
+
+    std::vector<float> output(11);
+    cudaMemcpy(
+        output.data(), d_output, sizeof(float) * 11, cudaMemcpyDeviceToHost
+    );
+
+    for (int i = 0; i < 5; ++i) {
+        EXPECT_EQ(output[i], inputA[i]);
+    }
+    for (int i = 0; i < 6; ++i) {
+        EXPECT_EQ(output[i + 5], inputB[i]);
+    }
+    cudaFree(d_output);
+}