From dbc206d18c88f352ee0331f73d8550224bf4c800 Mon Sep 17 00:00:00 2001
From: LordMathis <matus@namesny.com>
Date: Mon, 19 Feb 2024 22:27:21 +0100
Subject: [PATCH] Fix unit weight matrix test

---
 test/layers/test_dense.cpp | 90 +++++++++++++++++++++++++++-----------
 1 file changed, 65 insertions(+), 25 deletions(-)

diff --git a/test/layers/test_dense.cpp b/test/layers/test_dense.cpp
index e427a60..966acaf 100644
--- a/test/layers/test_dense.cpp
+++ b/test/layers/test_dense.cpp
@@ -6,20 +6,45 @@
 
 class DenseLayerTest : public CublasTestFixture {
 protected:
-};
+    Layers::Dense commonTestSetup(int inputSize, int outputSize, std::vector<float>& input, std::vector<std::vector<float>>& weights, std::vector<float>& biases, float*& d_input, float*& d_output) {
+        // Create Dense layer
+        Layers::Dense denseLayer(inputSize, outputSize, cublasHandle);
 
+        // Set weights and biases
+        denseLayer.setWeights(weights);
+        denseLayer.setBiases(biases);
 
-TEST_F(DenseLayerTest, Forward) {
+        // Allocate device memory
+        cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * input.size());
+        EXPECT_EQ(cudaStatus, cudaSuccess);
+
+        cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * outputSize);
+        EXPECT_EQ(cudaStatus, cudaSuccess);
+
+        // Copy input to device
+        cublasStatus = cublasSetVector(input.size(), sizeof(float), input.data(), 1, d_input, 1);
+        EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
+
+        return denseLayer;
+    }
+
+    void commonTestTeardown(float* d_input, float* d_output) {
+        // Free device memory
+        cudaFree(d_input);
+        cudaFree(d_output);
+    }
 
     cudaError_t cudaStatus;
     cublasStatus_t cublasStatus;
+};
+
+TEST_F(DenseLayerTest, ForwardUnitWeightMatrix) {
 
     int inputSize = 3;
     int outputSize = 3;
 
-    Layers::Dense denseLayer(inputSize, outputSize, cublasHandle);
+    std::vector<float> input = {1.0f, 2.0f, 3.0f};
 
-    // Initialize a weight matrix
     std::vector<std::vector<float>> weights(inputSize, std::vector<float>(outputSize, 0.0f));
     for (int i = 0; i < inputSize; ++i) {
         for (int j = 0; j < outputSize; ++j) {
@@ -28,32 +53,15 @@ TEST_F(DenseLayerTest, Forward) {
             }
         }
     }
-
-    // Set the weights
-    denseLayer.setWeights(weights);
-
-    // Initialize and set a bias vector
     std::vector<float> biases(outputSize, 1.0f);
-    denseLayer.setBiases(biases);
-
-    std::vector<float> input = {1.0f, 2.0f, 3.0f};
-    std::vector<float> output(outputSize);
 
     float* d_input;
     float* d_output;
 
-    cudaStatus =cudaMalloc((void**)&d_input, sizeof(float) * input.size());
-    EXPECT_EQ(cudaStatus, cudaSuccess);
-
-    cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * outputSize);
-    EXPECT_EQ(cudaStatus, cudaSuccess);
-
-    cublasStatus =cublasSetVector(input.size(), sizeof(float), input.data(), 1, d_input, 1);
-    EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
-
-    // Perform forward pass
+    Layers::Dense denseLayer = commonTestSetup(inputSize, outputSize, input, weights, biases, d_input, d_output);
     denseLayer.forward(d_input, d_output);
 
+    std::vector<float> output(outputSize);
     cublasStatus = cublasGetVector(outputSize, sizeof(float), d_output, 1, output.data(), 1);
     EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
 
@@ -62,6 +70,38 @@ TEST_F(DenseLayerTest, Forward) {
     EXPECT_FLOAT_EQ(output[1], 3.0f);
     EXPECT_FLOAT_EQ(output[2], 4.0f);
 
-    cudaFree(d_input);
-    cudaFree(d_output);
+    commonTestTeardown(d_input, d_output);
 }
+
+TEST_F(DenseLayerTest, ForwardRandomWeightMatrix) {
+    int inputSize = 5;
+    int outputSize = 4;
+
+    std::vector<float> input = {1.0f, 2.0f, 3.0f, 4.0f, 5.0f};
+
+    std::vector<std::vector<float>> weights = {
+        {0.5f, 1.0f, 0.2f, 0.8f},
+        {1.2f, 0.3f, 1.5f, 0.4f},
+        {0.7f, 1.8f, 0.9f, 0.1f},
+        {0.4f, 2.0f, 0.6f, 1.1f},
+        {1.3f, 0.5f, 0.0f, 1.7f}
+    };
+    std::vector<float> biases = {0.2f, 0.5f, 0.7f, 1.1f};
+
+    float* d_input;
+    float* d_output;    
+
+    Layers::Dense denseLayer = commonTestSetup(inputSize, outputSize, input, weights, biases, d_input, d_output);
+    denseLayer.forward(d_input, d_output);
+
+    std::vector<float> output(outputSize);
+    cublasStatus = cublasGetVector(outputSize, sizeof(float), d_output, 1, output.data(), 1);
+    EXPECT_EQ(cublasStatus, CUBLAS_STATUS_SUCCESS);
+
+    std::vector<float> expectedOutput = {3.4f, 4.4f, 5.6f, 7.4f};
+    for (int i = 0; i < outputSize; ++i) {
+        EXPECT_NEAR(output[i], expectedOutput[i], 1e-4); // Allow small tolerance for floating-point comparison
+    }
+
+    commonTestTeardown(d_input, d_output);
+}
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