Add more softmax tests

src/kernels/activation_functions.cu

@@ -1,5 +1,3 @@
-#include <cmath>
-
 #include "activation_functions.cuh"
 #include "cuda_helper.cuh"
 
@@ -40,7 +38,7 @@ __global__ void Kernels::softmax_exp(
     int tid    = blockDim.x * blockIdx.x + threadIdx.x;
 
     for (int i = tid; i < len; i += stride) {
-        dst[i] = std::exp(src[i]);
+        dst[i] = expf(src[i]);
     }
 }
 

src/layers/activation.cu

@@ -41,7 +41,7 @@ void Activation::activate(float* __restrict__ d_input) {
                 d_input, d_input, length
             );
 
-            Kernels::softmax_sum<<<gridSize / 2, BLOCK_SIZE>>>(
+            Kernels::softmax_sum<<<gridSize, BLOCK_SIZE>>>(
                 d_input, d_softmax_sum, length
             );
 

test/kernels/test_activation_functions.cu

@@ -5,8 +5,7 @@
 
 #include "activation_functions.cuh"
 
-TEST(ActivationsTest, SigmoidSanityCheck) {
+TEST(ActivationFunctionsTest, SigmoidSanityCheck) {
-
     cudaError_t cudaStatus;
 
     float input[3] = {-100.0f, 0.0f, 100.0f};
@@ -22,7 +21,8 @@ TEST(ActivationsTest, SigmoidSanityCheck) {
     cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * 3);
     EXPECT_EQ(cudaStatus, cudaSuccess);
 
-    cudaStatus = cudaMemcpy(d_input, input, sizeof(float) * 3, cudaMemcpyHostToDevice);
+    cudaStatus =
+        cudaMemcpy(d_input, input, sizeof(float) * 3, cudaMemcpyHostToDevice);
     EXPECT_EQ(cudaStatus, cudaSuccess);
 
     CUDANet::Kernels::sigmoid<<<1, 3>>>(d_input, d_output, 3);
@@ -31,7 +31,9 @@ TEST(ActivationsTest, SigmoidSanityCheck) {
 
     std::vector<float> output(3);
 
-    cudaStatus = cudaMemcpy(output.data(), d_output, sizeof(float) * 3, cudaMemcpyDeviceToHost);
+    cudaStatus = cudaMemcpy(
+        output.data(), d_output, sizeof(float) * 3, cudaMemcpyDeviceToHost
+    );
     EXPECT_EQ(cudaStatus, cudaSuccess);
 
     for (int i = 0; i < 3; i++) {
@@ -41,3 +43,58 @@ TEST(ActivationsTest, SigmoidSanityCheck) {
     cudaFree(d_input);
     cudaFree(d_output);
 }
+
+TEST(ActivationFunctionsTest, SoftmaxExpTest) {
+    cudaError_t cudaStatus;
+
+    float input[6] = {22.496f,  36.9006f, 30.9904f,
+                      28.4213f, 26.4541f, 31.7887f};
+
+    std::vector<float> expected = {5886928896.0f,     1.06102872080384e+16f,
+                                   28771323215872.0f, 2204012904448.0f,
+                                   308226162688.0f,   63922983927808.0f};
+
+    float* d_input;
+    float* d_output;
+
+    cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * 6);
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+
+    cudaStatus = cudaMalloc((void**)&d_output, sizeof(float) * 6);
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+
+    cudaStatus =
+        cudaMemcpy(d_input, input, sizeof(float) * 6, cudaMemcpyHostToDevice);
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+
+    CUDANet::Kernels::softmax_exp<<<1, 6>>>(d_input, d_output, 6);
+    cudaStatus = cudaDeviceSynchronize();
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+
+    std::vector<float> output(6);
+
+    cudaStatus = cudaMemcpy(
+        output.data(), d_output, sizeof(float) * 6, cudaMemcpyDeviceToHost
+    );
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+
+    for (int i = 0; i < 6; i++) {
+        EXPECT_NEAR(expected[i], output[i], 1e7);
+    }
+
+    cudaFree(d_input);
+    cudaFree(d_output);
+}
+
+TEST(ActivationFunctionsTest, SoftmaxSumTest) {
+    cudaError_t cudaStatus;
+
+    std::vector<float> input = {5886928896.0f,     1.06102872080384e+16f,
+                                28771323215872.0f, 2204012904448.0f,
+                                308226162688.0f,   63922983927808.0f};
+
+    float* d_input;
+
+    cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * 6);
+    EXPECT_EQ(cudaStatus, cudaSuccess);
+}

test/layers/test_activation.cu

@@ -3,7 +3,7 @@
 #include <cuda_runtime.h>
 #include <vector>
 
-TEST(ActivationTest, SoftmaxTest) {
+TEST(ActivationTest, SoftmaxTest1) {
     CUDANet::Layers::Activation activation(
         CUDANet::Layers::ActivationType::SOFTMAX, 5
     );
@@ -32,3 +32,33 @@ TEST(ActivationTest, SoftmaxTest) {
 
     cudaFree(d_input);
 }
+
+TEST(ActivationTest, SoftmaxTest2) {
+    CUDANet::Layers::Activation activation(
+        CUDANet::Layers::ActivationType::SOFTMAX, 6
+    );
+
+    std::vector<float> input = {22.496f, 36.9006f, 30.9904f, 28.4213f, 26.4541f, 31.7887f};
+
+    float* d_input;
+    cudaMalloc((void**)&d_input, sizeof(float) * 6);
+    cudaMemcpy(d_input, input.data(), sizeof(float) * 6, cudaMemcpyHostToDevice);
+
+    activation.activate(d_input);
+    std::vector<float> output(6);
+    cudaMemcpy(
+        output.data(), d_input, sizeof(float) * 6, cudaMemcpyDeviceToHost
+    );
+    
+    float sum = 0.0f;
+
+    std::vector<float> expected = {0.0f, 0.99111f, 0.00269f, 0.00021f, 3e-05f, 0.00597f};
+    for (int i = 0; i < 5; ++i) {
+        sum += output[i];
+        EXPECT_NEAR(output[i], expected[i], 1e-5f);
+    }
+
+    EXPECT_NEAR(sum, 1.0f, 1e-5f);
+
+    cudaFree(d_input);
+}