generated from aselimov/cpp_project_template
70 lines
1.9 KiB
C++
70 lines
1.9 KiB
C++
#include "../../src/activation_function.hpp"
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#include <cmath>
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#include <gtest/gtest.h>
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#include <vector>
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TEST(ActivationFunctionTest, SigmoidTest) {
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std::vector<float> input = {0.0, 10.0, -10.0, 1.0, -1.0};
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std::vector<float> expected = {0.5, 0.9999546, 0.0000454,
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static_cast<float>(1.0 / (1.0 + exp(-1.0))),
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static_cast<float>(1.0 / (1.0 + exp(1.0)))};
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std::vector<float> test = input;
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Sigmoid::apply(test);
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ASSERT_EQ(test.size(), expected.size());
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for (size_t i = 0; i < test.size(); i++) {
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EXPECT_NEAR(test[i], expected[i], 1e-6);
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}
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// Test initialization standard deviation
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EXPECT_NEAR(Sigmoid::init_stddev(100), sqrt(1.0 / 100), 1e-6);
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}
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TEST(ActivationFunctionTest, ReLUTest) {
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std::vector<float> input = {0.0, 5.0, -5.0, 0.0001, -0.0001};
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std::vector<float> expected = {0.0, 5.0, 0.0, 0.0001, 0.0};
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std::vector<float> test = input;
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ReLU::apply(test);
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ASSERT_EQ(test.size(), expected.size());
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for (size_t i = 0; i < test.size(); i++) {
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EXPECT_FLOAT_EQ(test[i], expected[i]);
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}
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// Test initialization standard deviation
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EXPECT_NEAR(ReLU::init_stddev(100), sqrt(2.0 / 100), 1e-6);
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}
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TEST(ActivationFunctionTest, SoftMaxTest) {
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SoftMax softmax;
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std::vector<float> input = {1.0, 2.0, 3.0, 4.0, 1.0};
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std::vector<float> test = input;
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SoftMax::apply(test);
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// Test properties of softmax
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ASSERT_EQ(test.size(), input.size());
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// Sum should be approximately 1
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float sum = 0.0;
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for (float val : test) {
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sum += val;
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// All values should be between 0 and 1
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EXPECT_GE(val, 0.0);
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EXPECT_LE(val, 1.0);
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}
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EXPECT_NEAR(sum, 1.0, 1e-6);
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// Higher input should lead to higher output
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for (size_t i = 0; i < test.size() - 1; i++) {
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if (input[i] < input[i + 1]) {
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EXPECT_LT(test[i], test[i + 1]);
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}
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}
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// Test initialization standard deviation
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EXPECT_NEAR(softmax.init_stddev(100), sqrt(1.0 / 100), 1e-6);
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}
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