#include #include #include #include "conv2d.cuh" TEST(Conv2dTest, SimpleExample) { int inputSize = 4; int inputChannels = 1; int kernelSize = 2; int stride = 1; std::string padding = "VALID"; int numFilters = 1; Activation activation = LINEAR; Layers::Conv2d conv2d( inputSize, inputChannels, kernelSize, stride, padding, numFilters, activation ); int outputSize = (inputSize - kernelSize) / stride + 1; EXPECT_EQ(outputSize, conv2d.outputSize); std::vector input = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f, 13.0f, 14.0f, 15.0f, 16.0f }; std::vector kernels = { 1.0f, 2.0f, 3.0f, 4.0f, }; conv2d.setKernels(kernels); std::vector output(outputSize * outputSize * numFilters); conv2d.host_conv(input.data(), output.data()); std::vector expected = { 44.0f, 54.0f, 64.0f, 84.0f, 94.0f, 104.0f, 124.0f, 134.0f, 144.0f }; for (int i = 0; i < output.size(); ++i) { EXPECT_FLOAT_EQ(expected[i], output[i]); } }