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https://github.com/lordmathis/CUDANet.git
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84 lines
2.4 KiB
Plaintext
84 lines
2.4 KiB
Plaintext
#include "activation.hpp"
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#include <gtest/gtest.h>
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#include <cuda_runtime.h>
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#include <vector>
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TEST(ActivationTest, SoftmaxTest1) {
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const int inputSize = 5;
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cudaError_t cudaStatus;
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CUDANet::Layers::Activation activation(
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CUDANet::Layers::ActivationType::SOFTMAX, inputSize
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);
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std::vector<float> input = {0.573f, 0.619f, 0.732f, 0.055f, 0.243f};
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float* d_input;
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cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * inputSize);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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cudaStatus = cudaMemcpy(d_input, input.data(), sizeof(float) * inputSize, cudaMemcpyHostToDevice);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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activation.activate(d_input);
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std::vector<float> output(5);
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cudaStatus = cudaMemcpy(
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output.data(), d_input, sizeof(float) * inputSize, cudaMemcpyDeviceToHost
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);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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float sum = 0.0f;
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std::vector<float> expected = {0.22055f, 0.23094f, 0.25856f, 0.13139f, 0.15856f};
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for (int i = 0; i < inputSize; ++i) {
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sum += output[i];
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EXPECT_NEAR(output[i], expected[i], 1e-5f);
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}
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EXPECT_NEAR(sum, 1.0f, 1e-5f);
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cudaStatus = cudaFree(d_input);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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}
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TEST(ActivationTest, SoftmaxTest2) {
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const int inputSize = 6;
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cudaError_t cudaStatus;
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CUDANet::Layers::Activation activation(
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CUDANet::Layers::ActivationType::SOFTMAX, inputSize
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);
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cudaStatus = cudaGetLastError();
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EXPECT_EQ(cudaStatus, cudaSuccess);
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std::vector<float> input = {22.496f, 36.9006f, 30.9904f, 28.4213f, 26.4541f, 31.7887f};
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float* d_input;
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cudaStatus = cudaMalloc((void**)&d_input, sizeof(float) * inputSize);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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cudaStatus = cudaMemcpy(d_input, input.data(), sizeof(float) * inputSize, cudaMemcpyHostToDevice);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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activation.activate(d_input);
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std::vector<float> output(inputSize);
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cudaStatus = cudaMemcpy(
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output.data(), d_input, sizeof(float) * inputSize, cudaMemcpyDeviceToHost
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);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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float sum = 0.0f;
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std::vector<float> expected = {0.0f, 0.99111f, 0.00269f, 0.00021f, 3e-05f, 0.00597f};
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for (int i = 0; i < inputSize; ++i) {
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sum += output[i];
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EXPECT_NEAR(output[i], expected[i], 1e-5f);
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}
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EXPECT_NEAR(sum, 1.0f, 1e-5f);
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// Cleanup
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cudaStatus = cudaFree(d_input);
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EXPECT_EQ(cudaStatus, cudaSuccess);
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} |