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BiPy/Xenith/core.hpp
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2026-05-03 21:02:34 +07:00

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#ifndef CORE_H
#define CORE_H
#include "typedef.hpp"
#include <vector>
#include <string>
#include <vulkan/vulkan.hpp>
#include <functional>
struct TrainStatus {
int currentEpoch;
int totalEpochs;
int currentToken;
int totalTokens;
double currentLoss;
double epochLoss;
double lastEpochLoss;
double speed;
double eta;
float percentage;
long totalParams;
};
class Tokenizer;
class Embedder;
class NeuralNetwork {
private:
int numLayers;
std::vector<int> sizes;
std::vector<float> h_weights, h_biases, h_outputs, h_errors;
std::vector<uint32_t> wOff, bOff, oOff;
bool useVulkan;
vk::Instance instance;
vk::PhysicalDevice physDev;
vk::Device device;
vk::Queue queue;
vk::CommandPool cmdPool;
uint32_t computeQueueFamilyIndex;
vk::Buffer gpuW, gpuB, gpuO, gpuE, gpuT;
vk::DeviceMemory memW, memB, memO, memE, memT;
void *pW = nullptr, *pB = nullptr, *pO = nullptr, *pE = nullptr, *pT = nullptr;
vk::DescriptorPool descriptorPool;
vk::DescriptorSet descriptorSet;
vk::DescriptorSetLayout dsLayout;
vk::PipelineLayout pipeLayout;
vk::Pipeline pipeline;
vk::ShaderModule shaderModule;
struct TrainParams {
uint32_t mode;
uint32_t prevSize;
uint32_t nextSize;
uint32_t wOff;
uint32_t bOff;
uint32_t oOff;
uint32_t nextOOff;
float lr;
};
void initVulkan();
void initVulkanResources();
uint32_t findMemoryType(uint32_t typeFilter, vk::MemoryPropertyFlags properties);
std::vector<char> readFile(const std::string& filename);
double runTrainCPU(const std::vector<double>& input, const std::vector<double>& target, double lr);
public:
int cpu_count = 4;
NeuralNetwork(LayerStructure_t layers[], int count, bool useVulkan = false);
~NeuralNetwork();
void syncToCPU();
void syncToGPU();
std::vector<double> feedForward(const std::vector<double>& input);
double train(const std::vector<double>& input, const std::vector<double>& target, double lr);
void trainOnSequence(
Tokenizer& tok,
Embedder& emb,
const std::string& dataset,
int epochs,
double lr,
std::function<std::vector<double>(const std::vector<int>&, Embedder&)> buildInput,
std::function<void(const TrainStatus&)> onProgress = nullptr
);
long long getTotalParameters() {
long long total = 0;
for (int i = 0; i < numLayers - 1; i++) {
total += (long long)sizes[i] * sizes[i+1];
total += (long long)sizes[i+1];
}
return total;
}
};
#endif