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mikolasanmikolasan
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Data processor defines first layer of sensors
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7 files changed

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-143
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7 files changed

+200
-143
lines changed

‎graphics/neurons/data_processor.h‎

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#ifndef DATA_PROCESSOR_H
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#define DATA_PROCESSOR_H
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#include <bx/math.h>
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class DataProcessor {
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virtual bx::Vec3 get_area_size() const = 0;
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};
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#endif

‎graphics/neurons/data_processor.hpp‎

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This file was deleted.

‎graphics/neurons/mnist_data_processor.cpp‎

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#include "mnist_data_processor.h"
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#include "render/neuron_render.hpp"
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const size_t input_size = 784;
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const uint32_t width = 28, height = 28;
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struct MnistImage {
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uint8_t label;
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uint8_t pixels[input_size];
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};
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std::vector<MnistImage> load_mnist_bin(const std::string& path) {
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std::ifstream in(path, std::ios::binary);
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std::vector<MnistImage> images;
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MnistImage img;
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while (in.read(reinterpret_cast<char*>(&img), sizeof(MnistImage))) {
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images.push_back(img);
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}
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return images;
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}
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bgfx::TextureHandle create_mnist_texture(const uint8_t* pixels) {
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std::vector<uint8_t> rgba(width * height * 4);
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for (int i = 0; i < input_size; ++i) {
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uint8_t v = pixels[i];
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rgba[i * 4 + 0] = v;
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rgba[i * 4 + 1] = v;
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rgba[i * 4 + 2] = v;
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rgba[i * 4 + 3] = 255;
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}
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const bgfx::Memory* mem = bgfx::copy(rgba.data(), rgba.size());
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return bgfx::createTexture2D(width, height, false, 1, bgfx::TextureFormat::RGBA8, 0, mem);
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}
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void MnistDataProcessor::init() {
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images = load_mnist_bin("mnist.bin");
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current_image_id = 0;
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cached_texture = BGFX_INVALID_HANDLE;
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}
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size_t MnistDataProcessor::get_input_size() const {
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return input_size;
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}
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bx::Vec3 MnistDataProcessor::get_area_size() const {
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return { width, height, 1.0f };
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}
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size_t MnistDataProcessor::get_max_id() const {
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return images.size() - 1;
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}
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size_t MnistDataProcessor::get_current_id() const {
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return current_image_id;
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}
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uint8_t MnistDataProcessor::get_current_label() const {
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return images[current_image_id].label;
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}
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void MnistDataProcessor::set_current_id(size_t id) {
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if (id != current_image_id) {
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if (bgfx::isValid(cached_texture)) {
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bgfx::destroy(cached_texture);
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}
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cached_texture = create_mnist_texture(images[id].pixels);
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}
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current_image_id = id;
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}
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bgfx::TextureHandle MnistDataProcessor::create_currnet_texture() {
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if (!bgfx::isValid(cached_texture)) {
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cached_texture = create_mnist_texture(images[current_image_id].pixels);
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}
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return cached_texture;
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}
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std::vector<uint8_t> MnistDataProcessor::convert_current_to_inputs() {
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std::vector<uint8_t> inputs;
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// TODO: wtf is the type for `pixels` to pass to `begin` and `end` ???
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inputs.assign(
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std::begin(images[current_image_id].pixels),
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std::end(images[current_image_id].pixels));
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return inputs;
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}
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std::vector<Neuron> MnistDataProcessor::prepare_neurons() const {
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std::vector<Neuron> neurons(input_size);
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bx::Vec3 area_size = get_area_size();
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for (size_t i = 0; i < input_size; ++i) {
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auto ctx = std::make_shared<NeuronVisualContext>(neurons[i]);
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ctx->position = {
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float(i % int32_t(area_size.x)),
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i / area_size.x,
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0.0f };
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neurons[i].render = std::make_shared<NeuronRenderStrategy>(ctx);
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}
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}

‎graphics/neurons/mnist_data_processor.h‎

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#ifndef MNIST_DATA_PROCESSOR_H
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#define MNIST_DATA_PROCESSOR_H
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#include <iostream>
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#include <fstream>
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#include <string>
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#include <vector>
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#include <bx/math.h>
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#include <bx/uint32_t.h>
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#include <bgfx/bgfx.h>
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#include "data_processor.h"
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#include "neuron.hpp"
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struct MnistImage;
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class MnistDataProcessor : public DataProcessor {
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private:
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std::vector<MnistImage> images;
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size_t current_image_id;
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bgfx::TextureHandle cached_texture;
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public:
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void init();
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size_t get_input_size() const;
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bx::Vec3 get_area_size() const override;
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size_t get_max_id() const;
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size_t get_current_id() const;
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uint8_t get_current_label() const;
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void set_current_id(size_t id);
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bgfx::TextureHandle create_currnet_texture();
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std::vector<uint8_t> convert_current_to_inputs();
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std::vector<Neuron> prepare_neurons() const;
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};
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#endif

‎graphics/neurons/network.hpp‎

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struct Network {
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std::vector<Neuron> neurons;
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using NeuronLayer = std::vector<Neuron>;
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// std::vector<Neuron> neurons;
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std::vector<NeuronLayer> layers;
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using Location = uint64_t;
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std::unordered_map<Location, Synapse> synapses;
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// std::vector<std::vector<Synapse>> synapses;
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explicit Network() = default;
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Network(int N) {
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setSize(N);
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Network() {
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// setSize(N);
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// Init weights, if desired
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}
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void setSize(int N) {
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neurons.resize(N);
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// synapses.resize(N, std::vector<Synapse>(N));
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void addLayer(const NeuronLayer&& layer) {
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layers.push_back(layer);
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}
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// void setSize(int N) {
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// neurons.resize(N);
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// // synapses.resize(N, std::vector<Synapse>(N));
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// }
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std::vector<float> get_current_voltage_state() const {
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std::vector<float> state(neurons.size(), 0.0);
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for (size_t i = 0; i < neurons.size(); ++i) {

‎graphics/neurons/neurons_gui.cpp‎

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#include "render/neuron_render.hpp"
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#include "render/network_render.hpp"
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#include "simulation_clock.hpp"
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#include "data_processor.hpp"
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#include "mnist_data_processor.h"
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#include "camera.cpp"
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#include "mouse.cpp"
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namespace
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{
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36-
const int32_t width = 28, height = 28;
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class SpikingWorld : public entry::AppI
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{
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public:
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{
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Args args(_argc, _argv);
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data.init();
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// TODO: data dimensions should come from MnistData
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data.init();
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m_width = _width;
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m_height = _height;
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auto ctx = std::make_shared<NetworkVisualContext>(net);
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net.render = std::make_shared<NetworkRenderStrategy>(ctx);
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for (size_t i = 0; i < net.neurons.size(); ++i) {
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auto ctx2 = std::make_shared<NeuronVisualContext>(net.neurons[i]);
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ctx2->position = {
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float(i % width),
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float(i / width),
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0.0f };
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net.neurons[i].render = std::make_shared<NeuronRenderStrategy>(ctx2);
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}
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net.addLayer(data.prepare_neurons());
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// bx::Vec3 area_size = data.get_area_size();
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// for (size_t i = 0; i < net.neurons.size(); ++i) {
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// auto ctx2 = std::make_shared<NeuronVisualContext>(net.neurons[i]);
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// ctx2->position = {
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// float(i % int32_t(area_size.x)),
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// i / area_size.x,
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// 0.0f };
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// net.neurons[i].render = std::make_shared<NeuronRenderStrategy>(ctx2);
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// }
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sim_clock.set_dt(10);
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sim_clock.pause();

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