static void Main(string[] args) { KernelManager.Initialize(); KernelManager.GPUMode = true; //var superResolution = new GAN();//new ReversibleAutoencoder(); //new ConvSuperResolution(); new ConvSuperResolution().Train(); //new GradientChecking().Check(); }
static void Main(string[] args) { KernelManager.Initialize(); var tags = new string[] { //"emilia_(re:zero)", //"katou_megumi", //"tokisaki_kurumi", //"sawamura_spencer_eriri", //"kasumigaoka_utaha", //"zero_two_(darling_in_the_franxx)", //"nishikino_maki", //"souryuu_asuka_langley", //"shiba_miyuki", //"akemi_homura", //"kizuna_ai", //"euryale", "osakabe-hime_(fate/grand_order)", "momo_velia_deviluke", "semiramis_(fate)", "altera_(fate)", "takao_(aoki_hagane_no_arpeggio)", "medb_(fate)_(all)", "meltlilith", "yuzuriha_inori", //"redjuice" }; var globalTags = new string[] { "1girl", "solo", "-*boy*", "-large_breasts", "-video", }; BooruDatasetBuilder datasetBuilder = new BooruDatasetBuilder(); for (int i = 0; i < globalTags.Length; i++) { datasetBuilder.AddGlobalTag(globalTags[i]); } for (int i = 0; i < tags.Length; i++) { datasetBuilder.AddLocalTag(tags[i]); } datasetBuilder.Download(500, @"I:\Datasets\Gelbooru"); //var inputDataset = datasetBuilder.GetDataset(@"I:\Datasets\Gelbooru", @"I:\Datasets\Gelbooru_SMALL", Side, 250); /* * var classifier = new NeuralNetworkBuilder(Side * Side * 3) * .WeightInitializer(new UniformWeightInitializer(0, 0)) * .LossFunction<Quadratic>() * .AddConv(3, 3, 1, 0, Side, 3) * .AddActivation<ReLU>() * .AddPooling(2, 2, 3) * .AddConv(3, 10, 1, 0, Side / 2, 3) * .AddActivation<ReLU>() * .AddPooling(2, 2, 10) * .AddFC(4096) * .AddActivation<LeakyReLU>() * .AddFC(1024) * .AddActivation<ReLU>() * .AddFC(512) * .AddActivation<ReLU>() * .AddFC(256) * .AddActivation<ReLU>() * .AddFC(64) * .AddActivation<ReLU>() * .AddFC(16) * .AddActivation<ReLU>() * .AddFC(8) * .AddActivation<ReLU>() * .AddFC(8) * .AddActivation<ReLU>() * .AddFC(8) * .AddActivation<ReLU>() * .AddFC(tags.Length) * .AddActivation<Sigmoid>() * .Build(); * * var trainer = new ClassifierTrainer("Anime Classifier", tags, classifier); * trainer.SetDataset(inputDataset); * * LearningManager.Show(trainer);*/ }