def ex_info_gan(): data_sets = ReWrite.load_data_in_seq(source_files) data_sets = ReWrite.MyDataSet(data_sets) data_loader = DataLoader( data_sets, batch_size=256, shuffle=True, ) generator = G_D_Module.GeneratorInfo(latent_dim=50, n_classes=5, code_dim=2, img_shape=img_shape) discriminator = G_D_Module.DiscriminatorInfo(n_classes=5, code_dim=2, img_shape=img_shape) TrainFunction.train_info_gan(generator, discriminator, data_loader, opt.n_epochs, opt.lr, opt.b1, opt.b2, latent_dim=50, n_classes=5, code_dim=2, cuda=cuda, first_train=False)
def ex_ponodcwcgan(): data_sets = ReWrite.load_data_in_seq(source_files) data_sets = ReWrite.MyDataSet(data_sets) data_loader = DataLoader( data_sets, batch_size=256, shuffle=True, ) latent_dim = 100 generator = G_D_Module.GeneratorPONODCWCGAN( latent_dim, opt.n_classes, img_shape) # latent_dim should be 20 discriminator = G_D_Module.DiscriminatorPONODCWCGAN( opt.n_classes, img_shape) TrainFunction.train_ponodcwcgan(generator, discriminator, data_loader, opt.n_epochs, opt.lr, opt.b1, opt.b2, latent_dim, opt.n_classes, cuda, fist_train=False)
def ex_self_noise_gan(): data_sets = ReWrite.load_data_in_seq(source_files) data_sets = ReWrite.MyDataSet(data_sets) data_loader = DataLoader( data_sets, batch_size=256, shuffle=True, ) generator = G_D_Module.GeneratorSelfNoise(img_shape) discriminator = G_D_Module.DiscriminatorSelfNoise(img_shape) TrainFunction.train_self_noise_gan(generator, discriminator, data_loader, opt.n_epochs, opt.lr, opt.b1, opt.b2, cuda, first_train=False)
def ex_selfnoise_1d_gan(): data_sets = ReWrite.load_data_in_seq_1d('data') data_sets = ReWrite.MyDataSet1D(data_sets) data_loader = DataLoader( data_sets, batch_size=128, shuffle=True, ) generator = G_D_Module.GeneratorSelfNoise1D() discriminator = G_D_Module.DiscriminatorSelfNoise1D() TrainFunction.train_selfnoise_1d_gan(generator, discriminator, data_loader, opt.n_epochs, opt.lr, opt.b1, opt.b2, -1, opt.n_classes, cuda, first_train=False)
def ex_linear1d_gan(): data_sets = ReWrite.load_data_in_seq_1d('data') data_sets = ReWrite.MyDataSet1D(data_sets) data_loader = DataLoader( data_sets, batch_size=512, shuffle=True, ) latent_dim = 50 generator = G_D_Module.GeneratorLinear1D(latent_dim, opt.n_classes) discriminator = G_D_Module.DiscriminatorLinear1D(opt.n_classes) TrainFunction.train_linear_1d_gan(generator, discriminator, data_loader, opt.n_epochs, opt.lr, opt.b1, opt.b2, latent_dim, opt.n_classes, cuda, first_train=False)