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)