def create_dcgan_encoder(args, device):
net = dcgan.Encoder(args.image_size, args.nc, args.ndf, args.nz, args.n_extra_layers)
net.apply(model_helper.weights_init)
print(net)
optimizer = model_helper.get_optimizer(args, net.parameters())
if torch.cuda.is_available():
net = net.type(torch.cuda.FloatTensor)
return net, optimizer
def create_mlp_encoder(args, device):
net = mlp.Encoder(args.image_size, args.nc, args.enc_layers, args.nz,
activation=nn.LeakyReLU(0.2), use_bn=True, dropout=0)
net.apply(model_helper.weights_init)
print(net)
optimizer = model_helper.get_optimizer(args, net.parameters())
if torch.cuda.is_available():
net = net.type(torch.cuda.FloatTensor)
return net, optimizer