dcgan_vae_pytorch
dcgan combined with vae in pytorch!
this code is based on pytorch/examples and staturecrane/dcgan_vae_torch
The original artical can be found here
Requirements
- torch
- torchvision
- visdom
- (optional) lmdb
Usage
to start visdom:
python -m visdom.server
to start the training:
usage: main.py [-h] --dataset DATASET --dataroot DATAROOT [--workers WORKERS]
[--batchSize BATCHSIZE] [--imageSize IMAGESIZE] [--nz NZ]
[--ngf NGF] [--ndf NDF] [--niter NITER] [--saveInt SAVEINT] [--lr LR]
[--beta1 BETA1] [--cuda] [--ngpu NGPU] [--netG NETG]
[--netD NETD]
optional arguments:
-h, --help show this help message and exit
--dataset DATASET cifar10 | lsun | imagenet | folder | lfw
--dataroot DATAROOT path to dataset
--workers WORKERS number of data loading workers
--batchSize BATCHSIZE
input batch size
--imageSize IMAGESIZE
the height / width of the input image to network
--nz NZ size of the latent z vector
--ngf NGF
--ndf NDF
--niter NITER number of epochs to train for
--saveInt SAVEINT number of epochs between checkpoints
--lr LR learning rate, default=0.0002
--beta1 BETA1 beta1 for adam. default=0.5
--cuda enables cuda
--ngpu NGPU number of GPUs to use
--netG NETG path to netG (to continue training)
--netD NETD path to netD (to continue training)