mine + infogan
python infogan.py --help
usage: infogan.py [-h] [--n_epochs N_EPOCHS] [--batch_size BATCH_SIZE]
[--lr LR] [--b1 B1] [--b2 B2] [--n_cpu N_CPU]
[--latent_dim LATENT_DIM] [--code_dim CODE_DIM]
[--n_classes N_CLASSES] [--img_size IMG_SIZE]
[--channels CHANNELS] [--sample_interval SAMPLE_INTERVAL]
optional arguments:
-h, --help show this help message and exit
--n_epochs N_EPOCHS number of epochs of training
--batch_size BATCH_SIZE
size of the batches
--lr LR adam: learning rate
--b1 B1 adam: decay of first order momentum of gradient
--b2 B2 adam: decay of first order momentum of gradient
--n_cpu N_CPU number of cpu threads to use during batch generation
--latent_dim LATENT_DIM
dimensionality of the latent space
--code_dim CODE_DIM latent code
--n_classes N_CLASSES
number of classes for dataset
--img_size IMG_SIZE size of each image dimension
--channels CHANNELS number of image channels
--sample_interval SAMPLE_INTERVAL
interval between image samplingpython infogan.py --n_epochs=200 --batch_size 64 --lr 0.0002 --n_cpu 8 --latent_dim 62 --code_dim 2