8f420a3b35944dcfa470dee958ef61dee221ce02,implementations/dualgan/dualgan.py,,,#,20

Before Change

parser.add_argument("--b2", type=float, default=0.999, help="adam: decay of first order momentum of gradient")
parser.add_argument("--n_cpu", type=int, default=8, help="number of cpu threads to use during batch generation")
parser.add_argument("--n_residual_blocks", type=int, default=6, help="number of residual blocks in generator")
parser.add_argument("--latent_dim", type=int, default=10, help="dimensionality of the noise input")
parser.add_argument("--img_size", type=int, default=32, help="size of each image dimension")
parser.add_argument("--channels", type=int, default=3, help="number of image channels")
parser.add_argument("--n_critic", type=int, default=5, help="number of training steps for discriminator per iter")
parser.add_argument("--clip_value", type=float, default=0.01, help="lower and upper clip value for disc. weights")

After Change

opt = parser.parse_args()
print(opt)

img_shape = (opt.channels, opt.img_size, opt.img_size)

// Calculate output of image discriminator (PatchGAN)
patch = int(opt.img_size / 2**4)
patch = (1, patch, patch)

Instances