# Number of jumps per scale _C.alphaNJumps = [0, 600, 600, 600, 600, 600, 600, 600, 600] # Number of iterations between two jumps _C.alphaSizeJumps = [0, 32, 32, 32, 32, 32, 32, 32, 32, 32] ############################################################# # Type of convolutional layer _C.transposed = False # Depth of a convolutional layer for each scale _C.depthScales = [512, 512, 512, 512, 256, 128, 64, 32, 16] # Mini batch size _C.miniBatchSize = 16 # Dimension of the latent vector _C.dimLatentVector = 512 # Should bias be initialized to zero ? _C.initBiasToZero = True # Per channel normalization _C.perChannelNormalization = True # Loss mode _C.lossMode = 'WGANGP' _C.ac_gan = False # Gradient penalty coefficient (WGANGP)
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved # # Source: https://github.com/facebookresearch/pytorch_GAN_zoo from utils.config import BaseConfig # Default configuration for ProgressiveGANTrainer _C = BaseConfig() ############################################################ # Depth of a convolutional layer for each scale _C.depth = 3 # Mini batch size _C.miniBatchSize = 256 # 64 # Dimension of the latent vector _C.dimLatentVector = 100 # Dimension of the output image _C.dimOutput = 3 # Dimension of the generator _C.dimG = 64 # Dimension of the discrimator _C.dimD = 64 # Image dimension _C.imageSize = 64