| import os |
|
|
|
|
| class Options: |
| def __init__(self, checkpoints, gpu_ids): |
| self.serial_batches = True |
| self.no_flip = True |
| self.label_nc = 0 |
| self.n_downsample_global = 3 |
| self.mc = 64 |
| self.k_size = 4 |
| self.start_r = 1 |
| self.mapping_n_block = 6 |
| self.map_mc = 512 |
| self.no_instance = True |
| self.checkpoints_dir = checkpoints |
| self.gpu_ids = gpu_ids |
| self.mapping_net_dilation = 1 |
| self.use_segmentation_model = False |
| self.feat_dim = -1 |
| self.spatio_size = 64 |
| self.resize_or_crop = 'scale_width' |
| self.isTrain = False |
| self.input_nc = 3 |
| self.output_nc = 3 |
| self.ngf = 64 |
| self.norm = "instance" |
| self.load_pretrain = "" |
| self.which_epoch = "latest" |
| self.load_pretrain = "" |
| self.no_load_VAE = False |
| self.use_vae_which_epoch = "latest" |
|
|
| self.NL_res = True |
| self.use_SN = True |
| self.correlation_renormalize = True |
| self.NL_use_mask = True |
| self.NL_fusion_method = "combine" |
| self.non_local = "Setting_42" |
| |
| self.load_pretrainA = os.path.join(self.checkpoints_dir, "VAE_A_quality") |
| self.load_pretrainB = os.path.join(self.checkpoints_dir, "VAE_B_scratch") |
|
|
| self.mapping_exp = 1 |
| self.inference_optimize = True |
| self.mask_dilation = 3 |
| self.name = "mapping_Patch_Attention" |
|
|
