make visdom default & add no_html & update scripts

1 files changed, 4 insertions, 4 deletions

diff --git a/options/train_options.py b/options/train_options.py
index e7d4b3a..b241863 100644
--- a/options/train_options.py
+++ b/options/train_options.py
@@ -7,8 +7,7 @@ class TrainOptions(BaseOptions):
         self.parser.add_argument('--print_freq', type=int, default=100, help='frequency of showing training results on console')
         self.parser.add_argument('--save_latest_freq', type=int, default=5000, help='frequency of saving the latest results')
         self.parser.add_argument('--save_epoch_freq', type=int, default=5, help='frequency of saving checkpoints at the end of epochs')
-        self.parser.add_argument('--save_display_freq', type=int, default=2500, help='save the current display of results every save_display_freq_iterations')
-        self.parser.add_argument('--continue_train', action='store_true', help='if continue training, load the latest model')
+        self.parser.add_argument('--continue_train', action='store_true', help='continue training: load the latest model')
         self.parser.add_argument('--phase', type=str, default='train', help='train, val, test, etc')
         self.parser.add_argument('--which_epoch', type=str, default='latest', help='which epoch to load? set to latest to use latest cached model')
         self.parser.add_argument('--niter', type=int, default=100, help='# of iter at starting learning rate')
@@ -16,9 +15,10 @@ class TrainOptions(BaseOptions):
         self.parser.add_argument('--beta1', type=float, default=0.5, help='momentum term of adam')
         self.parser.add_argument('--ntrain', type=int, default=float("inf"), help='# of examples per epoch.')
         self.parser.add_argument('--lr', type=float, default=0.0002, help='initial learning rate for adam')
-        self.parser.add_argument('--no_lsgan', action='store_true', help='if true, do *not* use least square GAN, if false, use vanilla GAN')
+        self.parser.add_argument('--no_lsgan', action='store_true', help='do *not* use least square GAN, if false, use vanilla GAN')
         self.parser.add_argument('--lambda_A', type=float, default=10.0, help='weight for cycle loss (A -> B -> A)')
         self.parser.add_argument('--lambda_B', type=float, default=10.0, help='weight for cycle loss (B -> A -> B)')
         self.parser.add_argument('--pool_size', type=int, default=0, help='the size of image buffer that stores previously generated images')
-        self.parser.add_argument('--preprocessing', type=str, default='resize_and_crop', help='resizing/cropping strategy')
+        self.parser.add_argument('--no_html', action='store_true', help='do not save intermediate training results to [opt.checkpoints_dir]/[opt.name]/web/')
+        # NOT-IMPLEMENTED self.parser.add_argument('--preprocessing', type=str, default='resize_and_crop', help='resizing/cropping strategy')
         self.isTrain = True