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main.py

@@ -1,7 +1,6 @@
 
 from parameter import *
 from trainer import Trainer
-from qgan_trainer import Trainer as qgan_trainer
 # from tester import Tester
 from data_loader import Data_Loader
 from torch.backends import cudnn
@@ -18,7 +17,6 @@ def main(config):
 
     # Create directories if not exist
     make_folder(config.model_save_path, config.version)
-    make_folder(config.result_path, config.version)
     make_folder(config.sample_path, config.version)
     make_folder(config.log_path, config.version)
     make_folder(config.attn_path, config.version)

parameter.py

@@ -16,6 +16,7 @@ def get_parameters():
     parser.add_argument('--g_conv_dim', type=int, default=64)
     parser.add_argument('--d_conv_dim', type=int, default=64)
     parser.add_argument('--lambda_gp', type=float, default=10)
+    parser.add_argument('--version', type=str, default='sagan_1')
 
     # Training setting
     parser.add_argument('--total_step', type=int, default=1000000, help='how many times to update the generator')
@@ -31,33 +32,12 @@ def get_parameters():
     # using pretrained
     parser.add_argument('--pretrained_model', type=int, default=None)
 
-    # gating net
-    parser.add_argument('--gum_orig', type=float, default=1)  # gum start temperature
-    parser.add_argument('--gum_temp', type=float, default=1)
-    parser.add_argument('--min_temp', type=float, default=0.01)
-    parser.add_argument('--gum_temp_decay', type=float, default=0.0001)
-    parser.add_argument('--step_anneal', type=int, default=1)  # epoch to apply decaying
-    parser.add_argument('--start_anneal', type=int, default=0)  # epoch to start annealing
-
-
-    # Test setting
-    parser.add_argument('--test_size', type=int, default=64)
-    parser.add_argument('--test_model', type=str, default='50000_G.pth')
-    parser.add_argument('--result_path', type=str, default='./results')
-    parser.add_argument('--version', type=str, default='Gum')
-    parser.add_argument('--nrow', type=int, default=8)
-    parser.add_argument('--ncol', type=int, default=8)
-
     # Misc
     parser.add_argument('--train', type=str2bool, default=True)
     parser.add_argument('--parallel', type=str2bool, default=False)
-    parser.add_argument('--dataset', type=str, default='cifar', choices=['lsun', 'celeb', ])
+    parser.add_argument('--dataset', type=str, default='cifar', choices=['lsun', 'celeb'])
     parser.add_argument('--use_tensorboard', type=str2bool, default=False)
 
-    # Load balance
-    parser.add_argument('--load_balance_on', type=str2bool, default=False)
-    parser.add_argument('--load_weight', type=float, default=1.0) # for 2, for 5 1000, for 4500
-
     # Path
     parser.add_argument('--image_path', type=str, default='./data')
     parser.add_argument('--log_path', type=str, default='./logs')
@@ -70,9 +50,5 @@ def get_parameters():
     parser.add_argument('--sample_step', type=int, default=100)
     parser.add_argument('--model_save_step', type=float, default=1.0)
 
-    # claculating quantitative measures
-    parser.add_argument('--score_epoch', type=int, default=3)  # = 5 epochs
-    parser.add_argument('--score_start', type=int, default=3)  # start at 5 (default)
-
 
     return parser.parse_args()

trainer.py

@@ -40,30 +40,17 @@ def __init__(self, data_loader, config):
         self.beta1 = config.beta1
         self.beta2 = config.beta2
         self.pretrained_model = config.pretrained_model
-        self.gum_orig = config.gum_orig
-        self.gum_temp = config.gum_temp
-        self.min_temp = config.min_temp
-        self.gum_temp_decay = config.gum_temp_decay
-        self.step_anneal = config.step_anneal
-        self.start_anneal = config.start_anneal
-        self.test_model = config.test_model
-        self.result_path = config.result_path
-        self.version = config.version
-        self.nrow = config.nrow
-        self.ncol = config.ncol
+
         self.dataset = config.dataset
         self.use_tensorboard = config.use_tensorboard
-        self.load_balance_on = config.load_balance_on
-        self.load_weight = config.load_weight
         self.image_path = config.image_path
         self.log_path = config.log_path
         self.model_save_path = config.model_save_path
         self.sample_path = config.sample_path
         self.log_step = config.log_step
         self.sample_step = config.sample_step
         self.model_save_step = config.model_save_step
-        self.score_epoch = config.score_epoch
-        self.score_start = config.score_start
+        self.version = config.version
 
         # Path
         self.log_path = os.path.join(config.log_path, self.version)