Update srpseudolabel.py

semilearn/algorithms/srpseudolabel/srpseudolabel.py

@@ -34,11 +34,11 @@ def __init__(self, args, net_builder, tb_log=None, logger=None, **kwargs):
         super().__init__(args, net_builder, tb_log, logger, **kwargs)
         self.init(p_cutoff=args.p_cutoff, unsup_warm_up=args.unsup_warm_up)
         self.it=0
-        self.rewarder = Rewarder(128,384).cuda(self.gpu)
-        self.generator = Generator(384).cuda(self.gpu)
-        self.starttiming=20000
-        self.rewarder_optimizer = torch.optim.Adam(self.rewarder.parameters(), lr=0.0005)
-        self.generator_optimizer = torch.optim.Adam(self.generator.parameters(), lr=0.0005)
+        self.rewarder = Rewarder(128,self.featinput).cuda(self.gpu)
+        self.generator = Generator(self.featinput).cuda(self.gpu)
+        self.starttiming=self.start
+        self.rewarder_optimizer = torch.optim.Adam(self.rewarder.parameters(), lr=self.srlr)
+        self.generator_optimizer = torch.optim.Adam(self.generator.parameters(), lr=self.srlr)
         self.criterion = torch.nn.MSELoss()
 
         self.semi_reward_infer = SemiReward_infer(self.rewarder, self.starttiming)
@@ -109,4 +109,4 @@ def get_argument():
             SSL_Argument('--p_cutoff', float, 0.95),
             SSL_Argument('--unsup_warm_up', float, 0.4, 'warm up ratio for unsupervised loss'),
             # SSL_Argument('--use_flex', str2bool, False),
-        ]
+        ]