update save and load

rl/value.py

@@ -3,10 +3,10 @@ import torch.nn as nn
 import torch.optim as optim
 from torch.distributions import Categorical
 
-from dlgo import encoders
-from dlgo import goboard
-from dlgo.agent import Agent
-from dlgo.agent.helpers import is_point_an_eye
+from tugo import encoders
+from tugo import goboard
+from tugo.agents import Agent
+from tugo.agents.helpers import is_point_an_eye
 
 
 class ValueAgent(Agent):
@@ -109,7 +109,7 @@ class ValueAgent(Agent):
     def diagnostics(self):
         return {'value': self.last_move_value}
 
-    def save(self, filename):
+    def save(self, file_path):
         torch.save({
             'model': self.model.state_dict(),
             'encoder': {
@@ -117,11 +117,11 @@ class ValueAgent(Agent):
                 'board_width': self.encoder.board_width,
                 'board_height': self.encoder.board_height,
             }
-        }, filename)
+        }, file_path)
 
     @classmethod
-    def load(cls, filename):
-        checkpoint = torch.load(filename)
+    def load(cls, file_path):
+        checkpoint = torch.load(file_path)
 
         model = Model()  # The Model class should be defined appropriately
         model.load_state_dict(checkpoint['model'])
@@ -134,9 +134,9 @@ class ValueAgent(Agent):
         return cls(model, encoder)
 
 
-def load_value_agent(filename):
+def load_value_agent(file_path):
     # 我假设 Model 类是预先定义好的 PyTorch 模型，你需要根据实际情况替换或实现这个模型。
-    checkpoint = torch.load(filename)
+    checkpoint = torch.load(file_path)
 
     model = Model()  # The Model class should be defined appropriately
     model.load_state_dict(checkpoint['model'])