update save and load

alphago_value.py

@@ -0,0 +1,21 @@
+""" AlphaGo 的价值网络部分，用于评估棋盘状态的价值，即估算当前的局面走某步棋后的胜率 """
+# from tugo.models.alphago import alphago_model
+from tugo.models.alphago import AlphaGoModel
+from tugo.encoders.alphago import AlphaGoEncoder
+from tugo.rl.value import ValueAgent
+from tugo.rl.experience import ExperienceBuffer
+
+# init_value
+rows, cols = 19, 19
+encoder = AlphaGoEncoder()
+input_shape = (encoder.num_planes, rows, cols)
+alphago_value_network = AlphaGoModel(input_shape)
+
+alphago_value = ValueAgent(alphago_value_network, encoder)
+
+# train_value
+experience = ExperienceBuffer.load('checkpoints/alphago_rl_experience.h5')
+
+alphago_value.train(experience)
+
+alphago_value.save('checkpoints/alphago_value.h5')