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modify the training config

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This commit is contained in:
rtz19970824 2017-12-22 13:30:48 +08:00
parent 7f1191ef02
commit d151f71ee3
1 changed files with 4 additions and 3 deletions
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7
AlphaGo/model.py
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@ -101,8 +101,8 @@ class ResNet(object):
self._build_network(residual_block_num, self.checkpoint_path)
# training hyper-parameters:
self.window_length = 1000
self.save_freq = 1000
self.window_length = 7000
self.save_freq = 5000
self.training_data = {'states': deque(maxlen=self.window_length), 'probs': deque(maxlen=self.window_length),
'winner': deque(maxlen=self.window_length)}
@ -241,6 +241,7 @@ class ResNet(object):
self.saver.save(self.sess, self.checkpoint_path + save_path)
def _file_to_training_data(self, file_name):
print(file_name)
with open(file_name, 'r') as file:
data = cPickle.load(file)
history = deque(maxlen=self.history_length)
@ -267,4 +268,4 @@ class ResNet(object):
if __name__=="__main__":
model = ResNet(board_size=9, action_num=82)
model.train("file", data_path="./data/", batch_size=128, checkpoint_path="./checkpoint/")
model.train("file", data_path="./data/", batch_size=128, checkpoint_path="./checkpoint/")