modify the training config
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@ -101,8 +101,8 @@ class ResNet(object):
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self._build_network(residual_block_num, self.checkpoint_path)
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# training hyper-parameters:
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self.window_length = 1000
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self.save_freq = 1000
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self.window_length = 7000
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self.save_freq = 5000
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self.training_data = {'states': deque(maxlen=self.window_length), 'probs': deque(maxlen=self.window_length),
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'winner': deque(maxlen=self.window_length)}
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@ -241,6 +241,7 @@ class ResNet(object):
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self.saver.save(self.sess, self.checkpoint_path + save_path)
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def _file_to_training_data(self, file_name):
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print(file_name)
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with open(file_name, 'r') as file:
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data = cPickle.load(file)
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history = deque(maxlen=self.history_length)
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