关于采样结果不能直接计算 compute_levenshtein()

[JinmingZhao]

Hi，

https://github.com/ne7ermore/deeping-flow/blob/master/reinforced-translate/model.py

b_words = model.sample(self.prev) s_words, s_props = model.sample(self.prev, False)

rewards = self.compute_levenshtein(model.tgt, s_words) baseline = self.compute_levenshtein(model.tgt, b_words) advantage = rewards - baseline

其中的 b-words 和 s-words 都是 Tensor 类型， 而计算 compute_levenshtein 里面直接用的 for 循环展开，用的 eager 模式？

Thanks