ne7ermore / deeping-flow

Deep-learning by using TensorFlow. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.
MIT License
50 stars 14 forks source link

关于采样结果不能直接计算 compute_levenshtein() #7

Open JinmingZhao opened 5 years ago

JinmingZhao commented 5 years ago

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