Tensorflow 中的计划采样

问题描述

最新的关于seq2seq模型的Tensorflow api已经包含了定时采样:

The newest Tensorflow api about seq2seq model has included scheduled sampling:

https://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/ScheduledEmbeddingTrainingHelperhttps://www.tensorflow.org/api_docs/python/tf/contrib/seq2seq/ScheduledOutputTrainingHelper

预定抽样的原始论文可以在这里找到:https://arxiv.org/abs/1506.03099

The original paper of scheduled sampling can be found here:https://arxiv.org/abs/1506.03099

我阅读了论文，但我无法理解ScheduledEmbeddingTrainingHelper 和ScheduledOutputTrainingHelper 之间的区别.文档只说 ScheduledEmbeddingTrainingHelper 是一个添加预定采样的训练助手，而 ScheduledOutputTrainingHelper 是一个直接将预定采样添加到输出的训练助手.

I read the paper but I cannot understand the difference between ScheduledEmbeddingTrainingHelper and ScheduledOutputTrainingHelper. The documentation only says ScheduledEmbeddingTrainingHelper is a training helper that adds scheduled sampling while ScheduledOutputTrainingHelper is a training helper that adds scheduled sampling directly to outputs.

我想知道这两个助手有什么区别?

I wonder what's the difference between these two helpers?

推荐答案

我联系了这背后的工程师，他回复了:

I contacted the engineer behind this, and he responded:

输出采样器在该时间步发出原始 rnn 输出或原始地面实况.嵌入采样器将 rnn 输出视为分布的对数，并发出来自该分类分布的采样 id 的嵌入查找或该时间步的原始地面实况.

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