matlab代码左移-Neural-Machine-Translation-seq2seq-Tutorial:神经机器翻译-seq2seq-教

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matlab代码左移神经机器翻译(seq2seq)教程 作者:Thang Luong,Eugene Brevdo,赵瑞(,) 此版本的教程要求。 要使用稳定的TensorFlow版本,请考虑其他分支,例如。 如果您使用此代码库进行研究,请引用。 介绍 序列到序列(seq2seq)模型(,)在各种任务(例如机器翻译,语音识别和文本摘要)中都取得了巨大的成功。 本教程为读者提供了对seq2seq模型的全面理解,并展示了如何从头开始构建具有竞争力的seq2seq模型。 我们专注于神经机器翻译(NMT)的任务,这是带有wild的seq2seq模型的第一个测试平台。 所包含的代码轻巧,高质量,可立即投入生产,并结合了最新的研究思路。 我们通过以下方式实现这一目标: 使用最新的解码器/注意包装器,TensorFlow 1.2数据迭代器 结合我们在构建递归模型和seq2seq模型方面的专业知识 提供有关构建最佳NMT模型和复制的提示和技巧。 我们认为,提供人们可以轻松复制的基准非常重要。 结果,我们提供了完整的实验结果,并在以下公开可用的数据集上对我们的模型进行了预训练: 小型:由ET提供的TED演

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