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idcnn-crf-pytorch's Introduction

IDCNN-CRF-Pytorch

迭代膨胀卷积命名实体抽取
论文 Fast and Accurate Entity Recognition with Iterated Dilated Convolutions pytorch实现
Git翻了一圈竟然没有pytorch的实现，于是撸了一个。
戳这里有动态原理图
除了没有Pooling操作和加了dilation，和普通卷积基本相同，并不神秘

几点总结

  • 没有传说中的快，虽然每层是并行的，但是由于是多个CNN stacking结构（为了捕获长程信息），层与层之间还是串行的
  • 对于文本较长的，意味着block层数(N)需要越多，按log(N)增长，容易出现梯度消失。这里我加了层归一化和relu缓解这个问题。
  • 在长本文上（seq_length=256）试了一把，效果没有BILSTM好，谨慎使用

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