论文解读:Sequence to Sequence Mixture Model for Diverse Machine Translation 论文解读:Sequence to Sequence Mixture Model for Diverse Machine Translation 机器翻译是自然语言处理中比较热门的研究任务,在深度学习背景下,通过神经网络搭建的机器翻译也称为当今主流方式。在解决机器翻译过程中需要解决诸多问题,...
首先介绍几篇比较重要的 seq2seq 相关的论文: [1] Cho et al., 2014 . Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation [2] Sutskever et al., 2014. Sequence …
The evaluation process of Seq2seq PyTorch is to check the model output. Each pair of Sequence to sequence models will be feed into the model and generate the predicted words. After that you will look the highest value at each output to find the correct index. And in the end, you will ...
Neural translation model While the core of the sequence-to-sequence model is constructed by the functions intensorflow/tensorflow/python/ops/seq2seq.py, there are still a few tricks that are worth mentioning that are used in our translation model inmodels/tutorials/rnn/translate/seq2seq_model.py...
一、序列模型-sequence model 简介:一、序列模型-sequence model 在生活中,有许多领域都用到了序列模型,如语音识别,音乐创作,情感分类,DNA序列分析,机器翻译,视频动作检测,名称实体识别等。 1、符号定义 对于训练数据中的输入序列X和输出序列Y,令 x(i)<t>表示第 i个训练数据输入序列中,第 t个位置的序列元素;...
序列模型(Sequence Model) PNauX 代码编程初级 2 人赞同了该文章 1.参数介绍: sequence.pad_sequences() sequences --- 是要被填充或截断的序列列表 maxlen --- 序列的最大长度 dtype --- 填充值的数据类型,默认是int32 padding --- 指定了填充应该发生在序列的哪一边,默认是'pre' --- 意味着序列将被...
基本Sequence to Sequence模型描述了基本的Encoder-Decoder模型,在作为翻译模型的时候,这种基本的Encoder-Decoder模型有较大缺点,就是Encoder部分每一个输入对Decoder部分每一个输出的贡献都是一样的。下面先看一个例子[1], 在基本模型中,每一个英文单词对杰瑞都是一样的贡献,这似乎是不太合理的;也就是说 ...
序列模型(sequence models) 文章目录 循环神经网络 RNN出现前 RNN GRU 双向循环神经网络 深层循环神经网络 循环神经网络 RNN出现前 在RNN之前,语言模型主要是N-Gram。N是一个自然数,它的含义是假设一个词出现的概率至于前面N个词相关,我们以2-Gram为例:...
This example shows how to classify each time step of sequence data using a generic temporal convolutional network (TCN).
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