Define your own trainer extensions in Chainer

    So how to implement custom extensions for trainer in Chainer? There are mainly 3 approaches. Define function Use decorator, Define class Most of the case, 1. Define function is the easiest way to quickly implement your extension.   1. Define function Just a function can be a trainer extension. Simply, define a function […]

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Predict code for Penn Bank Tree (ptb) dataset

  Predict code is pretty much the same with Predict code for simple sequence dataset, so I won’t explain in detail.   Code The code is on the github,

    Given the first text by the index, args.primeindex, model will predict the following sequence as word id. The last three line converts the […]

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Training LSTM model with Penn Bank Tree (ptb) dataset

  This post mainly explains, uploaded on github.   We have already learned RNN and LSTM network architecture, let’s apply it to PTB dataset. It is quite similar to explained in Training RNN with simple sequence dataset, so no much explanation is necessary.   Train code I will just paste whole the training code […]

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Penn Tree Bank (PTB) dataset introduction

  This post is based on the jupyter notebook ptb_dataset_introduction.ipynb uploaded on github. Penn Treebank dataset, known as PTB dataset, is widely used in machine learning of NLP (Natural Language Processing) research. Dataset if provided by the official page: Treebank-3 In Chainer, PTB dataset can be obtained with build-in function. Let’s see the dataset structure.  


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