NQG | Neural Question Generation from Text : A Preliminary Study | Machine Learning library

by magic282 Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | NQG Summary

NQG is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. NQG has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However NQG build file is not available. You can download it from GitHub.

The experiments in the paper were done with an in-house deep learning tool. Therefore, we re-implement this with PyTorch as a reference. This code only implements the setting NQG+ in the paper. Within 1 hour's training on Tesla P100, the NQG+ model achieves 12.78 BLEU-4 score on the dev set.

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Quality

Security

License

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NQG has a low active ecosystem.

It has 135 star(s) with 27 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 11 have been closed. On average issues are closed in 238 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NQG is current.

Quality

NQG has 0 bugs and 243 code smells.

Security

NQG has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NQG code analysis shows 0 unresolved vulnerabilities.

There are 2 security hotspots that need review.

License

NQG is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

NQG releases are not available. You will need to build from source code and install.

NQG has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions, examples and code snippets are available.

NQG saves you 842 person hours of effort in developing the same functionality from scratch.

It has 1930 lines of code, 118 functions and 24 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed NQG and discovered the below as its top functions. This is intended to give you an instant insight into NQG implemented functionality, and help decide if they suit your requirements.

Train a model
Update learning rate based on ppl
Create a NLLLoss
Shuffle the features
Compute BLEU
Compute the modified precision
Calculate brevity penalty
Find the length of the closest reference
Add training options to the given parser
Computes a sentence BLEU
Compute the BLEU score
Save a tf model
Perform a single step
Add data options for training
Load dev data
Collects the vocabulary
Add model options to given parser
Forward computation
Translate source to words
Prepare the data for training
Forward layer attention
Forward the input tensor
Create a vocabulary from a list of filenames
Set parameters
Implements Method 4
Calculate the total loss function
Load labels from file

Get all kandi verified functions for this library.

NQG Key Features

No Key Features are available at this moment for NQG.

NQG Examples and Code Snippets

No Code Snippets are available at this moment for NQG.

Community Discussions

Trending Discussions on NQG

How can i read this javascript code?

QUESTION

How can i read this javascript code?

Asked 2018-May-10 at 15:49

I'm not really sure how can i read this code of Javascript, so i need your help guys to know if this normal or not!

My question is how can i read/unobfuscated this code

The full code here: rBKsXKct

...

ANSWER

Answered 2018-May-10 at 15:49

The code is obfuscated using this function:

Source https://stackoverflow.com/questions/50274243

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install NQG

PyTorch version: This code requires PyTorch v0.4.0. Python version: This code requires Python3. Warning: Older versions of NLTK have a bug in the PorterStemmer. Therefore, a fresh installation or update of NLTK is recommended. A Docker image is also provided.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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