deconv_paragraph_represention | Deconvolutional Paragraph Representation Learning
kandi X-RAY | deconv_paragraph_represention Summary
kandi X-RAY | deconv_paragraph_represention Summary
deconv_paragraph_represention is a Python library. deconv_paragraph_represention has no vulnerabilities, it has build file available and it has low support. However deconv_paragraph_represention has 1 bugs. You can download it from GitHub.
Implementations of the models in the paper "Deconvolutional Paragraph Representation Learning" by Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao and Lawrence Carin, NIPS 2017.
Implementations of the models in the paper "Deconvolutional Paragraph Representation Learning" by Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao and Lawrence Carin, NIPS 2017.
Support
Quality
Security
License
Reuse
Support
deconv_paragraph_represention has a low active ecosystem.
It has 155 star(s) with 47 fork(s). There are 8 watchers for this library.
It had no major release in the last 6 months.
There are 2 open issues and 8 have been closed. On average issues are closed in 8 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of deconv_paragraph_represention is current.
Quality
deconv_paragraph_represention has 1 bugs (1 blocker, 0 critical, 0 major, 0 minor) and 275 code smells.
Security
deconv_paragraph_represention has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
deconv_paragraph_represention code analysis shows 0 unresolved vulnerabilities.
There are 4 security hotspots that need review.
License
deconv_paragraph_represention does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
deconv_paragraph_represention releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
deconv_paragraph_represention saves you 1069 person hours of effort in developing the same functionality from scratch.
It has 2423 lines of code, 156 functions and 25 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed deconv_paragraph_represention and discovered the below as its top functions. This is intended to give you an instant insight into deconv_paragraph_represention implemented functionality, and help decide if they suit your requirements.
- Convolutional decoder
- Performs regularization
- Convolutional model
- Decompose a 4 layer
- Calculate ROUGE score
- Safe divider
- Calculate the F1 score
- ROUGE - l recall score
- Prepare the data for a character network
- Convert an index to a list of integers
- Restore T_vars from file
- Find the key in a checkpoint
- Calculate the Nkde density
- Wrapper for convolution
- Calculate the squared error
- Embed embedding only
- Calculate the gain for a given set of inputs
- ROUGE - 1
- Calculate ROUGE - 2
- Convert text to indices
- Add noise to sents
- Compute the score for the given images
- Prepare data for training
- Compute the cider score
- Calculate the average score
- Embed embedding
Get all kandi verified functions for this library.
deconv_paragraph_represention Key Features
No Key Features are available at this moment for deconv_paragraph_represention.
deconv_paragraph_represention Examples and Code Snippets
No Code Snippets are available at this moment for deconv_paragraph_represention.
Community Discussions
No Community Discussions are available at this moment for deconv_paragraph_represention.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install deconv_paragraph_represention
You can download it from GitHub.
You can use deconv_paragraph_represention like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use deconv_paragraph_represention like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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 .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
