BAMnet | Code & data accompanying the NAACL 2019 paper "Bidirectional Attentive Memory Networks for Question | Machine Learning library

by hugochan Python Version: Current License: Apache-2.0

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

kandi X-RAY | BAMnet Summary

BAMnet is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Neural Network applications. BAMnet has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Code & data accompanying the NAACL2019 paper "Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases".

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Quality

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BAMnet has a low active ecosystem.

It has 172 star(s) with 36 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 9 have been closed. On average issues are closed in 110 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of BAMnet is current.

Quality

BAMnet has 0 bugs and 0 code smells.

Security

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

BAMnet code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

BAMnet is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

BAMnet 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.

BAMnet saves you 1112 person hours of effort in developing the same functionality from scratch.

It has 2516 lines of code, 120 functions and 28 files.

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

Top functions reviewed by kandi - BETA

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

Vectorize data
Vectorize Ent data
Train the model
Pad the ctx memory
Predict a single step
Predict next batch of candidates
Return a list of candidate answers
Determine if a filter is filter out
Build query data
Build candidate answers
Removes mentions from the given query
Fetch metadata from subgraph
Builds a vocabulary
Performs a multi - task forward
Forward computation
Build seed entity data
Compute the forward computation
Extract the feature from the given text
Get all freebase keys
Print a progress bar
Compute the layer
Calculate a premature score
Dump embeddings to disk
Predict next batch
Get a set of freebase keys used in training and validation sets
Predict next batch of data

Get all kandi verified functions for this library.

BAMnet Key Features

No Key Features are available at this moment for BAMnet.

BAMnet Examples and Code Snippets

No Code Snippets are available at this moment for BAMnet.

Community Discussions

Trending Discussions on BAMnet

Push gitlab repository code to Google source repository

QUESTION

Push gitlab repository code to Google source repository

Asked 2020-Aug-29 at 19:54

I followed below article to push gitlab repository code to Google cloud source repository but I'm getting an error on this command

...

ANSWER

Answered 2020-Aug-29 at 19:54

src refspec master does not match any

Source https://stackoverflow.com/questions/63648650

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

Vulnerabilities

No vulnerabilities reported

Install BAMnet

You can download it from GitHub.
You can use BAMnet 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 .

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