SWEM | Tensorflow code for this ACL 2018 paper | Natural Language Processing library

by dinghanshen Python Version: Current License: No License

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

kandi X-RAY | SWEM Summary

SWEM is a Python library typically used in Artificial Intelligence, Natural Language Processing, Deep Learning, Pytorch, Tensorflow, Bert applications. SWEM has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This repository contains source code necessary to reproduce the results presented in the following paper:. This project is maintained by Dinghan Shen. Feel free to contact dinghan.shen@duke.edu for any relevant issues.

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Quality

Security

License

Reuse

Support

SWEM has a low active ecosystem.

It has 282 star(s) with 53 fork(s). There are 12 watchers for this library.

It had no major release in the last 6 months.

There are 7 open issues and 5 have been closed. On average issues are closed in 55 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SWEM is current.

Quality

SWEM has 0 bugs and 0 code smells.

Security

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

SWEM code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SWEM 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

SWEM 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.

SWEM saves you 2541 person hours of effort in developing the same functionality from scratch.

It has 5523 lines of code, 367 functions and 49 files.

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

Top functions reviewed by kandi - BETA

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

Auto encoder
Encoder
2layer layer
Embed word embedding
Build the layer
Adds a weight layer
Add a non - trainable weight
Construct the offset from the input shape
Restore tensors from save_vars
Return the key of tensors key in a file
Notes a list
Prepare data for rank
Build the convolution matrix
Calculate the average of actual and predicted precision
Calculate the mean reciprocal rank
Compute the score for a set of images
Generate indices of n - grams
Compute the mean average precision
Returns the key of the tensors key in a file
Convert text to index
Calculate the average score for an image
Embedding layer
Build the model
Build the convolution layer
Prepare data for embedding
Prepare the data for training
Compute the score for a given set of images

Get all kandi verified functions for this library.

SWEM Key Features

No Key Features are available at this moment for SWEM.

SWEM Examples and Code Snippets

No Code Snippets are available at this moment for SWEM.

Community Discussions

Trending Discussions on SWEM

Printing every row of dataframe to .txt in specific format

QUESTION

Printing every row of dataframe to .txt in specific format

Asked 2020-Jun-06 at 00:12

I am creating software that generates inputs for an electrical grid simulator. The simulator reads a new txt file of energy demand for each period.

I have a data frame that I want to iterate through and generate a new text file for each line.

...

ANSWER

Answered 2020-Jun-05 at 23:39

EDIT: I added an ugly workaround using .replace to get rid of the brackets and new line. This requires a lot of file opening and closing which isn't ideal but this task is often only performed once.

Source https://stackoverflow.com/questions/62224121

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

Vulnerabilities

No vulnerabilities reported

Install SWEM

You can download it from GitHub.
You can use SWEM 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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