acl_flow | Normalizing Flow for PCFG induction

by lifengjin Python Version: Current License: No License

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

kandi X-RAY | acl_flow Summary

acl_flow is a Python library. acl_flow has no bugs, it has no vulnerabilities and it has low support. However acl_flow build file is not available. You can download it from GitHub.

This is the repository for our ACL 2019 paper Unsupervised PCFG Induction with Normalizing Flow. Newest versions of the packages should also work.

Support

Quality

Security

License

Reuse

Support

acl_flow has a low active ecosystem.

It has 7 star(s) with 2 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

acl_flow has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of acl_flow is current.

Quality

acl_flow has no bugs reported.

Security

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

License

acl_flow 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

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

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

Top functions reviewed by kandi - BETA

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

Sample the log space from the tree
Forward computation
Sample from the model
True if j is a terminal
Wrap sampling_beam
Compiles embeddings
Batch function
Sample a beam
R Replaces a pseudo - count model
Calculate the delta matrix of the model
Calculate the sum of the sum of the gamma values
Translate model to pcfg
Compute the non - term nonterms
Compute Q coefficients
Calculate expansion dependency
Computes the probabilities for a single cat
Calculate the average depth of a tree
Calculates the accuave depth per tree
Calculate the length of all trees
Calculates the maximum length of the tree
Get the maximum depth of trees
Calculates the maximum depth of a tree
Calculate the measures at n
Read parameters from config file

Get all kandi verified functions for this library.

acl_flow Key Features

No Key Features are available at this moment for acl_flow.

acl_flow Examples and Code Snippets

No Code Snippets are available at this moment for acl_flow.

Community Discussions

No Community Discussions are available at this moment for acl_flow.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install acl_flow

You can download it from GitHub.
You can use acl_flow 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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