TransE-Knowledge-Graph-Embedding | TensorFlow implementation of TransE | Graph Database library

by Lapis-Hong Python Version: Current License: MIT

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

kandi X-RAY | TransE-Knowledge-Graph-Embedding Summary

TransE-Knowledge-Graph-Embedding is a Python library typically used in Database, Graph Database, Tensorflow applications. TransE-Knowledge-Graph-Embedding has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TransE-Knowledge-Graph-Embedding build file is not available. You can download it from GitHub.

TensorFlow implementation of TransE and its extended models for Knowledge Representation Learning

Support

Quality

Security

License

Reuse

Support

TransE-Knowledge-Graph-Embedding has a low active ecosystem.

It has 61 star(s) with 17 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 0 have been closed. On average issues are closed in 480 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of TransE-Knowledge-Graph-Embedding is current.

Quality

TransE-Knowledge-Graph-Embedding has 0 bugs and 0 code smells.

Security

TransE-Knowledge-Graph-Embedding has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

TransE-Knowledge-Graph-Embedding code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

TransE-Knowledge-Graph-Embedding is licensed under the MIT License. This license is Permissive.

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

Reuse

TransE-Knowledge-Graph-Embedding releases are not available. You will need to build from source code and install.

TransE-Knowledge-Graph-Embedding has no build file. You will be need to create the build yourself to build the component from source.

TransE-Knowledge-Graph-Embedding saves you 159 person hours of effort in developing the same functionality from scratch.

It has 396 lines of code, 27 functions and 14 files.

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

Top functions reviewed by kandi - BETA

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

Build the graph
Get an optimizer instance
Prints out the model stats
Compute the score function
Train the model
Save the current step
Trains the model
Returns an iterator over the dataset
Generate samples from the input file
Load vocabulary from file
Print the arguments to stdout

Get all kandi verified functions for this library.

TransE-Knowledge-Graph-Embedding Key Features

No Key Features are available at this moment for TransE-Knowledge-Graph-Embedding.

TransE-Knowledge-Graph-Embedding Examples and Code Snippets

No Code Snippets are available at this moment for TransE-Knowledge-Graph-Embedding.

Community Discussions

Trending Discussions on TransE-Knowledge-Graph-Embedding

Use tensorflow's .ckpt model

QUESTION

Use tensorflow's .ckpt model

Asked 2020-Sep-10 at 11:03

I used this code for training a model. I now have 3 files:

model.ckpt-1.meta
model.ckpt-1.index
model.ckpt-1.data-00000-of-00001

How (with what methods) can I use these models now?

...

ANSWER

Answered 2020-Sep-10 at 11:03

I'm not exactly sure what you mean with

How (with what methods) can I use these models now?

The model is not saved in those files but i can be restored with them.

Those*.ckpt get saved during training but do not contain your model. If you want to "use" your model you need to restore those files to it. Take a look at Tensorflow's Checkpoint and CheckpointManager. This tutorial shows a simple snipped of how to restore .ckpt files to your model.

Source https://stackoverflow.com/questions/63823994

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

Vulnerabilities

No vulnerabilities reported

Install TransE-Knowledge-Graph-Embedding

You can download it from GitHub.
You can use TransE-Knowledge-Graph-Embedding 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: