Metadata-Version: 2.1
Name: triple_walk
Version: 0.0.2
Summary: A pytorch extension library to perform triple walks on knowledge graphs
Home-page: UNKNOWN
Author: Sachin Gavali
Author-email: saching@udel.edu
License: UNKNOWN
Description: > A simple algorithm to learn embeddings of entities in knowledge graph.
        
        ## What is it
        TripleWalk is an algorithm to learn vector embeddings of entities in a knowledge graph by performing random walks on triples.
        
        ## Installation
        
        ***Please not this package is only available for python 3.8+ and Pytorch >= 1.9.0***
        
        #### Install from PyPI
        ``` Python
        pip install triple-walk
        ```
        
        #### Install from Github
        ``` bash
        pip install git+https://github.com/udel-cbcb/triple_walk.git#egg=triple_walk
        ```
        
        
        # Triple Walk
        Author : Sachin Gavali
        
        ## Requirements
        ```
        1. Pytorch >= 1.9.0
        2. NVIDIA-GPU (Cuda Toolkit >= 11.4
        3. AMD-GPU (ROCM == 4.0.1)
        4. Python == 3.8
        ```
        
        ## Examples
        * SkipGram Triple Walk model : [SkipGramTriple](examples/skipgram_triple_walk.py)
        * CBOW Triple Walk model : [CBOWTriple](examples/skipgram_triple_walk.py)
        
        
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
