Skip to content

Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"

License

Notifications You must be signed in to change notification settings

viyang/code_search

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

GitHub license Python 3.6 GitHub issues

Semantic Code Search

Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"

Alt text


Resources

Docker Containers

You can use these container to reproduce the environment the authors used for this tutorial. Incase it is helpful, I have provided a requirements.txt file, however, we highly recommend using the docker containers provided below as the dependencies can be complicated to build yourself.

  • hamelsmu/ml-gpu: Use this container for any gpu bound parts of the tutorial. We recommend running the entire tutorial on an aws p3.8xlarge and using this image.

  • hamelsmu/ml-cpu: Use this container for any cpu bound parts of this tutorial.

Notebooks

The notebooks folder contains 5 Jupyter notebooks that correspond to Parts 1-5 of the tutorial.

Related Blog Posts

This tutorial assumes knowledge of the material presented in a previous tutorial on sequence-to-sequence models.


PRs And Comments Are Welcome

We have made best attempts to make sure running this tutorial is as painless as possible. If you think something can be improved, please submit a PR!

About

Code For Medium Article: "How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning"

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 95.4%
  • Python 4.5%
  • Other 0.1%