Dgl Ke Versions Save

High performance, easy-to-use, and scalable package for learning large-scale knowledge graph embeddings.

0.1.1

3 years ago

This patch release provides the following features.

Offline inference: https://github.com/awslabs/dgl-ke/pull/103
Reorganize documentation.
Fix bugs:
- #85 , Force user to provide dataset name when using udd or raw_udd. (This avoid set 'FB15k' as dataset name of user defined data.
Minor improvements:
- remove unnecessary eval log: https://github.com/awslabs/dgl-ke/pull/104
- Add check for udd input
- allow users to specify the delimiter

v0.1.0

4 years ago

We are happy to announce the first release of DGL-KE, a lightning-speed package for learning knowledge graph embeddings. DGL-KE was previously incubated under the DGL repository. It is now a standalone package with more efficient and more scalable training. The key highlights are:

Effortlessly generate knowledge graph embedding with one line of code.
Support for giant graphs with millions of nodes and billions of edges for various hardware:
- multi-CPU machines,
- multi-GPU machines,
- a cluster of machines.
Support for both Pytorch and MXNet.