CogDL v0.4.1
A new release! 🎉🎉🎉
In the new v0.4.1 release, CogDL implements multiple deepgnn models and we also give a analysis of deepgnn in Chinese. Now CogDL. supports both reversible and actnn for memory efficiency to help build super deep GNNs. Come and have a try. BTW, we are glad to announce that we will give a tutorial on KDD 2021 in August. Please see this link for more details. 🎉
New Features
- #230 Add new tasks for OAGBert, including zero-shot inference and supervised classification
- #243 #251 Add new pipelines of GenerateEmbeddingPipeline
- #248 Add recommendation task
- #249 Separate layers from models for users to build custom models more conveniently.
- #256 Add message-passing base framework.
- #262 #263 #266 Supports actnn in graph neural networks
- #266 Add message-passing ops implemented in Python
New Models
- #258 Add c&s(correct and smooth) and SAGN
- #260 #261 Add RevGNN wrappers and models (
revgcn
,revgat
,revgen
)
New Datasets
- #230 Add datasest for OAGBert:
l0fos
,aff30
,arxivvenue
.
New Examples
- #265 Implements HGNN using CogDL.
Bug Fixes
- #237 #240 Fix bugs in calling ge-spmm and using Graph
- #238 Modify examples of gnns to adapt to cogdl.Graph.
- #257 Fix bugs in ogb datasets and moe-gcn
- #259 Fix bugs in calling cusparse API.
Docs
- #242 Add a brief tutorial for CogDL.