Release v0.2.3

We are thrilled to announce the release of GraphLearn for PyTorch v0.2.3. This update includes some enhancements focusing on:

• Distributed support for vineyard as an integration with GraphScope.
• Optimizations such as graph caching, and some experimental features including support for bf16 precision and all-to-all communication.
• Some bug fixes.

What's Changed

• IGBH: Add Dockerfile and some minors by @LiSu in #128
• IGBH: adjust mllogger tag position by @LiSu in #130
• Distributed support for v6d GraphScope by @husimplicity in #116
• add graph caching support for distributed training by @kaixuanliu in #132
• add bf16 precision support to utilize Intel's AMX accelerations by @kaixuanliu in #133
• fix: data path for s/c case by @husimplicity in #135
• add all2all support to replace p2p rpc, using gloo as backend temporarily by @kaixuanliu in #134
• Fix table dataset init graph by @husimplicity in #136
• Verify hops as dict with 0 by @husimplicity in #138
• fix: several bugs on distributed mode by @husimplicity in #139
• [fix] explicitly call share_memory_ in Feature in cpu mode by @Zhanghyi in #142
• upgrade pytorch and cuda versions by @Zhanghyi in #141

Full Changelog: v0.2.2...v0.2.3