Dgl

Latest version: v2.1.0

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0.2

Not secure
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Major release that includes many features, bugfix and performance improvement.
Speed of GCN model on Pubmed dataset has been improved by **4.19x**! Speed of
RGCN model on Mutag dataset has been improved by **7.35x**! Important new
feature: **graph sampling APIs**.

Update details:

Model examples
- [x] TreeLSTM w/ MXNet (PR 279 by szha )
- [x] GraphSage (ZiyueHuang )
- [x] Improve GAT model speed (PR 348 by jermainewang )

Core system improvement
- [x] Immutable CSR graph structure (PR 342 by zheng-da )
- [x] Finish remaining functionality (Issue 369, PR 404 by yzh119)
- [x] Nodeflow data structure (PR 361 by zheng-da )
- [x] Neighbor sampler (PR 322 )
- [x] Layer-wise sampler (PR 362 by GaiYu0 )
- [x] Multi-GPU support by data parallelism (PR 356 338 by ylfdq1118 )
- [x] More dataset:
- [x] Reddit dataset loader (PR 372 by ZiyueHuang )
- [x] PPI dataset loader (PR 395 by sufeidechabei )
- [x] Mini graph classification dataset (PR 364 by mufeili )
- [x] NN modules (PR 406 by jermainewang mufeili)
- [x] GraphConv layer
- [x] Edge softmax layer
- [x] Edge group apply API (PR 358 by VoVAllen )
- [x] Reversed graph and transform.py module (PR 331 by mufeili )
- [x] Max readout (PR 341 by mufeili )
- [x] Random walk APIs (PR 392 by BarclayII )

Tutorial/Blog
- [x] Batched graph classification in DGL (PR 360 by mufeili )
- [x] Understanding GAT (sufeidechabei )

Project improvement
- [x] Python lint check (PR 330 by jermainewang )
- [x] Win CI (PR 324 by BarclayII )
- [x] Auto doc build (by VoVAllen )
- [x] Unify tests for different backends (PR 333 by BarclayII )

0.1.3

Not secure
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Bug fix
* Compatible with Pytorch v1.0
* Bug fix in networkx graph conversion.

0.1.2

Not secure
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First open release.
* Basic graph APIs.
* Basic message passing APIs.
* Pytorch backend.
* MXNet backend.
* Optimization using SPMV.
* Model examples w/ Pytorch:
- GCN
- GAT
- JTNN
- DGMG
- Capsule
- LGNN
- RGCN
- Transformer
- TreeLSTM
* Model examples w/ MXNet:
- GCN
- GAT
- RGCN
- SSE

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Releases

Has known vulnerabilities

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