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@BarclayII BarclayII released this 08 Apr 03:22
· 2 commits to 0.6.x since this release
0.6.1
d4a1be3

0.6.1 is a minor release after 0.6.0 that includes some bug fixes, performance optimizations and minor feature updates.

OGB Large-scale Challenge Baselines

This release provides DGL-based baselines for the OGB Large Scale Challenge (https://ogb.stanford.edu/kddcup2021/), specifically the node classification (#2810) and graph classification (#2778) tasks.

For node classification in particular, we additionally provide the preprocessed author and institution features, as well as the homogenized graph for download.

System Support

  • Tensoradapter now supports PyTorch 1.8.1.

Model Updates

Feature Updates

  • dgl.nn.CFConv now supports unidirectional bipartite graphs, hence heterogeneous graphs (#2674)
  • A QM9 Dataset variant with edge features (#2704 and #2801, credits to @hengruizhang98 and @milesial)
  • Display error messages instead of error codes for TCP sockets (#2763)
  • Add the ability of specifying the starting point for farthest point sampler (#2755, credits to @lygztq)
  • Remove the specification of number of workers and servers in distributed training code and move them to launch script (#2775)

Performance Optimizations

  • Optimize the order between message passing and feature transformation in GraphSAGE (#2747)
  • Remove duplicate validation in dgl.graph creation (#2789)
  • Replacing uniform integer sampling from std::unordered_set to linear search (#2710, credits to @pawelpiotrowicz)
  • Automatically setting the number of OMP threads for distributed trainers (#2812)
  • Prefer parallelized conversion to CSC from COO instead of transposing CSR (#2793)

Bug Fixes

  • Prevents symbol collision of CUB with other libraries and removes thrust dependency (#2758, credits to @nv-dlasalle)
  • Temporarily disabling CPU FP16 support due to incomplete code (#2783)
  • GraphSAGE on graphs with zero edges produces NaNs (#2786, credits to @drsealks)
  • Improvements of DiffPool example (#2730, credits to @lygztq)
  • RGCN Link Prediction example sometimes runs beyond given number of epochs (#2757, credits to @turoger)
  • Add pseudo code for dgl.nn.HeteroGraphConv to demonstrate how it works (#2729)
  • The number of negative edges should be the same as positive edges (#2726, credits to @fang2hou)
  • Fix dgl.nn.HeteroGraphConv that cannot be pickled (#2761)
  • Add a default value for dgl.dataloading.BlockSampler (#2771, credits to @hengruizhang98)
  • Update num_labels to num_classes in datasets (#2769, credits to @andyxukq)
  • Remove unused and undefined function in SEAL example (#2791, credits to @ghk829)
  • Fix HGT example where relation-specific value tensors are overwritten (#2796)
  • Cleanup the process pool correctly when the process exits in distributed training (#2781)
  • Fix feature type of ENZYMES in TUDataset (#2800)
  • Documentation fixes (#2708, #2721, #2750, #2754, #2744, #2784, #2816, #2817, #2819, credits to @Padarn, @maqy1995, @Michael1015198808, @HuangLED, @xiamr, etc.)
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