Bump dgl from 1.0.1 to 1.1.2.post1 #122

dependabot · 2023-08-30T09:49:50Z

Bumps dgl from 1.0.1 to 1.1.2.post1.

Release notes

v1.1.2

Major changes

PyTorch 1.12.0, 1.12.1 are deprecated and the supported versions are 1.13.0, 1.13.1, 2.0.0, 2.0.1.

CUDA 10.2, 11.3 are deprecated and the supported versions are 11.6, 11.7. 11.8.

C++ standard used in build is upgraded to 17.

Several performance improvements such as #5885, #5924 and so on.

Multiple examples are updated for better readability such as #6035, #6036 and so on.

A few bug fixes such as #6044, #6001 and so on.

v1.1.1

What's new

Add support for PyTorch 2.0.1.

Fix several bugs such as #5872 for DistDGL, #5754 for dgl.khop_daj() and so on.

Remove several unused third-party libraries such as xbyak, tvm.

A few performance improvements such as #5508, #5685.

v1.1.0

What's new

Sparse API improvement

Datasets for evaluating graph transformers and graph learning under heterophily

Modules and utilities, including Cugraph convolution modules and SubgraphX

Graph transformer deprecation

Performance improvement

Extended BF16 data type to support 4th Generation Intel® Xeon® Scalable Processors [(#5497](dmlc/dgl#5497))

Detailed breakdown

Sparse API improvement (@czkkkkkk )

SparseMatrix class

Merge DiagMatrix class into SparseMatrix class, where the diagonal matrix is stored as a sparse matrix and inherits all the operators from sparse matrix. (#5367)

Support converting DGLGraph to SparseMatrix.g.adj(self, etype=None, eweight_name=None) returns the sparse matrix representation of the DGL graph g on the edge type etype and edge weight eweight_name. (#5372)

Enable zero-overhead conversion between Pytorch sparse tensors and SparseMatrix via dgl.sparse.to_torch_sparse_coo/csr/csc and dgl.sparse.from_torch_sparse. (#5373)

SparseMatrix operators

Support element-wise multiplication on two sparse matrices with different sparsities, e.g., A * B. (#5368)

Support element-wise division on two sparse matrices with the same sparsity, e.g., A / B. (#5369)

Support broadcast operators on a sparse matrix and a 1-D tensor via dgl.sparse.broadcast_add/sub/mul/div. (#5370)

Support column-wise softmax. (#5371)

SparseMatrix examples

Example for Heterogeneous Graph Attention Networks (#5568, @mufeili )

Datasets

... (truncated)

Commits

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Bumps [dgl](https://github.com/dmlc/dgl) from 1.0.1 to 1.1.2.post1. - [Release notes](https://github.com/dmlc/dgl/releases) - [Changelog](https://github.com/dmlc/dgl/blob/master/NEWS.md) - [Commits](https://github.com/dmlc/dgl/commits) --- updated-dependencies: - dependency-name: dgl dependency-type: direct:production update-type: version-update:semver-minor ... Signed-off-by: dependabot[bot] <[email protected]>