Hi Kenko,

Have you successfully solved this problem? I also encountered such situation, then I tried to install torch==2.1.0 and torchdata==0.7.0 while remaining dgl==2.2.1.

It was indeed useful for importing dgl, but when I tried to add edges to graph, a new error would rise: RuntimeError: Could not infer dtype of numpy.int64. Thus, the problem has been bothering me. It will be grateful if you have any new ideas and share them with me.

Best,
Bin

Have you tried with pip install dgl -f https://data.dgl.ai/wheels/torch-2.4/cu124/repo.html? (https://www.dgl.ai/pages/start.html) It contains wheels for dgl 2.4.0 based on pytorch 2.4

@kenko911 Great to see you here. Looks like dgl has their own way to distribute bdist and sdist. I'm not a dgl user at all, but they only ship 2.2.1 wheels for windows only, 2.2.0 wheels for macos only and so on.

For the time being we might need to build from source ourselves, or perhaps we might need to store a pre-built one somewhere as a temporary solution (as the build is pretty costly).

This issue has been automatically marked as stale due to lack of activity. It will be closed if no further activity occurs. Thank you

Have you tried with pip install dgl -f https://data.dgl.ai/wheels/torch-2.4/cu124/repo.html? (https://www.dgl.ai/pages/start.html) It contains wheels for dgl 2.4.0 based on pytorch 2.4

This is great as a solution for individuals, but it makes it very difficult to develop anything with dgl as a dependency, as it's not at all straightforward to specify this in a pyproject.toml file (or similar).

(The build-from-source requirements for MacOS/Windows also makes it unrealistic to run any cross-platform CI that depends on dgl, which is disappointing.)

Could any DGL developers provide comments or insights on this? Thank you!