ImportError: Cannot load Graphbolt C++ library

[bepisworld]

Yes, I was working with dgl 2.1.0, I think I was using cuda 11.8. I was also using the container image suggested by DGL (DGL | NVIDIA NGC)

[shadow150519]

You can try to install from source. That works for me.

[ybangaru]

In the cpu environment even the DGL 2.0.0 didn’t work for me, I was only able to install 1.1.3 without facing any issues during runtime

here’s my environment.yaml for conda

name: yourenvname
channels:
  - conda-forge
dependencies:
  - python=3.10
  - pytorch
  - pytorch_geometric
  - pytorch_scatter
  - pytorch_sparse
  - dgl=1.1.3

[Rhett-Ying]

Please refer to the install page to install the latest DGL version. As DGL library directly depend on specific torch version, so please make sure DGL and pytorch versions match.

DGL 2.1.0 supports torch 2.0.x, 2.1.x, 2.2.0/1.

[walidgeuttala]

Hi Rhett, could you please help with the error? I haven’t been able to solve it for the last 4 hours. Thank you!

Unique Case of Heterogeneous Graph: Optimizing Representation and Training Strategies

Thank you for your response. I tried to do it using the documentation, but I didn’t get it. I have the demo example. Could you explain what is wrong in the code? class RGCN3(nn.Module): def __init__(self, in_feats, hid_feats, out_feats, rel_names, num_layers = 4, n_heads = 16): super().__init__() self.rel_names = rel_names self.embed_layer = MLP2(in_feats, hid_feats, hid_feats) self.gnn_layers = torch.nn.ModuleList() for _ in range(num_layers): …

[tauChang]

@Tyizhanshen

.

Hi I’m still seeing the same question as OP. Any help is appreciated