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Since version 2.3, PyG can be installed and used with only raw PyTorch.
Hi, currently, I am using a non-CUDA device. Specifically, a device with Intel Gaudi HPUs.
Gaudi HPUs support PyTorch, and thus, PyG's basic functionalities can be used.
However, when I tried to use Node2Vec, I realized that it requires either pyg_lib or torch_cluster, but both libraries only support CPU or CUDA GPUs.
Similarly, many other functionalities require pyg_lib/torch_sparse/torch_cluster, while those libraries only support CPU and CUDA GPUs.
I am wondering whether there are general workarounds for using such functionalities on non-CUDA devices.
If not, what should I do to make it possible?
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Since version 2.3, PyG can be installed and used with only raw PyTorch.
Hi, currently, I am using a non-CUDA device. Specifically, a device with Intel Gaudi HPUs.
Gaudi HPUs support PyTorch, and thus, PyG's basic functionalities can be used.
However, when I tried to use
Node2Vec
, I realized that it requires eitherpyg_lib
ortorch_cluster
, but both libraries only support CPU or CUDA GPUs.Similarly, many other functionalities require pyg_lib/torch_sparse/torch_cluster, while those libraries only support CPU and CUDA GPUs.
I am wondering whether there are general workarounds for using such functionalities on non-CUDA devices.
If not, what should I do to make it possible?
Thank you for your help in advance.
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