You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
We continue to have issues with PyTorch in this repository's CI. In addition, the code that depends on PyTorch is really only used by cuGraph-GNN and does not really fit the mission of this repository. As discussed over the past few months, we want to migrate as much GNN code as possible to the cugraph-gnn repository.
There are three key pieces of code affected:
The FeatureStore class which is about to be deprecated (in release 25.02)
The BulkSampler class which is also about to be deprecated (in release 25.02)
The DistSampler class, the replacement for BulkSampler, which is a fundamental piece of our GNN infrastructure.
There is also going to be some additional code in the very near future supporting GNN use cases related to GraphRAG, graph databases, and other frameworks (beyond DGL and PyG). This would also better fit within cugraph-gnn.
We propose creating a new package, pylibcugraphgnn, which will contain the bulk sampling code, as well as any other framework-agnostic code and/or thin wrappers around our C++ code for GNN operations. This package will presumably launch with release 25.04.
The text was updated successfully, but these errors were encountered:
We continue to have issues with PyTorch in this repository's CI. In addition, the code that depends on PyTorch is really only used by cuGraph-GNN and does not really fit the mission of this repository. As discussed over the past few months, we want to migrate as much GNN code as possible to the
cugraph-gnn
repository.There are three key pieces of code affected:
FeatureStore
class which is about to be deprecated (in release 25.02)BulkSampler
class which is also about to be deprecated (in release 25.02)DistSampler
class, the replacement forBulkSampler
, which is a fundamental piece of our GNN infrastructure.There is also going to be some additional code in the very near future supporting GNN use cases related to GraphRAG, graph databases, and other frameworks (beyond DGL and PyG). This would also better fit within
cugraph-gnn
.We propose creating a new package,
pylibcugraphgnn
, which will contain the bulk sampling code, as well as any other framework-agnostic code and/or thin wrappers around our C++ code for GNN operations. This package will presumably launch with release 25.04.The text was updated successfully, but these errors were encountered: