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Describe the bug
Nodes are missing after sampling graph nodes without duplicates.
To Reproduce
Steps to reproduce the behavior:
Loading data for heterogeneous graph.
Neighborhood query for user nodes of heterogeneous graph using “Query” function, then feature stitching using function. And then we get “train_loader”.
Load the weights of the trained embedding model and perform the embedding operation on the “train_loader” based on all user nodes.
Outputs the “inputs”,“emb”, and “outputs” of the embedding model.
Expected behavior
The number of user nodes in the “inputs”, “emb”, and “outputs” of the embedding model should be the same as in the original graph.
Screenshots
Environment (please complete the following information):
GraphScope version: [e.g., v0.25]
OS: [e.g. Linux]
Version [Ubuntu 22.04(Jammy Jellyfish)]
Kubernetes Version [e.g., v3.3.0]
Additional context
The missing 5 user nodes have neighbors and are not duplicate nodes
The text was updated successfully, but these errors were encountered:
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Describe the bug
Nodes are missing after sampling graph nodes without duplicates.
To Reproduce
Steps to reproduce the behavior:
Expected behavior
The number of user nodes in the “inputs”, “emb”, and “outputs” of the embedding model should be the same as in the original graph.
Screenshots
Environment (please complete the following information):
Additional context
The missing 5 user nodes have neighbors and are not duplicate nodes
The text was updated successfully, but these errors were encountered: