Add sampled input to DistNeighborSampler._sample_from_nodes#160
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kmontemayor2-sc wants to merge 2 commits intoalibaba:mainfrom
Open
Add sampled input to DistNeighborSampler._sample_from_nodes#160kmontemayor2-sc wants to merge 2 commits intoalibaba:mainfrom
kmontemayor2-sc wants to merge 2 commits intoalibaba:mainfrom
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kmontemayor2-sc
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May 5, 2025
| if edge_dir == 'out': | ||
| data[res_edge_type]['edge_label_index'] = \ | ||
| torch.stack((v[1], v[0]), dim=0) | ||
| if isinstance(input_type, tuple): |
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Making this change as input_type can also be a NodeType or None, both of which will throw if passed into reverse_edge_type.
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I want to do this as I'd like to be able to maintain a full copy of the inputs to the sampling function - and AFAICT we do not currently store this anywhere.
My usecase here is that I have some specially constructed tensor which contains labels to sample against, and I'd like to be able to identify the "label nodes".
The tensor looks something like:
[<src_node>, <padding>, <positive_labels>, ...], and since this.nodeand.batchget deduped somewhere (idk where) I cannot reconstruct the labels per src node otherwise.