Enable Constructing DGraph with TimeDelta as String - #75
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Power users should still use TimeDelta, say they want 6 months as a time granularity. Agree that this is more intuitive for normal use. |
shenyangHuang
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Jul 1, 2025
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PR is approved, let's discuss how to iterate over fixed number of edges even for non-r time granularities
| train_dg = DGraph(args.dataset, time_delta=TimeDeltaDG('r'), split='train') | ||
| val_dg = DGraph(args.dataset, time_delta=TimeDeltaDG('r'), split='val') | ||
| test_dg = DGraph(args.dataset, time_delta=TimeDeltaDG('r'), split='test') | ||
| train_dg = DGraph(args.dataset, split='train') |
| edge_timestamps = torch.LongTensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) | ||
| data = DGData.from_raw(edge_timestamps, edge_index) | ||
| dg = DGraph(data, time_delta=TimeDeltaDG('s')) | ||
| dg = DGraph(data, time_delta='s') |
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can we still iterate by 200 edges when we have a 's' granularity?
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this PR is fine, but this point we can discuss at meeting
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Purpose
The purpose of this PR is to enable users to construct a
DGraphwith thetime_deltaas a string:which seems like a nice usability feature. User never has to know about
TimeDeltaDGanymore.Key Changes
DGraphconstructor to accept string optionRelevant Prs
Close #72