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[graphbolt] skip non-existent types in input_nodes #7386

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merged 4 commits into from
May 9, 2024
Merged

[graphbolt] skip non-existent types in input_nodes #7386

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fad21e9
[graphbolt] skip non-existent types in input_nodes
Rhett-Ying May 9, 2024
6f62d72
rewrite iterate logic
Rhett-Ying May 9, 2024
d85d984
fix lint
Rhett-Ying May 9, 2024
8e580de
fix lint
Rhett-Ying May 9, 2024
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2 changes: 1 addition & 1 deletion python/dgl/graphbolt/feature_fetcher.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def record_stream(tensor):
if self.node_feature_keys and input_nodes is not None:
if is_heterogeneous:
for type_name, feature_names in self.node_feature_keys.items():
nodes = input_nodes[type_name]
nodes = input_nodes.get(type_name, None)
if nodes is None:
continue
if nodes.is_cuda:
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4 changes: 3 additions & 1 deletion tests/python/pytorch/graphbolt/test_feature_fetcher.py
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Expand Up @@ -160,8 +160,10 @@ def test_FeatureFetcher_hetero():
num_layer = 2
fanouts = [torch.LongTensor([2]) for _ in range(num_layer)]
sampler_dp = gb.NeighborSampler(item_sampler, graph, fanouts)
# "n3" is not in the sampled input nodes.
node_feature_keys = {"n1": ["a"], "n2": ["a"], "n3": ["a"]}
fetcher_dp = gb.FeatureFetcher(
sampler_dp, feature_store, {"n1": ["a"], "n2": ["a"]}
sampler_dp, feature_store, node_feature_keys=node_feature_keys
)

assert len(list(fetcher_dp)) == 3
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