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46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
import math
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import unittest
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import backend as F
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import dgl
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from utils import parametrize_idtype
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@unittest.skipIf(
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dgl.backend.backend_name != "pytorch", reason="Only support PyTorch for now"
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)
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@parametrize_idtype
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def test_edge_label_informativeness(idtype):
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# IfChangeThenChange: python/dgl/label_informativeness.py
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# Update the docstring example.
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device = F.ctx()
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graph = dgl.graph(
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([0, 1, 2, 2, 3, 4], [1, 2, 0, 3, 4, 5]), idtype=idtype, device=device
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)
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y = F.tensor([0, 0, 0, 0, 1, 1])
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assert math.isclose(
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dgl.edge_label_informativeness(graph, y),
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0.25177597999572754,
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abs_tol=1e-6,
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)
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@unittest.skipIf(
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dgl.backend.backend_name != "pytorch", reason="Only support PyTorch for now"
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)
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@parametrize_idtype
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def test_node_label_informativeness(idtype):
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# IfChangeThenChange: python/dgl/label_informativeness.py
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# Update the docstring example.
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device = F.ctx()
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graph = dgl.graph(
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([0, 1, 2, 2, 3, 4], [1, 2, 0, 3, 4, 5]), idtype=idtype, device=device
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)
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y = F.tensor([0, 0, 0, 0, 1, 1])
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assert math.isclose(
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dgl.node_label_informativeness(graph, y),
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0.3381872773170471,
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abs_tol=1e-6,
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)
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