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import torch
from torch_geometric.data import Data, HeteroData
from torch_geometric.transforms import NormalizeFeatures
def test_normalize_scale():
transform = NormalizeFeatures()
assert str(transform) == 'NormalizeFeatures()'
x = torch.tensor([[1, 0, 1], [0, 1, 0], [0, 0, 0]], dtype=torch.float)
data = Data(x=x)
data = transform(data)
assert len(data) == 1
assert data.x.tolist() == [[0.5, 0, 0.5], [0, 1, 0], [0, 0, 0]]
def test_hetero_normalize_scale():
x = torch.tensor([[1, 0, 1], [0, 1, 0], [0, 0, 0]], dtype=torch.float)
data = HeteroData()
data['v'].x = x
data['w'].x = x
data = NormalizeFeatures()(data)
assert data['v'].x.tolist() == [[0.5, 0, 0.5], [0, 1, 0], [0, 0, 0]]
assert data['w'].x.tolist() == [[0.5, 0, 0.5], [0, 1, 0], [0, 0, 0]]
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