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- import decagon_pytorch.normalize
- import decagon.deep.minibatch
- import numpy as np
-
-
- def test_normalize_adjacency_matrix_square():
- mx = np.random.rand(10, 10)
- mx[mx < .5] = 0
- mx = np.ceil(mx)
- res_torch = decagon_pytorch.normalize.normalize_adjacency_matrix(mx)
- res_tf = decagon.deep.minibatch.EdgeMinibatchIterator.preprocess_graph(None, mx)
- assert len(res_torch) == len(res_tf)
- for i in range(len(res_torch)):
- assert np.all(res_torch[i] == res_tf[i])
-
-
- def test_normalize_adjacency_matrix_nonsquare():
- mx = np.random.rand(5, 10)
- mx[mx < .5] = 0
- mx = np.ceil(mx)
- res_torch = decagon_pytorch.normalize.normalize_adjacency_matrix(mx)
- res_tf = decagon.deep.minibatch.EdgeMinibatchIterator.preprocess_graph(None, mx)
- assert len(res_torch) == len(res_tf)
- for i in range(len(res_torch)):
- assert np.all(res_torch[i] == res_tf[i])
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