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