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import torch
from torch_sparse import SparseTensor, sample, sample_adj
def test_sample():
row = torch.tensor([0, 0, 2, 2])
col = torch.tensor([1, 2, 0, 1])
adj = SparseTensor(row=row, col=col, sparse_sizes=(3, 3))
out = sample(adj, num_neighbors=1)
assert out.min() >= 0 and out.max() <= 2
def test_sample_adj():
row = torch.tensor([0, 0, 0, 1, 1, 2, 2, 2, 2, 3, 4, 4, 5, 5])
col = torch.tensor([1, 2, 3, 0, 2, 0, 1, 4, 5, 0, 2, 5, 2, 4])
value = torch.arange(row.size(0))
adj_t = SparseTensor(row=row, col=col, value=value, sparse_sizes=(6, 6))
out, n_id = sample_adj(adj_t, torch.arange(2, 6), num_neighbors=-1)
assert n_id.tolist() == [2, 3, 4, 5, 0, 1]
row, col, val = out.coo()
assert row.tolist() == [0, 0, 0, 0, 1, 2, 2, 3, 3]
assert col.tolist() == [2, 3, 4, 5, 4, 0, 3, 0, 2]
assert val.tolist() == [7, 8, 5, 6, 9, 10, 11, 12, 13]
out, n_id = sample_adj(adj_t, torch.arange(2, 6), num_neighbors=2,
replace=True)
assert out.nnz() == 8
out, n_id = sample_adj(adj_t, torch.arange(2, 6), num_neighbors=2,
replace=False)
assert out.nnz() == 7 # node 3 has only one edge...
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