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test_radius.py 2.21 KB
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from itertools import product

import pytest
import torch
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import scipy.spatial
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from torch_cluster import radius, radius_graph
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from .utils import grad_dtypes, devices, tensor
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def to_set(edge_index):
    return set([(i, j) for i, j in edge_index.t().tolist()])


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@pytest.mark.parametrize('dtype,device', product(grad_dtypes, devices))
def test_radius(dtype, device):
    x = tensor([
        [-1, -1],
        [-1, +1],
        [+1, +1],
        [+1, -1],
        [-1, -1],
        [-1, +1],
        [+1, +1],
        [+1, -1],
    ], dtype, device)
    y = tensor([
        [0, 0],
        [0, 1],
    ], dtype, device)

    batch_x = tensor([0, 0, 0, 0, 1, 1, 1, 1], torch.long, device)
    batch_y = tensor([0, 1], torch.long, device)

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    edge_index = radius(x, y, 2, max_num_neighbors=4)
    assert to_set(edge_index) == set([(0, 0), (0, 1), (0, 2), (0, 3), (1, 1),
                                      (1, 2), (1, 5), (1, 6)])
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    edge_index = radius(x, y, 2, batch_x, batch_y, max_num_neighbors=4)
    assert to_set(edge_index) == set([(0, 0), (0, 1), (0, 2), (0, 3), (1, 5),
                                      (1, 6)])
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@pytest.mark.parametrize('dtype,device', product(grad_dtypes, devices))
def test_radius_graph(dtype, device):
    x = tensor([
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        [-1, -1],
        [-1, +1],
        [+1, +1],
        [+1, -1],
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    ], dtype, device)

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    edge_index = radius_graph(x, r=2, flow='target_to_source')
    assert to_set(edge_index) == set([(0, 1), (0, 3), (1, 0), (1, 2), (2, 1),
                                      (2, 3), (3, 0), (3, 2)])
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    edge_index = radius_graph(x, r=2, flow='source_to_target')
    assert to_set(edge_index) == set([(1, 0), (3, 0), (0, 1), (2, 1), (1, 2),
                                      (3, 2), (0, 3), (2, 3)])
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@pytest.mark.parametrize('dtype,device', product(grad_dtypes, devices))
def test_radius_graph_large(dtype, device):
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    x = torch.randn(1000, 3)
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    edge_index = radius_graph(x, r=0.5, flow='target_to_source', loop=True,
                              max_num_neighbors=1000, num_workers=6)
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    tree = scipy.spatial.cKDTree(x.numpy())
    col = tree.query_ball_point(x.cpu(), r=0.5)
    truth = set([(i, j) for i, ns in enumerate(col) for j in ns])
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    assert to_set(edge_index) == truth