test_radius.py

from itertools import product

import pytest
import torch
from torch_cluster import radius

from .utils import tensor

devices = [torch.device('cuda')]
grad_dtypes = [torch.float]


@pytest.mark.skipif(not torch.cuda.is_available(), reason='CUDA not available')
@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)

    out = radius(x, y, 2, batch_x, batch_y, max_num_neighbors=4)
    print()
    print([[0, 0, 0, 0, 1, 1], [0, 1, 2, 3, 5, 6]])
    print(out)