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| from torch.autograd import Function | |
| from .backend import _backend | |
| __all__ = ['ball_query'] | |
| def ball_query(centers_coords, points_coords, radius, num_neighbors): | |
| """ | |
| :param centers_coords: coordinates of centers, FloatTensor[B, 3, M] | |
| :param points_coords: coordinates of points, FloatTensor[B, 3, N] | |
| :param radius: float, radius of ball query | |
| :param num_neighbors: int, maximum number of neighbors | |
| :return: | |
| neighbor_indices: indices of neighbors, IntTensor[B, M, U] | |
| """ | |
| centers_coords = centers_coords.contiguous() | |
| points_coords = points_coords.contiguous() | |
| return _backend.ball_query(centers_coords, points_coords, radius, num_neighbors) | |