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import torch
import torch.nn as nn
from . import functional as F
__all__ = ['BallQuery']
class BallQuery(nn.Module):
def __init__(self, radius, num_neighbors, include_coordinates=True):
super().__init__()
self.radius = radius
self.num_neighbors = num_neighbors
self.include_coordinates = include_coordinates
def forward(self, points_coords, centers_coords, points_features=None):
points_coords = points_coords.contiguous()
centers_coords = centers_coords.contiguous()
neighbor_indices = F.ball_query(centers_coords, points_coords, self.radius, self.num_neighbors)
neighbor_coordinates = F.grouping(points_coords, neighbor_indices)
neighbor_coordinates = neighbor_coordinates - centers_coords.unsqueeze(-1)
if points_features is None:
assert self.include_coordinates, 'No Features For Grouping'
neighbor_features = neighbor_coordinates
else:
neighbor_features = F.grouping(points_features, neighbor_indices)
if self.include_coordinates:
neighbor_features = torch.cat([neighbor_coordinates, neighbor_features], dim=1)
return neighbor_features
def extra_repr(self):
return 'radius={}, num_neighbors={}{}'.format(
self.radius, self.num_neighbors, ', include coordinates' if self.include_coordinates else '')
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