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Running
on
Zero
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 '') | |