46 lines
1.3 KiB
Python
46 lines
1.3 KiB
Python
import torch
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from torch.autograd import Function
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from typing import Tuple
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from . import interpolate_ext
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class ThreeNN(Function):
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@staticmethod
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def forward(
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ctx, target: torch.Tensor, source: torch.Tensor
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) -> Tuple[torch.Tensor, torch.Tensor]:
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"""Find the top-3 nearest neighbors of the target set from the source
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set.
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Args:
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target (Tensor): shape (B, N, 3), points set that needs to
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find the nearest neighbors.
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source (Tensor): shape (B, M, 3), points set that is used
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to find the nearest neighbors of points in target set.
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Returns:
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Tensor: shape (B, N, 3), L2 distance of each point in target
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set to their corresponding nearest neighbors.
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"""
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assert target.is_contiguous()
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assert source.is_contiguous()
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B, N, _ = target.size()
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m = source.size(1)
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dist2 = torch.cuda.FloatTensor(B, N, 3)
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idx = torch.cuda.IntTensor(B, N, 3)
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interpolate_ext.three_nn_wrapper(B, N, m, target, source, dist2, idx)
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ctx.mark_non_differentiable(idx)
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return torch.sqrt(dist2), idx
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@staticmethod
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def backward(ctx, a=None, b=None):
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return None, None
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three_nn = ThreeNN.apply
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