46 lines
1.4 KiB
Python
Executable file
46 lines
1.4 KiB
Python
Executable file
import emd_cuda
|
|
import torch
|
|
|
|
|
|
class EarthMoverDistanceFunction(torch.autograd.Function):
|
|
@staticmethod
|
|
def forward(ctx, xyz1, xyz2):
|
|
xyz1 = xyz1.contiguous()
|
|
xyz2 = xyz2.contiguous()
|
|
assert xyz1.is_cuda and xyz2.is_cuda, "Only support cuda currently."
|
|
match = emd_cuda.approxmatch_forward(xyz1, xyz2)
|
|
cost = emd_cuda.matchcost_forward(xyz1, xyz2, match)
|
|
ctx.save_for_backward(xyz1, xyz2, match)
|
|
return cost
|
|
|
|
@staticmethod
|
|
def backward(ctx, grad_cost):
|
|
xyz1, xyz2, match = ctx.saved_tensors
|
|
grad_cost = grad_cost.contiguous()
|
|
grad_xyz1, grad_xyz2 = emd_cuda.matchcost_backward(grad_cost, xyz1, xyz2, match)
|
|
return grad_xyz1, grad_xyz2
|
|
|
|
|
|
def earth_mover_distance(xyz1, xyz2, transpose=True):
|
|
"""Earth Mover Distance (Approx)
|
|
|
|
Args:
|
|
xyz1 (torch.Tensor): (b, 3, n1)
|
|
xyz2 (torch.Tensor): (b, 3, n1)
|
|
transpose (bool): whether to transpose inputs as it might be BCN format.
|
|
Extensions only support BNC format.
|
|
|
|
Returns:
|
|
cost (torch.Tensor): (b)
|
|
|
|
"""
|
|
if xyz1.dim() == 2:
|
|
xyz1 = xyz1.unsqueeze(0)
|
|
if xyz2.dim() == 2:
|
|
xyz2 = xyz2.unsqueeze(0)
|
|
if transpose:
|
|
xyz1 = xyz1.transpose(1, 2)
|
|
xyz2 = xyz2.transpose(1, 2)
|
|
cost = EarthMoverDistanceFunction.apply(xyz1, xyz2)
|
|
return cost
|