def upsample(self, x, n1=1, n2=0):
"""Upsample mesh."""
if x.ndimension() < 3:
for i in reversed(range(n2, n1)):
x = spmm(self._U[i], x)
elif x.ndimension() == 3:
out = []
for i in range(x.shape[0]):
y = x[i]
for j in reversed(range(n2, n1)):
y = spmm(self._U[j], y)
out.append(y)
x = torch.stack(out, dim=0)
return x
def downsample(self, x, n1=0, n2=None):
"""Downsample mesh."""
if n2 is None:
n2 = self.num_downsampling
if x.ndimension() < 3:
for i in range(n1, n2):
x = spmm(self._D[i], x)
elif x.ndimension() == 3:
out = []
for i in range(x.shape[0]):
y = x[i]
for j in range(n1, n2):
y = spmm(self._D[j], y)
out.append(y)
x = torch.stack(out, dim=0)
return x