Source code for torch_lattice.nn.modules.crop
from typing import Optional, Tuple
from torch import nn
from torch_lattice import SparseTensor
from torch_lattice.nn import functional as F
__all__ = ["SparseCrop"]
[docs]
class SparseCrop(nn.Module):
def __init__(
self,
coords_min: Optional[Tuple[int, ...]] = None,
coords_max: Optional[Tuple[int, ...]] = None,
) -> None:
super().__init__()
self.coords_min = coords_min
self.coords_max = coords_max
[docs]
def forward(self, input: SparseTensor) -> SparseTensor:
return F.spcrop(input, self.coords_min, self.coords_max)