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)