code: def __init__(self, device, aabb, alpha_volume):
      super(AlphaGridMask, self).__init__()
      self.device = device
  
      self.aabb = aabb.to(self.device)
      self.aabbSize = self.aabb[1] - self.aabb[0]
      self.invgridSize = 1.0 / self.aabbSize * 2
      self.alpha_volume = alpha_volume.view(
          1, 1, *alpha_volume.shape[-3:]
      )
      self.gridSize = torch.LongTensor(
          [
              alpha_volume.shape[-1],
              alpha_volume.shape[-2],
              alpha_volume.shape[-3],
          ]
      ).to(self.device)
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .sh import eval_sh_bases
  import numpy
  import time
label_desc: Use image node_id 1 to create a new AlphaGridMask object from inherited base classes: torch.nn with example: obj = AlphaGridMask(device, aabb, alpha_volume)