code: def __init__(self, K=None, D=None, C1=None, C2=None, *args, **kwargs):
      super(PointCNNConvUp, self).__init__(
          DilatedKNNNeighbourFinder(K, D)
      )
  
      self._conv = XConv(C1, C2, 3, K)
  
imports: from math import ceil
  import torch
  from torch.nn import Sequential, Linear, BatchNorm1d
  from torch.nn import ELU, Conv1d
  from torch_geometric.nn import Reshape
  from torch_geometric.nn.inits import reset
  from torch_points3d.core.spatial_ops import RandomSampler, FPSSampler, DilatedKNNNeighbourFinder
  from torch_points3d.core.base_conv.message_passing import *
label_desc: Use image node_id 1 to create a new PointCNNConvUp object from inherited base classes: BaseConvolutionUp with example: obj = PointCNNConvUp(K, D, C1, C2)