code: def __init__(self, sampler, neighbour_finder, *args, **kwargs):
      super(BasePartialDenseConvolutionDown, self).__init__(
          sampler, neighbour_finder, *args, **kwargs
      )
  
      self._index = kwargs.get("index", None)
  
imports: from typing import *
  import torch
  from torch.nn import Linear, ReLU, LeakyReLU, BatchNorm1d, Dropout
  from torch_geometric.nn import knn_interpolate, fps, radius, global_max_pool, global_mean_pool, knn
  from torch_geometric.data import Batch
  from torch_points3d.core.spatial_ops import *
  from .base_conv import BaseConvolution
  from torch_points3d.core.common_modules.base_modules import BaseModule
  from torch_points3d.core.common_modules import MLP
label_desc: Use image node_id 1 to create a new BasePartialDenseConvolutionDown object from inherited base classes: BaseConvolution with example: obj = BasePartialDenseConvolutionDown(sampler, neighbour_finder)