code: def __init__(self, inc, outc, ks=3, stride=1, dilation=1):
      super().__init__()
      self.net = nn.Sequential(
          spnn.Conv3d(
              inc,
              outc,
              kernel_size=ks,
              dilation=dilation,
              stride=stride,
          ),
          spnn.BatchNorm(outc),
          spnn.ReLU(True),
      )
  
file_path: torch-points3d/torch_points3d/modules/PVCNN/blocks.py
imports: import torch.nn
  import torchsparse.nn
label_desc: Use image node_id 1 to create a new BasicConvolutionBlock object from inherited base classes: nn with example: obj = BasicConvolutionBlock(inc, outc, ks, stride, dilation)