code: def __init__(self, inc, outc, ks=3, stride=1):
      super().__init__()
      self.net = nn.Sequential(
          spnn.Conv3d(
              inc, outc, kernel_size=ks, stride=stride, transpose=True
          ),
          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 BasicDeconvolutionBlock object from inherited base classes: nn with example: obj = BasicDeconvolutionBlock(inc, outc, ks, stride)