code: def weight_initialization(self):
      for m in self.modules():
          if isinstance(m, nn.BatchNorm1d):
              nn.init.constant_(m.weight, 1)
              nn.init.constant_(m.bias, 0)
  
file_path: torch-points3d/torch_points3d/modules/PVCNN/pvcnn.py
imports: import torch.nn
  import torchsparse
  import torchsparse.nn
  import torchsparse.nn.functional
  from torchsparse.sparse_tensor import SparseTensor
  from torchsparse.point_tensor import PointTensor
  from torchsparse.utils.kernel_region import *
  from torchsparse.utils.helpers import *
  from torch_points3d.modules.PVCNN.blocks import *
  from torch_points3d.modules.PVCNN.utils import *
label_desc: Use image node_id 2 for calling the PVCNN obj's underlying member method code with example usage: obj.weight_initialization() without return types