docstr: 1x1 convolution on point cloud (we can even call it a mini pointnet)
docstr_tok: ["1x1","convolution","on","point","cloud","(","we","can","even","call","it","a","mini","pointnet",")"]
code: def __init__(self, kernel_shape):
      """
      1x1 convolution on point cloud (we can even call it a mini pointnet)
      """
      super(UnaryConv, self).__init__()
      self.weight = Parameter(weight_variable(kernel_shape))
  
imports: import numpy
  import torch
  from torch import nn
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 1 to create a new UnaryConv object from inherited base classes: BaseModule with example: obj = UnaryConv(kernel_shape)