code: def __init__(self, part_num=50):
      super(PointTransformerSeg, self).__init__()
      self.part_num = part_num
      self.conv1 = nn.Conv1d(3, 128, kernel_size=1, bias=False)
      self.conv2 = nn.Conv1d(128, 128, kernel_size=1, bias=False)
  
      self.bn1 = nn.BatchNorm1d(128)
      self.bn2 = nn.BatchNorm1d(128)
  
      self.sa1 = SALayerSeg(128)
      self.sa2 = SALayerSeg(128)
      self.sa3 = SALayerSeg(128)
      self.sa4 = SALayerSeg(128)
  
      self.conv_fuse = nn.Sequential(
          nn.Conv1d(512, 1024, kernel_size=1, bias=False),
          nn.BatchNorm1d(1024),
          nn.LeakyReLU(negative_slope=0.2),
      )
  
      self.label_conv = nn.Sequential(
          nn.Conv1d(16, 64, kernel_size=1, bias=False),
          nn.BatchNorm1d(64),
          nn.LeakyReLU(negative_slope=0.2),
      )
  
      self.convs1 = nn.Conv1d(1024 * 3 + 64, 512, 1)
      self.dp1 = nn.Dropout(0.5)
      self.convs2 = nn.Conv1d(512, 256, 1)
      self.convs3 = nn.Conv1d(256, self.part_num, 1)
      self.bns1 = nn.BatchNorm1d(512)
      self.bns2 = nn.BatchNorm1d(256)
  
      self.relu = nn.ReLU()
  
imports: import torch
  from helper import TransitionDown
  from torch import nn
label_desc: Use image node_id 1 to create a new PointTransformerSeg object from inherited base classes: nn with example: obj = PointTransformerSeg(part_num)