code: def forward(self, x):
      xyz = x[..., :3]
      x = x[..., 3:].permute(0, 2, 1)
      batch_size, _, _ = x.size()
      x = self.relu(self.bn1(self.conv1(x)))  # B, D, N
      x = self.relu(self.bn2(self.conv2(x)))  # B, D, N
      x = x.permute(0, 2, 1)
  
      new_xyz, feature_0 = self.g_op0(xyz, x, n_point=512)
      new_xyz, feature_1 = self.g_op1(new_xyz, feature_0, n_point=256)
  
      # add position embedding on each layer
      x = self.pt_last(feature_1, new_xyz)
  
      x = torch.cat([x, feature_1], dim=1)
      x = self.conv_fuse(x)
      x, _ = torch.max(x, 2)
      x = x.view(batch_size, -1)
  
      x = self.relu(self.bn6(self.linear1(x)))
      x = self.dp1(x)
      x = self.relu(self.bn7(self.linear2(x)))
      x = self.dp2(x)
      x = self.linear3(x)
  
      return x
  
imports: import torch
  from helper import TransitionDown
  from torch import nn
label_desc: Use image node_id 2 for calling the PointTransformerCLS obj's underlying member method code with example usage: obj.forward(x) and returns: x