code: def forward(self, x):
      if x.shape[-1] > 3:
          pos = x[:, :, :3]
          feat = x[:, :, 3:]
      else:
          pos = x
          feat = None
      pos, feat = self.sa_module1(pos, feat)
      pos, feat = self.sa_module2(pos, feat)
      _, h = self.sa_module3(pos, feat)
  
      h = self.mlp1(h)
      h = self.bn1(h)
      h = F.relu(h)
      h = self.drop1(h)
      h = self.mlp2(h)
      h = self.bn2(h)
      h = F.relu(h)
      h = self.drop2(h)
  
      out = self.mlp_out(h)
      return out
  
imports: import dgl
  import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.geometry import farthest_point_sampler
  from torch.autograd import Variable
label_desc: Use image node_id 2 for calling the PointNet2SSGCls obj's underlying member method code with example usage: obj.forward(x) and returns: out