code: def forward(self, x):
      for i in range(self.num_layers):
          i_layer = self.control_str[i]
          if i_layer == "N":
              x = self.layers[i](x.permute(0, 2, 3, 1)).permute(
                  0, 3, 1, 2
              )
          else:
              x = self.layers[i](x)
      return self.output(x)
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.nn.init
  from dgl.nn.pytorch import GraphConv
  from dgl.nn.pytorch.conv import ChebConv
label_desc: Use image node_id 2 for calling the STGCN_WAVE obj's underlying member method code with example usage: obj.forward(x) and returns: self