code: def forward(self, x, y):
      for layer in self.layers:
          x = layer(x)
          y = self.dag_layer(y)
      return x.sum(), y.sum()
  
imports: import argparse
  import os
  import warnings
  import torch
  import torch.distributed.rpc
  import torch.multiprocessing
  from torch import nn
  from torch._C._distributed_rpc import _is_current_rpc_agent_set
  from colossalai.legacy import launch
  from colossalai.legacy.pipeline.pipeline_process_group import ppg
  from colossalai.logging import disable_existing_loggers
label_desc: Use image node_id 2 for calling the DAG_MLP obj's underlying member method code with example usage: obj.forward(x, y) and returns: x,  y