code: def forward(self, x):
      for i in range(len(self.stages)):
          x = self.downsample_layers[i](x)
          x = self.stages[i](x)
      x = x.mean([-2, -1])
      x = self.head(x)
      return x
  
imports: import os
  import time
  import torch
  import torch.distributed
  import torch.multiprocessing
  import torch.nn
  from torch.distributed._tensor import DeviceMesh, distribute_module, distribute_tensor, Replicate, Shard
label_desc: Use image node_id 2 for calling the ConvNeXt obj's underlying member method code with example usage: obj.forward(x) and returns: x