code: def forward(self, x):
      output = self._norm(x)
      return output * self.weight
  
imports: import copy
  import sys
  from collections import OrderedDict
  from typing import Dict, List, Optional, Tuple
  import torch
  from torch import distributed
  from torch.distributed._tensor import DeviceMesh, distribute_module, DTensor, init_device_mesh, Replicate, Shard
  from torch.distributed._tensor.debug import CommDebugMode
  from torch.distributed.fsdp.fully_sharded_data_parallel import CPUOffload, FullyShardedDataParallel
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, RowwiseParallel
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_fsdp import FSDPTest
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests, TEST_WITH_DEV_DBG_ASAN
  from torch.testing._internal.distributed._tensor.common_dtensor import MLPModule
label_desc: Use image node_id 3 for calling the RMSNormPython obj's underlying member method code with example usage: obj.forward(x) and returns: unknown