code: def test_dynamo_dtensor_from_local(self):
      mesh = DeviceMesh(self.device_type, torch.arange(self.world_size))
  
      # create DTensor inside fn and run some compute
      def fn(x):
          dt = DTensor.from_local(
              x, mesh, [Replicate()], run_check=False
          )
          return dt.to_local() + 2
  
      # below is the op approach for reference
      # from torch.distributed._tensor.api import _FromTorchTensor
      # def from_local_tensor(x):
      #     return _FromTorchTensor.apply(x, mesh, [Replicate()], False)
  
      # _dt_lib_def = torch.library.Library("dtensor", "DEF")
      # _dt_lib_def.define("from_local(Tensor self) -> Tensor")
  
      # _dt_lib_impl = torch.library.Library("dtensor", "IMPL")
      # _dt_lib_impl.impl("from_local", from_local_tensor, "Autograd")
  
      x = torch.ones(1)
      ref = fn(x)
      opt_fn = torch.compile(fn, backend="aot_eager", fullgraph=True)
      res = opt_fn(x)
      self.assertEqual(res, ref)
  
      # test if user calls from_local with mesh/placements as kwargs and that should still work
      def from_local_kwargs_fn(x):
          dt = DTensor.from_local(
              x,
              device_mesh=mesh,
              placements=[Replicate()],
              run_check=False,
          )
          return dt.to_local() + 2
  
      ref = from_local_kwargs_fn(x)
      opt_kwargs_fn = torch.compile(
          from_local_kwargs_fn, backend="aot_eager", fullgraph=True
      )
      res = opt_kwargs_fn(x)
      self.assertEqual(res, ref)
  
imports: import copy
  import functools
  import unittest
  from unittest.mock import patch
  import torch
  import torch._dynamo
  import torch.distributed
  import torch.nn
  from torch._C import FileCheck
  from torch._inductor.utils import run_and_get_triton_code
  from torch.distributed._tensor import DeviceMesh, DTensor, init_device_mesh, Replicate, Shard
  from torch.distributed.algorithms._checkpoint.checkpoint_wrapper import checkpoint_wrapper, CheckpointImpl
  from torch.distributed.fsdp import FullyShardedDataParallel
  from torch.distributed.tensor.parallel import ColwiseParallel, parallelize_module, PrepareModuleInput, PrepareModuleOutput, RowwiseParallel
  from torch.testing._internal.common_distributed import skip_if_lt_x_gpu
  from torch.testing._internal.common_utils import instantiate_parametrized_tests, parametrize, run_tests
  from torch.testing._internal.distributed._tensor.common_dtensor import DTensorTestBase, MLPModule, with_comms
  from torch.testing._internal.distributed.fake_pg import FakeStore
  from torch.utils._triton import has_triton
  from torch.utils.checkpoint import checkpoint
  from functorch.compile import min_cut_rematerialization_partition
  from torch._dynamo.backends.common import aot_autograd
label_desc: Use image node_id 7 for calling the TestDTensorCompile obj's underlying member method code with example usage: obj.test_dynamo_dtensor_from_local() and returns: unknown, unknown