code: def _to_real_tensor(tensor: FakeTensor) -> torch.Tensor:
      if tensor.is_sparse:
          raise ValueError("sparse tensor is not yet supported.")
      out = torch.empty(
          tensor.size(), dtype=tensor.dtype, device=tensor.device
      )
      return out
  
imports: import dataclasses
  import importlib
  import logging
  from typing import Any, Dict, Final, List, Mapping, Optional, Sequence, Set, Tuple, Union
  from typing_extensions import TypeAlias
  import torch
  import torch._C
  import torch._ops
  import torch._prims.executor
  import torch.fx
  from torch._subclasses.fake_tensor import FakeTensor
  from torch.fx._compatibility import compatibility
  from torch.fx.passes.fake_tensor_prop import FakeTensorProp
  from torch.fx.passes.operator_support import OperatorSupport
  from torch.fx.passes.tools_common import CALLABLE_NODE_OPS
  from torch.utils import _pytree
label_desc: Use image node_id 14 for calling a global function with example usage: _to_real_tensor(tensor) and returns: out