code: def _is_fsdp_flattened(tensor: torch.Tensor) -> bool:
      """Returns if ``tensor`` has been marked as flattened by FSDP."""
      return getattr(tensor, FSDP_FLATTENED, False)
  
imports: import logging
  import traceback
  import warnings
  import weakref
  from enum import auto, Enum
  from functools import partial
  from typing import Any, Callable, cast, Dict, Generator, Iterable, List, no_type_check, Optional, Set, Tuple, Type, TYPE_CHECKING
  import torch
  import torch.distributed
  import torch.distributed.fsdp._flat_param
  import torch.nn
  from torch.distributed._composable_state import _get_module_state, _State
  from torch.distributed._tensor.device_mesh import DeviceMesh
  from torch.distributed.algorithms._checkpoint.checkpoint_wrapper import _CHECKPOINT_PREFIX
  from torch.distributed.fsdp._fsdp_extensions import FSDPExtensions
  from torch.distributed.utils import _apply_to_tensors
  from torch.utils._mode_utils import no_dispatch
  from .api import FullOptimStateDictConfig, FullStateDictConfig, OptimStateDictConfig, ShardingStrategy, StateDictConfig, StateDictType
label_desc: Use image node_id 9 for calling a global function with example usage: _is_fsdp_flattened(tensor) and returns: getattr