code: def _load_tensor(self) -> Tensor:
      from torch.storage import TypedStorage, UntypedStorage
  
      _, _, fn, _, size = self.storageinfo
      dtype = self.metatensor.dtype
  
      storage = self.archiveinfo.file_reader.get_storage_from_record(
          f"data/{fn}",
          size * torch._utils._element_size(dtype),
          UntypedStorage,
      )
      uts = storage._typed_storage()._untyped_storage
  
      with warnings.catch_warnings():
          # The TypedStorage APIs have heavy deprecations in torch, suppress all these warnings for now
          warnings.simplefilter("ignore")
          storage = TypedStorage(
              wrap_storage=uts, dtype=dtype, _internal=True
          )
      return torch._utils._rebuild_tensor_v2(
          storage, *self.rebuild_args
      )
  
imports: import os
  import pickle
  import warnings
  from functools import partial
  from io import BytesIO
  from typing import IO, TYPE_CHECKING, Any, Callable, Dict, Optional, OrderedDict, Sequence, Set, Union
  import torch
  from lightning_utilities.core.apply_func import apply_to_collection
  from torch import Tensor
  from torch._C import _TensorMeta
  from torch.nn import Parameter
  from typing_extensions import override
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_0
  from lightning.fabric.utilities.types import _PATH, _Stateful
label_desc: Use image node_id 5 for calling the _NotYetLoadedTensor obj's underlying member method code with example usage: obj._load_tensor() and returns: torch