code: def __getattr__(self, name: str) -> Any:
      # These properties don't require materialization and can be accessed through the meta tensor directly
      if name in {
          "dtype",
          "grad",
          "grad_fn",
          "is_meta",
          "layout",
          "names",
          "ndim",
          "output_nr",
          "requires_grad",
          "retains_grad",
          "size",
          "shape",
          "volatile",
      }:
          return getattr(self.metatensor, name)
  
      # materializing these is needed for quantization (see lit-gpt)
      if name in {"contiguous", "cuda", "half"}:
          return getattr(self._load_tensor(), name)
  
      raise AttributeError(
          f"'{type(self).__name__}' object has no attribute '{name}'"
      )
  
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 7 for calling the _NotYetLoadedTensor obj's underlying member method code with example usage: obj.__getattr__(name) and returns: getattr, getattr