class_docstr: Singleton class representing a required parameter for an Optimizer.
class_docstr_tok: ["Singleton","class","representing","a","required","parameter","for","an","Optimizer","."]
code: def __repr__(self) -> str:
      return "<required parameter>"
  
imports: import math
  import functools
  import warnings
  from collections import OrderedDict, defaultdict
  from copy import deepcopy
  from itertools import chain
  from typing import Any, Callable, DefaultDict, Dict, Hashable, Iterable, List, Optional, Set, Tuple, TypeVar, Union, cast, overload
  from typing_extensions import ParamSpec, Self, TypeAlias
  import torch
  import torch.utils.hooks
  from torch.utils.hooks import RemovableHandle
  from torch.utils._foreach_utils import Indices, TensorListList, _get_foreach_kernels_supported_devices, _get_fused_kernels_supported_devices
  from torch._utils import is_compiling
  from torch.utils._foreach_utils import _group_tensors_by_device_and_dtype
label_desc: Use image node_id 1 for calling the _RequiredParameter obj's underlying member method code with example usage: obj.__repr__() and returns: str