code: def _get_param_to_param_key(
      optim: torch.optim.Optimizer,
      model: Optional[nn.Module] = None,
      is_named_optimizer: bool = False,
      param_to_fqns: Optional[Dict[nn.Parameter, List[str]]] = None,
      flat_param_to_fqn: Optional[Dict[FlatParameter, str]] = None,
  ) -> Dict[nn.Parameter, Union[int, str]]:
      """
      Constructs the inverse mapping of :func:`_get_param_key_to_param`. This API
      only supports the case where `optim` is a regular optimizer, not NamedOptimizer.
      So the parameter keys will be parameter ids.
      """
      param_id_to_param = _get_param_key_to_param(
          optim,
          model,
          is_named_optimizer,
          param_to_fqns,
          flat_param_to_fqn,
      )
      return {
          param: param_id
          for param_id, param in param_id_to_param.items()
      }
  
imports: import copy
  import functools
  import logging
  import warnings
  from contextlib import ExitStack
  from dataclasses import dataclass, field
  from typing import Any, cast, Dict, Iterable, Iterator, List, NamedTuple, no_type_check, Optional, Sequence, Set, Tuple, Union
  import torch
  import torch.distributed
  import torch.distributed.fsdp._traversal_utils
  import torch.nn
  from torch.distributed._shard.sharded_tensor import ShardedTensor
  from torch.distributed._state_dict_utils import _gather_state_dict
  from torch.distributed._tensor import DTensor, Replicate
  from torch.distributed.distributed_c10d import _get_pg_default_device
  from torch.distributed.fsdp._common_utils import _apply_to_modules, _FSDPState, _get_module_fsdp_state_if_fully_sharded_module, _get_param_to_fqns, _module_handle, _named_parameters_with_duplicates, clean_tensor_name
  from torch.distributed.fsdp._debug_utils import SimpleProfiler
  from torch.distributed.fsdp._flat_param import FlatParameter, FlatParamHandle
  from torch.distributed.fsdp._fsdp_extensions import _ext_chunk_dtensor, _ext_chunk_tensor
  from torch.distributed.fsdp._runtime_utils import _lazy_init, _reset_flat_param_grad_info_if_needed
  from torch.distributed.fsdp.api import ShardingStrategy, StateDictSettings, StateDictType
  from torch.utils._pytree import tree_map_only
label_desc: Use image node_id 18 for calling a global function with example usage: _get_param_to_param_key(optim, model, is_named_optimizer, param_to_fqns, flat_param_to_fqn) and returns: unknown