code: def get_idx_from_placements(placements, current_rank) -> int:
      """
      Return the position of the current rank in the given placements.
  
      Args:
          placements(List[Union[_remote_device, str]]):
              Specifies the placement of each shard of the Tensor. The size of
              the list represents the number of shards to be created. This could
              be a list of
              :class:`torch.distributed._remote_device`'s. This list
              could also contain a string which represents remote
              device as accepted by
              :class:`torch.distributed._remote_device`
          current_rank (int): number of current device.
  
      Returns:
          A int which contains the position of current device in the placement list.
      """
      for idx, placement in enumerate(placements):  # type: ignore[attr-defined]
          if current_rank == placement.rank():  # type: ignore[union-attr]
              return idx
      raise RuntimeError("current_rank not in the placement.")
  
file_path: pytorch/torch/distributed/_shard/sharded_tensor/reshard.py
imports: import copy
  from typing import List, Tuple
  import torch
  import torch.distributed
  from torch._C._distributed_c10d import ProcessGroup
  import torch.distributed._shard.sharding_spec
  from torch.distributed._shard.sharding_spec._internals import get_split_size, get_chunked_dim_size
  from torch.distributed.nn.functional import all_to_all, all_to_all_single
  from torch.distributed._shard.metadata import ShardMetadata
  from .shard import Shard
label_desc: Use image node_id 1 for calling a global function with example usage: get_idx_from_placements(placements, current_rank) and returns: idx