code: def _get_inplace_metadata(
      self, func, out
  ) -> Tuple[int, int, Tuple[int, ...]]:
      curr_idx = len(self.data)
  
      def get_tensor_id(e):
          return (
              e.untyped_storage().data_ptr()
              if isinstance(e, torch.Tensor)
              else None
          )
  
      output_ids = tree_map(get_tensor_id, out)
      if not is_inplace(func):
          return curr_idx, output_ids, ()
  
      op_id = curr_idx
      op_parent_id = -1
      for i, d in enumerate(self.data):
          # find the first occurence of a tensor that
          # shares the same storage as the current tensor
          past_output_ids = d.output_ids
          past_output_ids = (
              [past_output_ids]
              if not isinstance(past_output_ids, (list, tuple, dict))
              else past_output_ids
          )
          if output_ids in past_output_ids:
              op_parent_id = i
              break
      if op_parent_id < 0:
          op_parent_id = op_id
      inplace_info = (op_id, op_parent_id)
      return curr_idx, output_ids, inplace_info
  
imports: import time
  import weakref
  from collections import defaultdict
  from contextlib import nullcontext
  from copy import deepcopy
  from dataclasses import astuple, dataclass
  from typing import Any, Callable, ContextManager, Dict, List, Optional, Tuple
  import torch
  from torch.testing._internal.composite_compliance import is_inplace, is_inplace_view_fn, is_view_fn
  from torch.utils._python_dispatch import TorchDispatchMode
  from torch.utils._pytree import tree_map
  from torch.utils.checkpoint import get_device_states, set_device_states
label_desc: Use image node_id 2 for calling the ProfileOperatorsTorchDispatchMode obj's underlying member method code with example usage: obj._get_inplace_metadata(func, out) and returns: curr_idx,  output_ids,  inplace_info, unknown, curr_idx,  output_ids,  