code: def merge_tensors(tensor_objects, non_tensor_objects, tensor_flags):
      """
      Merge two lists (or tuples) of tensors and non-tensors using a mapping of positions in merged list (or tuple).
  
      Parameters:
          tensor_objects (list/tuple): Tensors to merge.
          non_tensor_objects (list/tuple): Non-tensors to merge.
          tensor_flags (list/tuple): Indicates whether each position in output is a tensor.
  
      Returns:
          tuple: Merge of tensors and non-tensors
      """
      merged_objects = []
      tensor_idx = 0
      non_tensor_idx = 0
  
      real_tensor_flags = None
  
      # remove the flags that are assigned to the size of the flattened tensors
      if PARTITION_ACTIVATIONS:
          real_tensor_flags = []
          previous_flag = False
          for flag in tensor_flags:
              if previous_flag:
                  previous_flag = False
                  continue
              previous_flag = flag
              real_tensor_flags.append(flag)
      else:
          real_tensor_flags = tensor_flags
  
      for is_tensor in real_tensor_flags:
          if is_tensor:
              merged_objects.append(tensor_objects[tensor_idx])
              tensor_idx += 1
          else:
              merged_objects.append(non_tensor_objects[non_tensor_idx])
              non_tensor_idx += 1
  
      return tuple(merged_objects)
  
imports: import copy
  import torch
  import contextlib
  from deepspeed import comm
  import weakref
  import mmap
  from torch import _C
  from deepspeed.runtime.config import DeepSpeedConfig
  from deepspeed.utils import logger
  from deepspeed.runtime.utils import copy_to_device, move_to_device, see_memory_usage, bwc_tensor_model_parallel_rank
  from deepspeed.utils.timer import SynchronizedWallClockTimer, FORWARD_GLOBAL_TIMER
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 10 for calling a global function with example usage: merge_tensors(tensor_objects, non_tensor_objects, tensor_flags) and returns: tuple