code: def get_chunk_sizes(total_elems, chunk_size):
      n_chunks = n_chunks = total_elems // chunk_size
      chunk_sizes = [chunk_size] * n_chunks
      # remainder chunk
      remainder = total_elems % chunk_size
      if remainder != 0:
          chunk_sizes.append(remainder)
      return chunk_sizes
  
imports: import torch
  import functools
  import threading
  from torch import Tensor
  from typing import Any, Callable, Optional, Tuple, Union, List
  from torch.utils._pytree import tree_flatten, tree_unflatten, tree_map_, _broadcast_to_and_flatten, TreeSpec
  from functools import partial
  import os
  import itertools
  from torch._C._functorch import _add_batch_dim, _remove_batch_dim, _vmap_decrement_nesting, _vmap_increment_nesting, is_batchedtensor
label_desc: Use image node_id 14 for calling a global function with example usage: get_chunk_sizes(total_elems, chunk_size) and returns: chunk_sizes