code: def decompress_ids(c_ids: torch.Tensor) -> torch.Tensor:
      ids = torch.arange(
          c_ids.numel() - 1, dtype=c_ids.dtype, device=c_ids.device
      )
      return ids.repeat_interleave(c_ids[1:] - c_ids[:-1])
  
imports: from typing import Optional, Tuple, Union
  from cugraph.utilities.utils import import_optional
label_desc: Use image node_id 2 for calling a global function with example usage: decompress_ids(c_ids) and returns: ids