code: def tril_indices(
      n_rows: int,
      n_cols: Optional[int] = None,
      k: int = 0,
      /,
      *,
      device: torch.device = None,
  ) -> Tuple[torch.Tensor, ...]:
      n_cols = n_rows if n_cols is None else n_cols
  
      if n_rows <= 0 or n_cols <= 0:
          n_rows, n_cols = 0, 0
  
      return tuple(
          torch.tril_indices(
              row=n_rows,
              col=n_cols,
              offset=k,
              dtype=torch.int64,
              device=device,
          )
      )
  
file_path: ivy/ivy/functional/backends/torch/experimental/creation.py
imports: from typing import Optional, Tuple, Union
  import math
  import torch
  import ivy
  from ivy.func_wrapper import with_unsupported_dtypes, with_unsupported_device_and_dtypes
  from ..None import backend_version
label_desc: Use image node_id 5 for calling a global function with example usage: tril_indices() and returns: tuple