code: def tril_indices(
      n_rows: int,
      n_cols: Optional[int] = None,
      k: Optional[int] = 0,
      /,
      *,
      device: core.Place = None,
  ) -> Tuple[paddle.Tensor, ...]:
      # special case due to inconsistent behavior when n_cols=1 and n_rows=0
      if not (n_cols and n_rows):
          return paddle.to_tensor([], dtype="int64"), paddle.to_tensor(
              [], dtype="int64"
          )
      return tuple(
          paddle.tril_indices(
              n_rows, col=n_cols, offset=k, dtype="int64"
          )
      )
  
file_path: ivy/ivy/functional/backends/paddle/experimental/creation.py
imports: from typing import Optional, Tuple, Union
  import math
  import paddle
  import ivy.functional.backends.paddle
  from paddle.device import core
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_device_and_dtypes
  import ivy
  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, paddle,  paddle