code: def triu_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 n_cols == 1 and n_rows == 0:
          return paddle.to_tensor(
              [], place=device, dtype="int64"
          ), paddle.to_tensor([], place=device, dtype="int64")
      return tuple(
          paddle.triu_indices(
              n_rows, col=n_cols, offset=k, dtype="int64"
          )
      )
  
imports: import struct
  from numbers import Number
  from typing import Union, List, Optional, Sequence, Tuple
  import numpy
  import paddle
  import ivy.functional.backends.paddle
  import ivy
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from ivy.functional.ivy.creation import _asarray_to_native_arrays_and_back, _asarray_infer_device, _asarray_handle_nestable, _asarray_infer_dtype, NestedSequence, SupportsBufferProtocol, _asarray_inputs_to_native_shapes, _remove_np_bfloat16
  from .None import backend_version
  from paddle.device import core
label_desc: Use image node_id 24 for calling a global function with example usage: triu_indices() and returns: tuple, paddle,  paddle