code: def diff(
      x: Union[paddle.Tensor, list, tuple],
      /,
      *,
      n: int = 1,
      axis: int = -1,
      prepend: Optional[
          Union[paddle.Tensor, int, float, list, tuple]
      ] = None,
      append: Optional[
          Union[paddle.Tensor, int, float, list, tuple]
      ] = None,
      out: Optional[paddle.Tensor] = None,
  ) -> paddle.Tensor:
      ret_dtype = x.dtype
  
      def _tensor(val):
          if val is not None and not isinstance(val, paddle.Tensor):
              return paddle.to_tensor(val, dtype=ret_dtype)
          return val
  
      prepend = _tensor(prepend)
      append = _tensor(append)
      return paddle.diff(
          x, n=n, axis=axis, prepend=prepend, append=append
      ).cast(ret_dtype)
  
imports: import operator
  from typing import Optional, Union, Tuple, List, Sequence
  from numbers import Number
  import paddle
  from ivy.utils.exceptions import IvyNotImplementedException
  from ivy.func_wrapper import with_supported_dtypes, with_unsupported_device_and_dtypes, with_unsupported_dtypes
  import ivy.functional.backends.paddle
  import ivy
  from ivy import promote_types_of_inputs
  from ivy.functional.backends.paddle.elementwise import _elementwise_helper
  from ..None import backend_version
label_desc: Use image node_id 12 for calling a global function with example usage: diff() and returns: paddle, val, paddle