code: def diff(
      x: Union[tf.Tensor, tf.Variable, list, tuple],
      /,
      *,
      n: int = 1,
      axis: int = -1,
      prepend: Optional[
          Union[tf.Tensor, tf.Variable, int, float, list, tuple]
      ] = None,
      append: Optional[
          Union[tf.Tensor, tf.Variable, int, float, list, tuple]
      ] = None,
      out: Optional[Union[tf.Tensor, tf.Variable]] = None,
  ) -> Union[tf.Tensor, tf.Variable]:
      if n == 0:
          return x
      if prepend is not None:
          x = tf.experimental.numpy.append(
              prepend, x, axis=axis if axis != -1 else None
          )
      if append is not None:
          x = tf.experimental.numpy.append(
              x, append, axis=axis if axis != -1 else None
          )
      return tf.experimental.numpy.diff(x, n=n, axis=axis)
  
imports: import operator
  from typing import Union, Optional, Tuple, List, Sequence
  from numbers import Number
  import tensorflow
  from tensorflow.python.ops.numpy_ops import np_math_ops
  import ivy
  from ivy import promote_types_of_inputs
  from ivy.func_wrapper import with_unsupported_dtypes, with_supported_dtypes
  from ..None import backend_version
label_desc: Use image node_id 16 for calling a global function with example usage: diff() and returns: tf, x