code: def isin(
      elements: paddle.Tensor,
      test_elements: paddle.Tensor,
      /,
      *,
      assume_unique: Optional[bool] = False,
      invert: Optional[bool] = False,
  ) -> paddle.Tensor:
      input_shape = elements.shape
      if elements.ndim == 0:
          elements = paddle_backend.expand_dims(elements, axis=0)
      if test_elements.ndim == 0:
          test_elements = paddle_backend.expand_dims(
              test_elements, axis=0
          )
      if not assume_unique:
          test_elements = paddle_backend.unique_values(test_elements)
  
      elements = elements.reshape([-1])
      test_elements = test_elements.reshape([-1])
  
      output = paddle_backend.any(
          paddle_backend.equal(
              paddle_backend.expand_dims(elements, axis=-1),
              test_elements,
          ),
          axis=-1,
      )
      return paddle_backend.logical_xor(
          paddle_backend.reshape(output, input_shape), invert
      )
  
imports: from numbers import Number
  from typing import Optional, Union, Sequence, Callable, List, Tuple
  import paddle
  import numpy
  import multiprocessing
  import ivy
  import ivy.functional.backends.paddle
  from ivy.func_wrapper import with_unsupported_device_and_dtypes
  from ivy.functional.ivy.general import _broadcast_to
  from ivy.utils.exceptions import _check_inplace_update_support
  from .None import backend_version
label_desc: Use image node_id 24 for calling a global function with example usage: isin() and returns: paddle_backend