code: def test_isin_execution(setup):
      # one chunk in multiple chunks
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = pd.Series([2, 1, 9, 3])
      sa = from_pandas_series(a, chunk_size=10)
      sb = from_pandas_series(b, chunk_size=2)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      # multiple chunk in one chunks
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = pd.Series([2, 1, 9, 3])
      sa = from_pandas_series(a, chunk_size=2)
      sb = from_pandas_series(b, chunk_size=4)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      # multiple chunk in multiple chunks
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = pd.Series([2, 1, 9, 3] * 2)
      sa = from_pandas_series(a, chunk_size=2)
      sb = from_pandas_series(b, chunk_size=2)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = pd.Series([2, 1, 9, 3] * 3)
      sa = from_pandas_series(a, chunk_size=5)
      sb = from_pandas_series(b, chunk_size=2)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = pd.Series([2, 1, 9, 3])
      sa = from_pandas_series(a, chunk_size=2)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = np.array([2, 1, 9, 3] * 5)
      sa = from_pandas_series(a, chunk_size=5)
      sb = tensor(b, chunk_size=4)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      a = pd.Series([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
      b = {2, 1, 9, 3}  # set
      sa = from_pandas_series(a, chunk_size=2)
  
      result = sa.isin(sb).execute().fetch()
      expected = a.isin(b)
      pd.testing.assert_series_equal(result, expected)
  
      rs = np.random.RandomState(0)
      raw = pd.DataFrame(rs.randint(1000, size=(10, 3)))
      df = from_pandas_df(raw, chunk_size=(5, 2))
  
      # set
      b = {2, 1, raw[1][0]}
      r = df.isin(b)
      result = r.execute().fetch()
      expected = raw.isin(b)
      pd.testing.assert_frame_equal(result, expected)
  
      # mars object
      b = tensor([2, 1, raw[1][0]] * 2, chunk_size=2)
      r = df.isin(b)
      result = r.execute().fetch()
      expected = raw.isin([2, 1, raw[1][0]])
      pd.testing.assert_frame_equal(result, expected)
  
      # mars object and trigger iterative tiling
      raw = pd.DataFrame(rs.randint(1000, size=(10, 3)))
      df = from_pandas_df(raw, chunk_size=(5, 2))
  
      b = from_pandas_series(
          pd.Series([raw[1][0]] + list(range(9))), chunk_size=2
      )
      r = df.isin(b)
      result = r.execute().fetch()
      expected = raw.isin([2, 1, raw[1][0]])
      pd.testing.assert_frame_equal(result, expected)
  
      # dict
      b = {1: tensor([2, 1, raw[1][0]], chunk_size=2), 2: [3, 10]}
      r = df.isin(b)
      result = r.execute().fetch()
      expected = raw.isin({1: [2, 1, raw[1][0]], 2: [3, 10]})
      pd.testing.assert_frame_equal(result, expected)
  
imports: import random
  from collections import OrderedDict
  import numpy
  import pandas
  import pytest
  import mars
  from ....config import options, option_context
  from ....dataframe import DataFrame, Series
  from ....tensor import arange, tensor
  from ....tensor.random import rand
  from ....tests.core import require_cudf
  from ....utils import lazy_import, pd_release_version, no_default
  from ...None import eval, cut, qcut, get_dummies
  from ...core import DATAFRAME_OR_SERIES_TYPE
  from ...datasource.dataframe import from_pandas
  from ...datasource.series import from_pandas
  from ...datasource.index import from_pandas
  from ..None import to_gpu, to_cpu
  from ..bloom_filter import filter_by_bloom_filter
  from ..shift import _enable_no_default, _with_column_freq_bug
  from ..to_numeric import to_numeric
  from ..rebalance import DataFrameRebalance
label_desc: Use image node_id 16 for calling a global function with example usage: test_isin_execution(setup) without return types