code: def test_var_names_filter_multiple_input(var_args):
      samples = np.random.randn(10)
      data1 = dict_to_dataset(
          {"beta1": samples, "beta2": samples, "phi": samples}
      )
      data2 = dict_to_dataset(
          {"beta1": samples, "beta2": samples, "theta": samples}
      )
      data = [data1, data2]
      var_names, expected, filter_vars = var_args
      assert _var_names(var_names, data, filter_vars) == expected
  
imports: from unittest.mock import Mock
  import numpy
  import pytest
  import scipy.stats
  from ...data import dict_to_dataset, from_dict, load_arviz_data
  from ...stats.density_utils import _circular_mean, _normalize_angle, _find_hdi_contours
  from ...utils import _stack, _subset_list, _var_names, expand_dims, flatten_inference_data_to_dict, one_de, two_de
  from ..helpers import TestRandomVariable
label_desc: Use image node_id 6 for calling a global function with example usage: test_var_names_filter_multiple_input(var_args) without return types