docstr: Check input types (change, see earlier)
  
  posterior_predictive --> List[str], variable in posterior
  observed_data_var --> List[str], variable
docstr_tok: ["Check","input","types","(","change",",","see","earlier",")","posterior_predictive","--",">","List","[","str","]",",","variable","in","posterior","observed_data_var","--",">","List","[","str","]",",","variable"]
code: def test_inference_data_input_types2(
      self, paths, observed_data_paths
  ):
      """Check input types (change, see earlier)
  
      posterior_predictive --> List[str], variable in posterior
      observed_data_var --> List[str], variable
      """
      for key, path in paths.items():
          if "eight" not in key:
              continue
          inference_data = self.get_inference_data(
              posterior=path,
              posterior_predictive=["y_hat"],
              predictions=["y_hat"],
              prior=path,
              prior_predictive=["y_hat"],
              observed_data=observed_data_paths[0],
              observed_data_var=["y"],
              constant_data=observed_data_paths[0],
              constant_data_var=["y"],
              predictions_constant_data=observed_data_paths[0],
              predictions_constant_data_var=["y"],
              coords={"school": np.arange(8)},
              dims={
                  "theta": ["school"],
                  "y": ["school"],
                  "log_lik": ["school"],
                  "y_hat": ["school"],
                  "eta": ["school"],
              },
              dtypes={"theta": np.int64},
          )
          test_dict = {
              "posterior": ["mu", "tau", "theta_tilde", "theta"],
              "posterior_predictive": ["y_hat"],
              "predictions": ["y_hat"],
              "prior": ["mu", "tau", "theta_tilde", "theta"],
              "prior_predictive": ["y_hat"],
              "sample_stats": ["diverging"],
              "observed_data": ["y"],
              "constant_data": ["y"],
              "predictions_constant_data": ["y"],
              "log_likelihood": ["log_lik"],
          }
          fails = check_multiple_attrs(test_dict, inference_data)
          assert not fails
          assert isinstance(
              inference_data.posterior.theta.data.flat[0], np.integer
          )
  
imports: import os
  import numpy
  import pytest
  from ...None import from_cmdstan
  from ..helpers import check_multiple_attrs
label_desc: Use image node_id 8 for calling the TestDataCmdStan obj's underlying member method code with example usage: obj.test_inference_data_input_types2(paths, observed_data_paths) without return types