code: def test_inference_data(self, data, eight_schools_params):
      inference_data1 = self.get_inference_data(
          data, eight_schools_params
      )
      inference_data2 = self.get_inference_data2(
          data, eight_schools_params
      )
      inference_data3 = self.get_inference_data3(
          data, eight_schools_params
      )
      inference_data4 = self.get_inference_data4(data)
      inference_data5 = self.get_inference_data5(data)
      # inference_data 1
      test_dict = {
          "posterior": ["theta", "~log_lik"],
          "posterior_predictive": ["y_hat"],
          "predictions": ["y_hat"],
          "observed_data": ["y"],
          "constant_data": ["sigma"],
          "predictions_constant_data": ["sigma"],
          "sample_stats": ["diverging", "lp"],
          "log_likelihood": ["y", "~log_lik"],
          "prior": ["theta"],
      }
      fails = check_multiple_attrs(test_dict, inference_data1)
      assert not fails
      # inference_data 2
      test_dict = {
          "posterior_predictive": ["y_hat"],
          "predictions": ["y_hat"],
          "observed_data": ["y"],
          "sample_stats_prior": ["diverging"],
          "sample_stats": ["diverging", "lp"],
          "log_likelihood": ["log_lik"],
          "prior_predictive": ["y_hat"],
      }
      fails = check_multiple_attrs(test_dict, inference_data2)
      assert not fails
      assert any(
          item in inference_data2.posterior.attrs
          for item in ["stan_code", "program_code"]
      )
      assert any(
          item in inference_data2.sample_stats.attrs
          for item in ["stan_code", "program_code"]
      )
      # inference_data 3
      test_dict = {
          "posterior_predictive": ["y_hat", "log_lik"],
          "predictions": ["y_hat", "log_lik"],
          "constant_data": ["sigma", "y"],
          "predictions_constant_data": ["sigma", "y"],
          "sample_stats_prior": ["diverging"],
          "sample_stats": ["diverging", "lp"],
          "log_likelihood": ["log_lik"],
          "prior_predictive": ["y_hat", "log_lik"],
      }
      fails = check_multiple_attrs(test_dict, inference_data3)
      assert not fails
      # inference_data 4
      test_dict = {
          "posterior": ["theta"],
          "prior": ["theta"],
          "sample_stats": ["diverging", "lp"],
          "~log_likelihood": [""],
          "warmup_posterior": ["theta"],
          "warmup_sample_stats": ["diverging", "lp"],
      }
      fails = check_multiple_attrs(test_dict, inference_data4)
      assert not fails
      # inference_data 5
      test_dict = {
          "posterior": ["theta"],
          "prior": ["theta"],
          "sample_stats": ["diverging", "lp"],
          "~log_likelihood": [""],
          "warmup_posterior": ["theta"],
          "warmup_sample_stats": ["diverging", "lp"],
      }
      fails = check_multiple_attrs(test_dict, inference_data5)
      assert not fails
      assert inference_data5.posterior.eta.dtype.kind == "i"
  
imports: import importlib
  from collections import OrderedDict
  import numpy
  import pytest
  from ...None import from_pystan
  from ...data.io_pystan import get_draws, get_draws_stan3
  from ..helpers import chains, check_multiple_attrs, draws, eight_schools_params, importorskip, load_cached_models, pystan_version, running_on_ci
label_desc: Use image node_id 8 for calling the TestDataPyStan obj's underlying member method code with example usage: obj.test_inference_data(data, eight_schools_params) without return types