class_docstr: Module level tests for all sktime forecasters.
class_docstr_tok: ["Module","level","tests","for","all","sktime","forecasters","."]
code: def _check_predict_proba(self, pred_dist, y_train, fh_int):
      assert hasattr(pred_dist, "get_tag")
      obj_type = pred_dist.get_tag("object_type", None, False)
      assert obj_type == "distribution"
  
      pred_cols = pred_dist.columns
      pred_index = pred_dist.index
  
      # check time index
      cutoff = get_cutoff(y_train, return_index=True)
      _assert_correct_pred_time_index(pred_index, cutoff, fh_int)
  
      # check columns
      if isinstance(y_train, pd.Series):
          if y_train.name is not None:
              assert (pred_cols == y_train.name).all()
          else:
              assert (pred_cols == pd.Index([0])).all()
      else:
          assert (pred_cols == y_train.columns).all()
  
imports: import numpy
  import pandas
  import pytest
  from sktime.datatypes import check_is_mtype
  from sktime.datatypes._utilities import get_cutoff
  from sktime.exceptions import NotFittedError
  from sktime.forecasting.base._delegate import _DelegatedForecaster
  from sktime.forecasting.base._fh import ForecastingHorizon
  from sktime.forecasting.tests._config import TEST_ALPHAS, TEST_FHS, TEST_OOS_FHS, TEST_STEP_LENGTHS_INT, TEST_WINDOW_LENGTHS_INT, VALID_INDEX_FH_COMBINATIONS
  from sktime.performance_metrics.forecasting import mean_absolute_percentage_error
  from sktime.split import ExpandingWindowSplitter, SlidingWindowSplitter, temporal_train_test_split
  from sktime.tests.test_all_estimators import BaseFixtureGenerator, QuickTester
  from sktime.utils._testing.forecasting import _assert_correct_columns, _assert_correct_pred_time_index, _get_expected_index_for_update_predict, _get_n_columns, _make_fh, make_forecasting_problem
  from sktime.utils._testing.series import _make_series
  from sktime.utils.validation.forecasting import check_fh
label_desc: Use image node_id 14 for calling the TestAllForecasters obj's underlying member method code with example usage: obj._check_predict_proba(pred_dist, y_train, fh_int) without return types