code: def test_models_does_not_fall_on_constant_data():
      """Run models on constant data"""
      # models that raise exception
      to_skip = [
          "custom",
          "arima",
          "catboost",
          "catboostreg",
          "cgru",
          "lda",
          "fast_ica",
          "decompose",
          "class_decompose",
      ]
  
      for operation in OperationTypesRepository("all")._repo:
          if operation.id in to_skip:
              continue
          for task_type in operation.task_type:
              for data_type in operation.input_types:
                  data = get_data_for_testing(
                      task_type,
                      data_type,
                      length=100,
                      features_count=2,
                      random=False,
                  )
                  if data is not None:
                      nodes_from = []
                      if task_type is TaskTypesEnum.ts_forecasting:
                          if "non_lagged" not in operation.tags:
                              nodes_from = [PipelineNode("lagged")]
                      node = PipelineNode(
                          operation.id, nodes_from=nodes_from
                      )
                      pipeline = Pipeline(node)
                      pipeline.fit(data)
                      assert pipeline.predict(data) is not None
  
imports: import pickle
  from copy import deepcopy
  from time import perf_counter
  from typing import Tuple, Optional
  import numpy
  import pytest
  from golem.core.log import default_log
  from sklearn.datasets import make_classification
  from sklearn.metrics import mean_absolute_error, mean_squared_error, roc_auc_score
  from sklearn.preprocessing import MinMaxScaler
  from fedot.core.constants import FAST_TRAIN_PRESET_NAME
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.supplementary_data import SupplementaryData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import PCAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.discriminant_analysis import LDAImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.naive import NaiveAverageForecastImplementation, RepeatLastValueImplementation
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.statsmodels import GLMImplementation
  from fedot.core.operations.model import Model
  from fedot.core.operations.operation_parameters import get_default_params, OperationParameters
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.operation_types_repository import OperationMetaInfo, OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.core.utils import fedot_project_root
  from test.unit.common_tests import is_predict_ignores_target
  from test.unit.data_operations.test_time_series_operations import synthetic_univariate_ts
  from test.unit.tasks.test_forecasting import get_ts_data, get_ts_data_with_dt_idx
  from test.unit.tasks.test_regression import get_synthetic_regression_data
label_desc: Use image node_id 23 for calling a global function with example usage: test_models_does_not_fall_on_constant_data() without return types