code: def test_api_fit_predict_with_pseudo_large_dataset_with_onehot_correct():
      """
      Test if safe mode in API use OneHotEncoder with small data with small cardinality
      """
      model = Fedot(
          problem="classification", **TESTS_MAIN_API_DEFAULT_PARAMS
      )
      model.data_analyser.max_size = 1000
      data = get_small_cat_data()
      model.fit(features=data, predefined_model="auto")
  
      model.predict(features=data)
      # there should be all light models + data operations
      assert "logit" in model.params.get("available_operations")
  
file_path: FEDOT/test/unit/api/test_api_safety.py
imports: import numpy
  from fedot.api.api_utils.api_data import ApiDataProcessor
  from fedot.api.api_utils.input_analyser import InputAnalyser
  from fedot import Fedot
  from fedot.core.data.data import InputData
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import TaskTypesEnum, Task
  from fedot.preprocessing.preprocessing import DataPreprocessor
  from test.integration.api.test_main_api import TESTS_MAIN_API_DEFAULT_PARAMS
label_desc: Use image node_id 7 for calling a global function with example usage: test_api_fit_predict_with_pseudo_large_dataset_with_onehot_correct() without return types