code: def test_str_numbers_with_dots_and_commas_in_predict():
      """Checks that if training part type was defined as int than predict part will be correctly
      converted to ints even if it contains str with dots/commas"""
      task = Task(TaskTypesEnum.classification)
      features = np.array(
          [["8,5"], ["4.9"], ["3,2"], ["6.1"]], dtype=object
      )
      target = np.array([["no"], ["yes"], ["yes"], ["yes"]])
      input_data = InputData(
          idx=np.arange(4),
          features=features,
          target=target,
          task=task,
          data_type=DataTypesEnum.table,
      )
  
      transformed_predict = apply_type_transformation(
          table=input_data.features,
          col_type_ids=[TYPE_TO_ID[int]],
          log=default_log(
              "test_str_numbers_with_dots_and_commas_in_predict"
          ),
      )
  
      assert all(transformed_predict == np.array([[8], [4], [3], [6]]))
  
imports: import numpy
  import pandas
  from golem.core.log import default_log
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  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.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from fedot.preprocessing.data_types import TableTypesCorrector, apply_type_transformation
  from fedot.preprocessing.structure import DEFAULT_SOURCE_NAME
  from test.unit.preprocessing.test_pipeline_preprocessing import correct_preprocessing_params, data_with_mixed_types_in_each_column
label_desc: Use image node_id 12 for calling a global function with example usage: test_str_numbers_with_dots_and_commas_in_predict() without return types