code: def test_inf_and_nan_absence_after_pipeline_fitting_from_scratch():
      train_input = get_nan_inf_data()
  
      model_names = OperationTypesRepository().suitable_operation(
          task_type=TaskTypesEnum.regression
      )
  
      for model_name in model_names:
          node_data_operation = PipelineNode(model_name)
          node_final = PipelineNode(
              "linear", nodes_from=[node_data_operation]
          )
          pipeline = Pipeline(node_final)
  
          # Fit and predict for pipeline
          pipeline.fit_from_scratch(train_input)
          predicted_output = pipeline.predict(train_input)
          predicted = predicted_output.predict
  
          assert np.sum(np.isinf(predicted)) == 0
          assert np.sum(np.isnan(predicted)) == 0
  
imports: import os
  import numpy
  import pytest
  from examples.simple.classification.classification_with_tuning import get_classification_dataset
  from examples.simple.regression.regression_with_tuning import get_regression_dataset
  from examples.simple.time_series_forecasting.gapfilling import generate_synthetic_data
  from fedot.core.data.data import InputData
  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_imbalanced_class import ResampleImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.sklearn_transformations import ImputationImplementation
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import CutImplementation, LaggedTransformationImplementation
  from fedot.core.operations.operation_parameters import 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 OperationTypesRepository
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
  from fedot.preprocessing.data_types import TYPE_TO_ID
  from test.unit.preprocessing.test_preprocessing_through_api import data_with_only_categorical_features
label_desc: Use image node_id 18 for calling a global function with example usage: test_inf_and_nan_absence_after_pipeline_fitting_from_scratch() without return types