code: def test_fit_predict_atomized_model_correctly():
      """Check if pipeline nested in AtomizedModel can give the same result as Pipeline stand-alone"""
      train_data, test_data = create_input_data()
  
      pipeline = create_pipeline_with_several_nested_atomized_model()
      AtomizedModel(pipeline)
  
      pipeline.fit(train_data)
      predicted_values = pipeline.predict(test_data)
  
      pipeline.unfit()
  
      pipeline.fit(train_data)
      predicted_atomized_output = pipeline.predict(test_data)
      predicted_atomized_values = predicted_atomized_output.predict
  
      source_mse = mean_squared_error(
          y_true=test_data.target, y_pred=predicted_values.predict
      )
      atomized_mse = mean_squared_error(
          y_true=test_data.target, y_pred=predicted_atomized_values
      )
  
      assert np.isclose(atomized_mse, source_mse)
  
imports: import json
  import os
  from functools import reduce
  import numpy
  import pytest
  from sklearn.metrics import mean_squared_error
  from fedot.core.composer.metrics import RMSE
  from fedot.core.data.data import InputData
  from fedot.core.operations.atomized_model import AtomizedModel
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.utils import fedot_project_root
  from test.integration.utilities.test_pipeline_import_export import create_correct_path, create_func_delete_files
label_desc: Use image node_id 11 for calling a global function with example usage: test_fit_predict_atomized_model_correctly() without return types