code: def test_load_though_api_perform_correctly():
      """Test API wrapper for pipeline loading"""
      input_data = data_with_spaces_and_nans_in_features()
  
      model = Fedot(problem="regression")
      obtained_pipeline = model.fit(
          input_data, predefined_model="ridge"
      )
      predictions = model.predict(input_data)
  
      # Save pipeline
      obtained_pipeline.save(
          "test_load_though_api_perform_correctly", create_subdir=False
      )
  
      loaded_model = Fedot(problem="regression")
      loaded_model.load(
          create_correct_path("test_load_though_api_perform_correctly")
      )
      loaded_predictions = loaded_model.predict(input_data)
  
      assert np.array_equal(predictions, loaded_predictions)
  
imports: import json
  import os
  import shutil
  import numpy
  import pytest
  from sklearn.metrics import mean_absolute_error
  from fedot import Fedot
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.template import PipelineTemplate, extract_subtree_root
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root
  from test.integration.api.test_main_api import get_dataset
  from test.unit.data_operations.test_data_operations_implementations import get_mixed_data
  from test.unit.multimodal.data_generators import get_single_task_multimodal_tabular_data
  from test.unit.pipelines.test_decompose_pipelines import get_classification_data
  from test.unit.preprocessing.test_preprocessing_through_api import data_with_spaces_and_nans_in_features
  from test.unit.tasks.test_forecasting import get_multiscale_pipeline, get_simple_ts_pipeline, get_ts_data
label_desc: Use image node_id 30 for calling a global function with example usage: test_load_though_api_perform_correctly() without return types