code: def get_not_default_search_space():
      custom_search_space = {
          "logit": {
              "C": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [1e-1, 5.0],
                  "type": "continuous",
              }
          },
          "ridge": {
              "alpha": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [0.01, 5.0],
                  "type": "continuous",
              }
          },
          "lgbmreg": {
              "learning_rate": {
                  "hyperopt-dist": hp.loguniform,
                  "sampling-scope": [0.05, 0.1],
                  "type": "continuous",
              },
              "colsample_bytree": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [0.2, 0.8],
                  "type": "continuous",
              },
              "subsample": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [0.1, 0.8],
                  "type": "continuous",
              },
          },
          "dt": {
              "max_depth": {
                  "hyperopt-dist": hp.uniformint,
                  "sampling-scope": [1, 5],
                  "type": "discrete",
              },
              "min_samples_split": {
                  "hyperopt-dist": hp.uniformint,
                  "sampling-scope": [10, 25],
                  "type": "discrete",
              },
          },
          "ar": {
              "lag_1": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [2, 100],
                  "type": "continuous",
              },
              "lag_2": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [2, 500],
                  "type": "continuous",
              },
          },
          "pca": {
              "n_components": {
                  "hyperopt-dist": hp.uniform,
                  "sampling-scope": [0.1, 0.5],
                  "type": "continuous",
              }
          },
      }
      return PipelineSearchSpace(
          custom_search_space=custom_search_space
      )
  
imports: import os
  from time import time
  import pytest
  from fedot.core.repository.dataset_types import DataTypesEnum
  from golem.core.tuning.hyperopt_tuner import get_node_parameters_for_hyperopt
  from golem.core.tuning.iopt_tuner import IOptTuner
  from golem.core.tuning.optuna_tuner import OptunaTuner
  from golem.core.tuning.sequential import SequentialTuner
  from golem.core.tuning.simultaneous import SimultaneousTuner
  from golem.utilities.data_structures import ensure_wrapped_in_sequence
  from hyperopt import hp
  from hyperopt.pyll.stochastic import sample
  from examples.simple.time_series_forecasting.ts_pipelines import ts_complex_ridge_smoothing_pipeline, ts_glm_pipeline
  from fedot.core.data.data import InputData
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.operations.evaluation.operation_implementations.models.ts_implementations.statsmodels import GLMImplementation
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.tuning.search_space import PipelineSearchSpace
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.metrics_repository import RegressionMetricsEnum, ClassificationMetricsEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum
  from fedot.core.utils import fedot_project_root, NESTED_PARAMS_LABEL
  from test.unit.multimodal.data_generators import get_single_task_multimodal_tabular_data, get_multimodal_pipeline
  from test.unit.tasks.test_forecasting import get_ts_data
label_desc: Use image node_id 20 for calling a global function with example usage: get_not_default_search_space() and returns: PipelineSearchSpace