code: def prepare_logging():
      old_factory = logging.getLogRecordFactory()
      records = []
  
      def record_factory(*args, **kwargs):
          record = old_factory(*args, **kwargs)
          records.append(record)
          return record
  
      logging.setLogRecordFactory(record_factory)
      return records
  
imports: import logging
  from copy import deepcopy
  import numpy
  import pytest
  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.data.multi_modal import MultiModalData
  from fedot.core.operations.evaluation.operation_implementations.data_operations.ts_transformations import _sparse_matrix, prepare_target, ts_to_table
  from fedot.core.optimisers.objective import MetricsObjective, PipelineObjectiveEvaluate
  from fedot.core.optimisers.objective.data_source_splitter import DataSourceSplitter
  from fedot.core.pipelines.node import PipelineNode
  from fedot.core.pipelines.pipeline import Pipeline
  from fedot.core.pipelines.pipeline_builder import PipelineBuilder
  from fedot.core.pipelines.tuning.tuner_builder import TunerBuilder
  from fedot.core.repository.dataset_types import DataTypesEnum
  from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_logging() and returns: records, record