code: def convert_to_pool(data: Optional[InputData]):
      return Pool(
          data=data.features,
          label=data.target,
          cat_features=data.categorical_idx,
          feature_names=data.features_names.tolist()
          if data.features_names is not None
          else None,
      )
  
imports: import os
  from typing import Optional
  import numpy
  import pandas
  from catboost import CatBoostClassifier, CatBoostRegressor, Pool
  from matplotlib import pyplot
  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.implementation_interfaces import ModelImplementation
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.utils import default_fedot_data_dir
label_desc: Use image node_id 5 for calling the FedotCatBoostImplementation obj's underlying member method code with example usage: obj.convert_to_pool(data) and returns: Pool