class_docstr: Class for text cleaning (lemmatization and stemming) operation 
class_docstr_tok: ["Class","for","text","cleaning","(","lemmatization","and","stemming",")","operation"]
code: def _download_nltk_resources():
      for resource in ["punkt"]:
          try:
              nltk.data.find(f"tokenizers/{resource}")
          except LookupError:
              nltk.download(f"{resource}")
      for resource in ["stopwords", "wordnet", "omw-1.4"]:
          try:
              nltk.data.find(f"corpora/{resource}")
          except LookupError:
              nltk.download(f"{resource}")
  
file_path: FEDOT/fedot/core/operations/evaluation/operation_implementations/data_operations/text_preprocessing.py
imports: import re
  from typing import Optional
  import numpy
  from golem.utilities.requirements_notificator import warn_requirement
  from fedot.core.data.data import InputData, OutputData
  from fedot.core.operations.operation_parameters import OperationParameters
  from fedot.core.operations.evaluation.operation_implementations.implementation_interfaces import DataOperationImplementation
  from fedot.core.repository.dataset_types import DataTypesEnum
label_desc: Use image node_id 5 for calling the TextCleanImplementation obj's underlying member method code with example usage: obj._download_nltk_resources() without return types