code: def copy_input_files(infold):
      """
      Put training files in convenient place for conversion to our format.
  
      Args:
          infold: location of an original fold of the dataset (in the sense of k-fold cross validation)
      """
      our_infold = infold + "/dataset"
  
      if os.path.exists(our_infold + "/trainset") and os.path.exists(
          our_infold + "/testset"
      ):
          logging.info("Input folders exists")
          return
  
      logging.info(f"Copying files to input folder: {our_infold}")
      os.makedirs(infold, exist_ok=True)
  
      old_infold = (
          infold
          + "/CrossValidation/autoGeneFromRealAnno/autoGene_2018_03_22-13_01_25_169/CrossValidation/KFold_1"
      )
      if not os.path.exists(our_infold + "/trainset"):
          shutil.copytree(
              old_infold + "/trainset", our_infold + "/trainset"
          )
  
      if not os.path.exists(our_infold + "/testset"):
          shutil.copytree(
              old_infold + "/testset/csv", our_infold + "/testset"
          )
  
file_path: NeMo/scripts/dataset_processing/nlp/intent_and_slot/assistant_utils.py
imports: import os
  import re
  import shutil
  from nemo.collections.nlp.data.data_utils.data_preprocessing import DATABASE_EXISTS_TMP, if_exist, write_files
  from nemo.utils import logging
label_desc: Use image node_id 1 for calling a global function with example usage: copy_input_files(infold) without return types