code: def get_baseline(
      texts: Union[str, List[str]],
      metadata: Optional[List[Dict[str, Any]]] = None,
  ) -> Union[str, List[str]]:
      """
      Generates a baseline by tokenizing and detokenizing the text
  
      @param texts: a string or a list of text documents to be augmented
  
      @param metadata: if set to be a list, metadata about the function execution
          including its name, the source & dest length, etc. will be appended to
          the inputted list. If set to None, no metadata will be appended or returned
  
      @returns: the list of augmented text documents
      """
      func_kwargs = txtutils.get_func_kwargs(metadata, locals())
  
      baseline_aug = a.BaselineAugmenter()
      aug_texts = baseline_aug.augment(texts, 1)
  
      txtutils.get_metadata(
          metadata=metadata,
          function_name="get_baseline",
          aug_texts=aug_texts,
          **func_kwargs,
      )
  
      return aug_texts
  
imports: from copy import deepcopy
  from typing import Any, Callable, Dict, List, Optional, Union
  from augly.text import augmenters, utils
  from augly.utils import CONTRACTIONS_MAPPING, FUN_FONTS_PATH, GENDERED_WORDS_MAPPING, MISSPELLING_DICTIONARY_PATH, UNICODE_MAPPING_PATH
label_desc: Use image node_id 4 for calling a global function with example usage: get_baseline(texts, metadata) and returns: aug_texts