code: def normalize_text(
      text_sample: str,
      *,
      ignore_case: bool = True,
      remove_punct: bool = True,
      normalize_uni: bool = True,
      remove_stops: bool = True,
      ignore_whitespace: bool = False,
  ) -> str:
      """Normalize given text sample."""
      if ignore_case:
          text_sample = text_sample.lower()
      if remove_punct:
          text_sample = remove_punctuation(text_sample)
      if normalize_uni:
          text_sample = normalize_unicode(text_sample)
      if remove_stops:
          text_sample = remove_stopwords(text_sample)
      if ignore_whitespace:
          text_sample = "".join(text_sample.split())
      return text_sample
  
file_path: deepchecks/deepchecks/nlp/utils/text.py
imports: import re
  import string
  import typing
  import unicodedata
  import warnings
  import nltk
  from nltk.corpus import stopwords
  from nltk.tokenize import word_tokenize
label_desc: Use image node_id 5 for calling a global function with example usage: normalize_text(text_sample) and returns: text_sample