code: def normalize_samples(
      text_samples: t.Sequence[str],
      *,
      ignore_case: bool = True,
      remove_punct: bool = True,
      normalize_uni: bool = True,
      remove_stops: bool = True,
      ignore_whitespace: bool = False,
  ) -> t.List[str]:
      """Normalize given sequence of text samples."""
      return [
          normalize_text(
              it,
              ignore_case=ignore_case,
              remove_punct=remove_punct,
              normalize_uni=normalize_uni,
              remove_stops=remove_stops,
              ignore_whitespace=ignore_whitespace,
          )
          for it in text_samples
      ]
  
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 7 for calling a global function with example usage: normalize_samples(text_samples) and returns: unknown