code: def tokenize(text, custom_dict=None):
      
      global TOKENIZER
      if not TOKENIZER:
          TOKENIZER = DeepcutTokenizer()
      return TOKENIZER.tokenize(text, custom_dict=custom_dict)
docs: Tokenize given Thai text string
  
      Input
      =====
      text: str, Thai text string
      custom_dict: str (or list), path to customized dictionary file
          It allows the function not to tokenize given dictionary wrongly.
          The file should contain custom words separated by line.
          Alternatively, you can provide list of custom words too.
  
      Output
      ======
      tokens: list, list of tokenized words
  
      Example
      =======
      >> deepcut.tokenize('ตัดคำได้ดีมาก')
      >> ['ตัดคำ','ได้','ดี','มาก']