class_docstr: A Transform object corresponds to a specific data format.
  It holds several instances of data fields that provide instructions for preprocessing and numericalizing, etc.
  
  Attributes:
      training (bool):
          Sets the object in training mode.
          If ``False``, some data fields not required for predictions won't be returned.
          Default: ``True``.
class_docstr_tok: ["A","Transform","object","corresponds","to","a","specific","data","format",".","It","holds","several","instances","of","data","fields","that","provide","instructions","for","preprocessing","and","numericalizing",",","etc",".","Attributes",":","training","(","bool",")",":","Sets","the","object","in","training","mode",".","If","``","False","``",",","some","data","fields","not","required","for","predictions","wo","n't","be","returned",".","Default",":","``","True","``","."]
code: def save(self, path, sentences):
      with open(path, "w") as f:
          f.write("\n".join([str(i) for i in sentences]) + "\n")
  
imports: from collections.abc import Iterable
  import nltk
  from tqdm import tqdm
  from underthesea.utils.sp_parallel import is_master
label_desc: Use image node_id 9 for calling the Transform obj's underlying member method code with example usage: obj.save(path, sentences) without return types