






import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer





def 				snake_case  (     lowerCamelCase					):




 '''simple docstring'''







 if (
     (cp >= 0x4e00 and cp <= 0x9fff)
     or (cp >= 0x3400 and cp <= 0x4dbf)  #
     or (cp >= 0x20000 and cp <= 0x2a6df)  #
     or (cp >= 0x2a700 and cp <= 0x2b73f)  #
     or (cp >= 0x2b740 and cp <= 0x2b81f)  #
     or (cp >= 0x2b820 and cp <= 0x2ceaf)  #
     or (cp >= 0xf900 and cp <= 0xfaff)
     or (cp >= 0x2f800 and cp <= 0x2fa1f)  #
 ):  #
  return True

 return False





def 				snake_case  (     lowerCamelCase					):




 '''simple docstring'''







 for char in word:
  __lowercase             =  ord(lowerCAmelCase__					)
  if not _is_chinese_char(lowerCAmelCase__					):
   return 0
 return 1





def 				snake_case  (     lowerCamelCase					):




 '''simple docstring'''







 __lowercase             =  set()

 for token in tokens:
  __lowercase             =  len(lowerCAmelCase__					) > 1 and is_chinese(lowerCAmelCase__					)
  if chinese_word:
   word_set.add(lowerCAmelCase__					)
 __lowercase             =  list(lowerCAmelCase__					)
 return word_list





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase					):




 '''simple docstring'''







 if not chinese_word_set:
  return bert_tokens
 __lowercase             =  max([len(lowerCAmelCase__					) for w in chinese_word_set]					)

 __lowercase             =  bert_tokens
 __lowercase             =  0, len(lowerCAmelCase__					)
 while start < end:
  __lowercase             =  True
  if is_chinese(bert_word[start]					):
   __lowercase             =  min(end - start				,  lowerCAmelCase__					)
   for i in range(lowerCAmelCase__				,  1				,  -1					):
    __lowercase             =  ''.join(bert_word[start : start + i]					)
    if whole_word in chinese_word_set:
     for j in range(start + 1				,  start + i					):
      __lowercase             =  '##' + bert_word[j]
     __lowercase             =  start + i
     __lowercase             =  False
     break
  if single_word:
   start += 1
 return bert_word





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase				,  lowerCamelCase					):




 '''simple docstring'''







 __lowercase             =  []

 for i in range(0				,  len(lowerCAmelCase__					)				,  100					):
  __lowercase             =  ltp_tokenizer.pipeline(lines[i : i + 100]				,  tasks=["""cws"""]					).cws
  __lowercase             =  [get_chinese_word(lowerCAmelCase__					) for r in res]
  ltp_res.extend(lowerCAmelCase__					)
 assert len(lowerCAmelCase__					) == len(lowerCAmelCase__					)

 __lowercase             =  []
 for i in range(0				,  len(lowerCAmelCase__					)				,  100					):
  __lowercase             =  bert_tokenizer(lines[i : i + 100]				,  add_special_tokens=lowerCAmelCase__				,  truncation=lowerCAmelCase__				,  max_length=512					)
  bert_res.extend(res["""input_ids"""]					)
 assert len(lowerCAmelCase__					) == len(lowerCAmelCase__					)

 __lowercase             =  []
 for input_ids, chinese_word in zip(lowerCAmelCase__				,  lowerCAmelCase__					):
  __lowercase             =  []
  for id in input_ids:
   __lowercase             =  bert_tokenizer._convert_id_to_token(lowerCAmelCase__					)
   input_tokens.append(lowerCAmelCase__					)
  __lowercase             =  add_sub_symbol(lowerCAmelCase__				,  lowerCAmelCase__					)
  __lowercase             =  []
  # We only save pos of chinese subwords start with ##, which mean is part of a whole word.
  for i, token in enumerate(lowerCAmelCase__					):
   if token[:2] == "##":
    __lowercase             =  token[2:]
    # save chinese tokens' pos
    if len(lowerCAmelCase__					) == 1 and _is_chinese_char(ord(lowerCAmelCase__					)					):
     ref_id.append(lowerCAmelCase__					)
  ref_ids.append(lowerCAmelCase__					)

 assert len(lowerCAmelCase__					) == len(lowerCAmelCase__					)

 return ref_ids





def 				snake_case  (     lowerCamelCase					):




 '''simple docstring'''







 with open(args.file_name				,  """r"""				,  encoding="""utf-8"""					) as f:
  __lowercase             =  f.readlines()
 __lowercase             =  [line.strip() for line in data if len(lowerCAmelCase__					) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
 __lowercase             =  LTP(args.ltp					)  # faster in GPU device
 __lowercase             =  BertTokenizer.from_pretrained(args.bert					)

 __lowercase             =  prepare_ref(lowerCAmelCase__				,  lowerCAmelCase__				,  lowerCAmelCase__					)

 with open(args.save_path				,  """w"""				,  encoding="""utf-8"""					) as f:
  __lowercase             =  [json.dumps(lowerCAmelCase__					) + '\n' for ref in ref_ids]
  f.writelines(lowerCAmelCase__					)


if __name__ == "__main__":
      __UpperCamelCase      :      Union[str, Any]     						=						argparse.ArgumentParser(description="""prepare_chinese_ref""")
      parser.add_argument(
          """--file_name""",
          required=False,
          type=str,
          default="""./resources/chinese-demo.txt""",
          help="""file need process, same as training data in lm""",
      )
      parser.add_argument(
          """--ltp""",
          required=False,
          type=str,
          default="""./resources/ltp""",
          help="""resources for LTP tokenizer, usually a path""",
      )
      parser.add_argument(
          """--bert""",
          required=False,
          type=str,
          default="""./resources/robert""",
          help="""resources for Bert tokenizer""",
      )
      parser.add_argument(
          """--save_path""",
          required=False,
          type=str,
          default="""./resources/ref.txt""",
          help="""path to save res""",
      )

      __UpperCamelCase      :      Dict     						=						parser.parse_args()
      main(args)









def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	__lowercase             =  """"""
	for ch in key:
		if ch == " " or ch not in key_no_dups and ch.isalpha():
			key_no_dups += ch
	return key_no_dups





def 				snake_case  (     lowerCamelCase					):




	'''simple docstring'''







	__lowercase             =  [chr(i + 65					) for i in range(26					)]
	# Remove duplicate characters from key
	__lowercase             =  remove_duplicates(key.upper()					)
	__lowercase             =  len(lowerCamelCase					)
	# First fill cipher with key characters
	__lowercase             =  {alphabet[i]: char for i, char in enumerate(lowerCamelCase					)}
	# Then map remaining characters in alphabet to
	# the alphabet from the beginning
	for i in range(len(lowerCamelCase					)				,  26					):
		__lowercase             =  alphabet[i - offset]
		# Ensure we are not mapping letters to letters previously mapped
		while char in key:
			offset -= 1
			__lowercase             =  alphabet[i - offset]
		__lowercase             =  char
	return cipher_alphabet





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







	return "".join(cipher_map.get(lowerCamelCase				,  lowerCamelCase					) for ch in message.upper()					)





def 				snake_case  (     lowerCamelCase				,  lowerCamelCase					):




	'''simple docstring'''







	__lowercase             =  {v: k for k, v in cipher_map.items()}
	return "".join(rev_cipher_map.get(lowerCamelCase				,  lowerCamelCase					) for ch in message.upper()					)





def 				snake_case  (     ):




	'''simple docstring'''







	__lowercase             =  input("""Enter message to encode or decode: """					).strip()
	__lowercase             =  input("""Enter keyword: """					).strip()
	__lowercase             =  input("""Encipher or decipher? E/D:"""					).strip()[0].lower()
	try:
		__lowercase             =  {"""e""": encipher, """d""": decipher}[option]
	except KeyError:
		raise KeyError("""invalid input option"""					)
	__lowercase             =  create_cipher_map(lowerCamelCase					)
	print(func(lowerCamelCase				,  lowerCamelCase					)					)


if __name__ == "__main__":
						import doctest

						doctest.testmod()
						main()

