





'''simple docstring'''






import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


      if (
          (cp >= 0x4e_00 and cp <= 0x9f_ff)
          or (cp >= 0x34_00 and cp <= 0x4d_bf)  #
          or (cp >= 0x2_00_00 and cp <= 0x2_a6_df)  #
          or (cp >= 0x2_a7_00 and cp <= 0x2_b7_3f)  #
          or (cp >= 0x2_b7_40 and cp <= 0x2_b8_1f)  #
          or (cp >= 0x2_b8_20 and cp <= 0x2_ce_af)  #
          or (cp >= 0xf9_00 and cp <= 0xfa_ff)
          or (cp >= 0x2_f8_00 and cp <= 0x2_fa_1f)  #
      ):  #
            return True

      return False
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


      for char in word:
            _lowerCAmelCase							     =							ord(_lowercase  )
            if not _is_chinese_char(_lowercase  ):
                  return 0
      return 1
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


      _lowerCAmelCase							     =							set()

      for token in tokens:
            _lowerCAmelCase							     =							len(_lowercase  ) > 1 and is_chinese(_lowercase  )
            if chinese_word:
                  word_set.add(_lowercase  )
      _lowerCAmelCase							     =							list(_lowercase  )
      return word_list
def    UpperCamelCase__      (		lowerCAmelCase							,	lowerCAmelCase  ):





      """simple docstring"""


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

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





      """simple docstring"""


      _lowerCAmelCase							     =							[]

      for i in range(0							,	len(_lowercase  )							,	1_00  ):
            _lowerCAmelCase							     =							ltp_tokenizer.pipeline(lines[i : i + 1_00]							,	tasks=["""cws"""]  ).cws
            _lowerCAmelCase							     =							[get_chinese_word(_lowercase  ) for r in res]
            ltp_res.extend(_lowercase  )
      assert len(_lowercase  ) == len(_lowercase  )

      _lowerCAmelCase							     =							[]
      for i in range(0							,	len(_lowercase  )							,	1_00  ):
            _lowerCAmelCase							     =							bert_tokenizer(lines[i : i + 1_00]							,	add_special_tokens=_lowercase							,	truncation=_lowercase							,	max_length=5_12  )
            bert_res.extend(res["""input_ids"""]  )
      assert len(_lowercase  ) == len(_lowercase  )

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

      assert len(_lowercase  ) == len(_lowercase  )

      return ref_ids
def    UpperCamelCase__      (		lowerCAmelCase  ):





      """simple docstring"""


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

      _lowerCAmelCase							     =							prepare_ref(_lowercase							,	_lowercase							,	_lowercase  )

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


if __name__ == "__main__":
      A__				:   Optional[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''',
      )

      A__				:   List[str]      =parser.parse_args()
      main(args)













"""simple docstring"""




from unittest.mock import Mock, patch

from file_transfer.send_file import send_file






@patch("socket.socket"					)
@patch("builtins.open"					)
def       _SCREAMING_SNAKE_CASE		(	_lowercase						:    List[Any]    ,       _lowercase						:    int					) ->str:






	'''simple docstring'''






	a      :		Optional[Any]	=				Mock()
	a      :		Dict	=				conn, Mock()
	a      :		Union[str, Any]	=				iter([1, None]					)
	a      :		Optional[int]	=				lambda _lowercase					: next(_lowercase					)

	# ===== invoke =====
	send_file(filename="mytext.txt"    ,       testing=_lowercase					)

	# ===== ensurance =====
	sock.assert_called_once()
	sock.return_value.bind.assert_called_once()
	sock.return_value.listen.assert_called_once()
	sock.return_value.accept.assert_called_once()
	conn.recv.assert_called_once()

	file.return_value.__enter__.assert_called_once()
	file.return_value.__enter__.return_value.read.assert_called()

	conn.send.assert_called_once()
	conn.close.assert_called_once()
	sock.return_value.shutdown.assert_called_once()
	sock.return_value.close.assert_called_once()


