"""simple docstring"""






import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer



def 						a_		(      lowerCamelCase ):
				# This defines a "chinese character" as anything in the CJK Unicode block:
				#   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
				#
				# Note that the CJK Unicode block is NOT all Japanese and Korean characters,
				# despite its name. The modern Korean Hangul alphabet is a different block,
				# as is Japanese Hiragana and Katakana. Those alphabets are used to write
				# space-separated words, so they are not treated specially and handled
				# like the all of the other languages.
				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 						a_		(      lowerCamelCase ):
				# word like '180' or '身高' or '神'
				for char in word:
								UpperCAmelCase__    =							ord(lowerCamelCase )
								if not _is_chinese_char(lowerCamelCase ):
												return 0
				return 1



def 						a_		(      lowerCamelCase ):
				UpperCAmelCase__    =							set()

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



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				if not chinese_word_set:
								return bert_tokens
				UpperCAmelCase__    =							max([len(lowerCamelCase ) for w in chinese_word_set] )

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



def 						a_		(      lowerCamelCase      ,    lowerCamelCase      ,    lowerCamelCase ):
				UpperCAmelCase__    =							[]

				for i in range(0      ,    len(lowerCamelCase )      ,    1_0_0 ):
								UpperCAmelCase__    =							ltp_tokenizer.pipeline(lines[i : i + 1_0_0]      ,    tasks=['cws'] ).cws
								UpperCAmelCase__    =							[get_chinese_word(lowerCamelCase ) for r in res]
								ltp_res.extend(lowerCamelCase )
				assert len(lowerCamelCase ) == len(lowerCamelCase )

				UpperCAmelCase__    =							[]
				for i in range(0      ,    len(lowerCamelCase )      ,    1_0_0 ):
								UpperCAmelCase__    =							bert_tokenizer(lines[i : i + 1_0_0]      ,    add_special_tokens=lowerCamelCase      ,    truncation=lowerCamelCase      ,    max_length=5_1_2 )
								bert_res.extend(res['input_ids'] )
				assert len(lowerCamelCase ) == len(lowerCamelCase )

				UpperCAmelCase__    =							[]
				for input_ids, chinese_word in zip(lowerCamelCase      ,    lowerCamelCase ):
								UpperCAmelCase__    =							[]
								for id in input_ids:
												UpperCAmelCase__    =							bert_tokenizer._convert_id_to_token(lowerCamelCase )
												input_tokens.append(lowerCamelCase )
								UpperCAmelCase__    =							add_sub_symbol(lowerCamelCase      ,    lowerCamelCase )
								UpperCAmelCase__    =							[]
								# 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] == "##":
																UpperCAmelCase__    =							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 						a_		(      lowerCamelCase ):
				# For Chinese (Ro)Bert, the best result is from : RoBERTa-wwm-ext (https://github.com/ymcui/Chinese-BERT-wwm)
				# If we want to fine-tune these model, we have to use same tokenizer : LTP (https://github.com/HIT-SCIR/ltp)
				with open(args.file_name      ,    'r'      ,    encoding='utf-8' ) as f:
								UpperCAmelCase__    =							f.readlines()
				UpperCAmelCase__    =							[line.strip() for line in data if len(lowerCamelCase ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
				UpperCAmelCase__    =							LTP(args.ltp )  # faster in GPU device
				UpperCAmelCase__    =							BertTokenizer.from_pretrained(args.bert )

				UpperCAmelCase__    =							prepare_ref(lowerCamelCase      ,    lowerCamelCase      ,    lowerCamelCase )

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


if __name__ == "__main__":
						lowerCAmelCase__						:						List[str]		  =			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',
						)

						lowerCAmelCase__						:						Optional[int]		  =			parser.parse_args()
						main(args)



"""simple docstring"""






import re



def 						a_		(      lowerCamelCase ):
				return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]'      ,    str_ )]



def 						a_		(      lowerCamelCase ):
				UpperCAmelCase__    =							split_input(str_ )
				return "".join(
				    [''.join([char.capitalize() for char in sub_str] ) for sub_str in string_split] )



def 						a_		(      lowerCamelCase      ,    lowerCamelCase      ,    lowerCamelCase ):
				try:
								UpperCAmelCase__    =							split_input(lowerCamelCase )
								if upper:
												UpperCAmelCase__    =							''.join(
												    [
												        separator.join([char.upper() for char in sub_str] )
												        for sub_str in string_split
												    ] )
								else:
												UpperCAmelCase__    =							''.join(
												    [
												        separator.join([char.lower() for char in sub_str] )
												        for sub_str in string_split
												    ] )
								return res_str
				except IndexError:
								return "not valid string"



def 						a_		(      lowerCamelCase ):
				return to_simple_case(lowerCamelCase )



def 						a_		(      lowerCamelCase ):
				try:
								UpperCAmelCase__    =							to_simple_case(lowerCamelCase )
								return res_str[0].lower() + res_str[1:]
				except IndexError:
								return "not valid string"



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return to_complex_case(lowerCamelCase      ,    lowerCamelCase      ,    '_' )



def 						a_		(      lowerCamelCase      ,    lowerCamelCase ):
				return to_complex_case(lowerCamelCase      ,    lowerCamelCase      ,    '-' )


if __name__ == "__main__":
						__import__('doctest').testmod()



