



import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			# 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 >= 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 __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			# word like '180' or '身高' or '神'
			for char in word:
						lowercase__   					=			ord(SCREAMING_SNAKE_CASE_					)
						if not _is_chinese_char(SCREAMING_SNAKE_CASE_					):
									return 0
			return 1



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			set()

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



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					):
			if not chinese_word_set:
						return bert_tokens
			lowercase__   					=			max([len(SCREAMING_SNAKE_CASE_					) for w in chinese_word_set]					)

			lowercase__   					=			bert_tokens
			lowercase__					,    lowercase__   					=			0, len(SCREAMING_SNAKE_CASE_					)
			while start < end:
						lowercase__   					=			True
						if is_chinese(bert_word[start]					):
									lowercase__   					=			min(end - start  ,					SCREAMING_SNAKE_CASE_					)
									for i in range(SCREAMING_SNAKE_CASE_  ,					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 __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			[]

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

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

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

			assert len(SCREAMING_SNAKE_CASE_					) == len(SCREAMING_SNAKE_CASE_					)

			return ref_ids



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			# 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:
						lowercase__   					=			f.readlines()
			lowercase__   					=			[line.strip() for line in data if len(SCREAMING_SNAKE_CASE_					) > 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(SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_  ,					SCREAMING_SNAKE_CASE_					)

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


if __name__ == "__main__":
							lowercase_						=       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""",
							)

							lowercase_						=       parser.parse_args()
							main(args)









def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			int(SCREAMING_SNAKE_CASE_					)
			if decimal in (0, 1):  # Exit cases for the recursion
						return str(SCREAMING_SNAKE_CASE_					)
			lowercase__					,    lowercase__   					=			divmod(SCREAMING_SNAKE_CASE_  ,					2					)
			return binary_recursive(SCREAMING_SNAKE_CASE_					) + str(SCREAMING_SNAKE_CASE_					)



def __lowerCAmelCase	(       SCREAMING_SNAKE_CASE_					):
			lowercase__   					=			str(SCREAMING_SNAKE_CASE_					).strip()
			if not number:
						raise ValueError("No input value was provided"					)
			lowercase__   					=			"-" if number.startswith("-"					) else ""
			lowercase__   					=			number.lstrip("-"					)
			if not number.isnumeric():
						raise ValueError("Input value is not an integer"					)
			return f'''{negative}0b{binary_recursive(int(SCREAMING_SNAKE_CASE_					)					)}'''


if __name__ == "__main__":
							from doctest import testmod

							testmod()




