

import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer






def        snake_case__		(    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 >= 0X4_e_0_0 and cp <= 0X9_f_f_f)
							    or (cp >= 0X3_4_0_0 and cp <= 0X4_d_b_f)  #
							    or (cp >= 0X2_0_0_0_0 and cp <= 0X2_a_6_d_f)  #
							    or (cp >= 0X2_a_7_0_0 and cp <= 0X2_b_7_3_f)  #
							    or (cp >= 0X2_b_7_4_0 and cp <= 0X2_b_8_1_f)  #
							    or (cp >= 0X2_b_8_2_0 and cp <= 0X2_c_e_a_f)  #
							    or (cp >= 0Xf_9_0_0 and cp <= 0Xf_a_f_f)
							    or (cp >= 0X2_f_8_0_0 and cp <= 0X2_f_a_1_f)  #
							):  #
														return True

							return False






def        snake_case__		(    lowerCamelCase_		):
							# word like '180' or '身高' or '神'
							for char in word:
														A      :					List[Any]      		=					ord(__UpperCamelCase		)
														if not _is_chinese_char(__UpperCamelCase		):
																					return 0
							return 1






def        snake_case__		(    lowerCamelCase_		):
							A      :					Optional[int]      		=					set()

							for token in tokens:
														A      :					int      		=					len(__UpperCamelCase		) > 1 and is_chinese(__UpperCamelCase		)
														if chinese_word:
																					word_set.add(__UpperCamelCase		)
							A      :					str      		=					list(__UpperCamelCase		)
							return word_list






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_		):
							if not chinese_word_set:
														return bert_tokens
							A      :					List[Any]      		=					max([len(__UpperCamelCase		) for w in chinese_word_set]		)

							A      :					Tuple      		=					bert_tokens
							A      :					str      		=					0, len(__UpperCamelCase		)
							while start < end:
														A      :					Optional[int]      		=					True
														if is_chinese(bert_word[start]		):
																					A      :					int      		=					min(end - start     ,				__UpperCamelCase		)
																					for i in range(__UpperCamelCase     ,				1     ,				-1		):
																												A      :					Tuple      		=					"".join(bert_word[start : start + i]		)
																												if whole_word in chinese_word_set:
																																			for j in range(start + 1     ,				start + i		):
																																										A      :					List[str]      		=					"##" + bert_word[j]
																																			A      :					Dict      		=					start + i
																																			A      :					Optional[int]      		=					False
																																			break
														if single_word:
																					start += 1
							return bert_word






def        snake_case__		(    lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_		):
							A      :					Optional[Any]      		=					[]

							for i in range(0     ,				len(__UpperCamelCase		)     ,				100		):
														A      :					List[Any]      		=					ltp_tokenizer.seg(lines[i : i + 100]		)[0]
														A      :					List[str]      		=					[get_chinese_word(__UpperCamelCase		) for r in res]
														ltp_res.extend(__UpperCamelCase		)
							assert len(__UpperCamelCase		) == len(__UpperCamelCase		)

							A      :					Dict      		=					[]
							for i in range(0     ,				len(__UpperCamelCase		)     ,				100		):
														A      :					List[str]      		=					bert_tokenizer(lines[i : i + 100]     ,				add_special_tokens=__UpperCamelCase     ,				truncation=__UpperCamelCase     ,				max_length=512		)
														bert_res.extend(res['''input_ids''']		)
							assert len(__UpperCamelCase		) == len(__UpperCamelCase		)

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

							assert len(__UpperCamelCase		) == len(__UpperCamelCase		)

							return ref_ids






def        snake_case__		(    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:
														A      :					Optional[int]      		=					f.readlines()
							A      :					Union[str, Any]      		=					[line.strip() for line in data if len(__UpperCamelCase		) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
							A      :					Any      		=					LTP(args.ltp		)  # faster in GPU device
							A      :					Union[str, Any]      		=					BertTokenizer.from_pretrained(args.bert		)

							A      :					Optional[Any]      		=					prepare_ref(__UpperCamelCase     ,				__UpperCamelCase     ,				__UpperCamelCase		)

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


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

		lowercase			:				Union[str, Any]   =     parser.parse_args()
		main(args)











import unittest

from knapsack import knapsack as k


class 				_a						(       unittest.TestCase			):





							'''simple docstring'''

							def 		_A	(							self				):







											"""simple docstring"""



											a__	:							List[str]      						= 0
											a__	:							Union[str, Any]      						= [0]
											a__	:							Optional[Any]      						= [0]
											a__	:							Tuple      						= len(__UpperCAmelCase				)
											self.assertEqual(k.knapsack(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				) ,					0				)

											a__	:							Optional[Any]      						= [60]
											a__	:							Tuple      						= [10]
											a__	:							Optional[Any]      						= len(__UpperCAmelCase				)
											self.assertEqual(k.knapsack(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				) ,					0				)



							def 		_A	(							self				):







											"""simple docstring"""



											a__	:							Dict      						= 3
											a__	:							Optional[int]      						= [1, 2, 3]
											a__	:							List[Any]      						= [3, 2, 1]
											a__	:							List[Any]      						= len(__UpperCAmelCase				)
											self.assertEqual(k.knapsack(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				) ,					5				)




							def 		_A	(							self				):







											"""simple docstring"""



											a__	:							List[Any]      						= 50
											a__	:							Union[str, Any]      						= [60, 100, 120]
											a__	:							str      						= [10, 20, 30]
											a__	:							Union[str, Any]      						= len(__UpperCAmelCase				)
											self.assertEqual(k.knapsack(__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase ,					__UpperCAmelCase				) ,					220				)


if __name__ == "__main__":
						unittest.main()


