


'''simple docstring'''





import argparse
import json
from typing import List

from ltp import LTP

from transformers.models.bert.tokenization_bert import BertTokenizer






def 							__lowercase     (				__lowerCAmelCase							:       Any     ):
							# 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 							__lowercase     (				__lowerCAmelCase							:       List[str]     ):
							# word like '180' or '身高' or '神'
							for char in word:
														a__    =  ord(__lowerCAmelCase     )
														if not _is_chinese_char(__lowerCAmelCase     ):
																					return 0
							return 1






def 							__lowercase     (				__lowerCAmelCase							:       List[str]     ):
							a__    =  set()

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






def 							__lowercase     (				__lowerCAmelCase							:       Union[str, Any]      ,					__lowerCAmelCase							:       Union[str, Any]     ):
							if not chinese_word_set:
														return bert_tokens
							a__    =  max([len(__lowerCAmelCase     ) for w in chinese_word_set]     )

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






def 							__lowercase     (				__lowerCAmelCase							:       Optional[int]      ,					__lowerCAmelCase							:       int      ,					__lowerCAmelCase							:       Any     ):
							a__    =  []

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

							a__    =  []
							for i in range(0      ,					len(__lowerCAmelCase     )      ,					1_0_0     ):
														a__    =  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     )

							a__    =  []
							for input_ids, chinese_word in zip(__lowerCAmelCase      ,					__lowerCAmelCase     ):
														a__    =  []
														for id in input_ids:
																					a__    =  bert_tokenizer._convert_id_to_token(__lowerCAmelCase     )
																					input_tokens.append(__lowerCAmelCase     )
														a__    =  add_sub_symbol(__lowerCAmelCase      ,					__lowerCAmelCase     )
														a__    =  []
														# 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] == "##":
																												a__    =  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 							__lowercase     (				__lowerCAmelCase							:       List[Any]     ):
							# 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__    =  f.readlines()
							a__    =  [line.strip() for line in data if len(__lowerCAmelCase     ) > 0 and not line.isspace()]  # avoid delimiter like '\u2029'
							a__    =  LTP(args.ltp     )  # faster in GPU device
							a__    =  BertTokenizer.from_pretrained(args.bert     )

							a__    =  prepare_ref(__lowerCAmelCase      ,					__lowerCAmelCase      ,					__lowerCAmelCase     )

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


if __name__ == "__main__":
						snake_case							: Dict      =   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''',
						)

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








def 							__lowercase     (				__lowerCAmelCase							:       list      ,					__lowerCAmelCase							:       list      ,					__lowerCAmelCase							:       int     ):
							if len(__lowerCAmelCase     ) != len(__lowerCAmelCase     ):
														raise ValueError('The length of profit and weight must be same.'     )
							if max_weight <= 0:
														raise ValueError('max_weight must greater than zero.'     )
							if any(p < 0 for p in profit     ):
														raise ValueError('Profit can not be negative.'     )
							if any(w < 0 for w in weight     ):
														raise ValueError('Weight can not be negative.'     )

							# List created to store profit gained for the 1kg in case of each weight
							# respectively.  Calculate and append profit/weight for each element.
							a__    =  [p / w for p, w in zip(__lowerCAmelCase      ,					__lowerCAmelCase     )]

							# Creating a copy of the list and sorting profit/weight in ascending order
							a__    =  sorted(__lowerCAmelCase     )

							# declaring useful variables
							a__    =  len(__lowerCAmelCase     )
							a__    =  0
							a__    =  0
							a__    =  0

							# loop till the total weight do not reach max limit e.g. 15 kg and till i<length
							while limit <= max_weight and i < length:
														# flag value for encountered greatest element in sorted_profit_by_weight
														a__    =  sorted_profit_by_weight[length - i - 1]
														a__    =  profit_by_weight.index(__lowerCAmelCase     )
														a__    =  -1

														# check if the weight encountered is less than the total weight
														# encountered before.
														if max_weight - limit >= weight[index]:
																					limit += weight[index]
																					# Adding profit gained for the given weight 1 ===
																					# weight[index]/weight[index]
																					gain += 1 * profit[index]
														else:
																					# Since the weight encountered is greater than limit, therefore take the
																					# required number of remaining kgs and calculate profit for it.
																					# weight remaining / weight[index]
																					gain += (max_weight - limit) / weight[index] * profit[index]
																					break
														i += 1
							return gain


if __name__ == "__main__":
						print(
						    '''Input profits, weights, and then max_weight (all positive ints) separated by '''
						    '''spaces.'''
						)

						snake_case							: Tuple      =   [int(x) for x in input('''Input profits separated by spaces: ''').split()]
						snake_case							: Optional[int]      =   [int(x) for x in input('''Input weights separated by spaces: ''').split()]
						snake_case							: List[str]      =   int(input('''Max weight allowed: '''))

						# Function Call
						calc_profit(profit, weight, max_weight)




