
"""simple docstring"""





import argparse
import json
from typing import List

from ltp import LTP

from transformers import BertTokenizer



def       lowerCamelCase__		(			__snake_case	)							->		Any:


					"""simple docstring"""





					if (
					    (cp >= 0x4E00 and cp <= 0x9FFF)
					    or (cp >= 0x3400 and cp <= 0x4DBF)  #
					    or (cp >= 0x2_0000 and cp <= 0x2_A6DF)  #
					    or (cp >= 0x2_A700 and cp <= 0x2_B73F)  #
					    or (cp >= 0x2_B740 and cp <= 0x2_B81F)  #
					    or (cp >= 0x2_B820 and cp <= 0x2_CEAF)  #
					    or (cp >= 0xF900 and cp <= 0xFAFF)
					    or (cp >= 0x2_F800 and cp <= 0x2_FA1F)  #
					):  #
										return True

					return False



def       lowerCamelCase__		(			__snake_case	)							->		Optional[Any]:


					"""simple docstring"""





					for char in word:
										_UpperCamelCase							 =  ord(__snake_case	)
										if not _is_chinese_char(__snake_case	):
															return 0
					return 1



def       lowerCamelCase__		(			__snake_case	)							->		Optional[int]:


					"""simple docstring"""





					_UpperCamelCase							 =  set()

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



def       lowerCamelCase__		(			__snake_case,     __snake_case	)							->		Dict:


					"""simple docstring"""





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

					_UpperCamelCase							 =  bert_tokens
					_UpperCamelCase ,  _UpperCamelCase							 =  0, len(__snake_case	)
					while start < end:
										_UpperCamelCase							 =  True
										if is_chinese(bert_word[start]	):
															_UpperCamelCase							 =  min(end - start,     __snake_case	)
															for i in range(__snake_case,     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       lowerCamelCase__		(			__snake_case,     __snake_case,     __snake_case	)							->		Optional[int]:


					"""simple docstring"""





					_UpperCamelCase							 =  []

					for i in range(0,     len(__snake_case	),     1_00	):
										_UpperCamelCase							 =  ltp_tokenizer.seg(lines[i : i + 1_00]	)[0]
										_UpperCamelCase							 =  [get_chinese_word(__snake_case	) for r in res]
										ltp_res.extend(__snake_case	)
					assert len(__snake_case	) == len(__snake_case	)

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

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

					assert len(__snake_case	) == len(__snake_case	)

					return ref_ids



def       lowerCamelCase__		(			__snake_case	)							->		Tuple:


					"""simple docstring"""





					with open(args.file_name,     '''r''',     encoding='''utf-8'''	) as f:
										_UpperCamelCase							 =  f.readlines()
					_UpperCamelCase							 =  [line.strip() for line in data if len(__snake_case	) > 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(__snake_case,     __snake_case,     __snake_case	)

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


if __name__ == "__main__":
				_a														=		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""")

				_a														=		parser.parse_args()
				main(args)








"""simple docstring"""





from collections import defaultdict






class     _UpperCAmelCase:



		def __init__(					self				,		__a				,		__a)       ->       Union[str, Any]:






							'''simple docstring'''
							_UpperCamelCase							 =  total  # total no of tasks (N)

							# DP table will have a dimension of (2^M)*N
							# initially all values are set to -1
							_UpperCamelCase							 =  [
							    [-1 for i in range(total + 1)] for j in range(2 ** len(__a))
							]

							_UpperCamelCase							 =  defaultdict(__a)  # stores the list of persons for each task

							# final_mask is used to check if all persons are included by setting all bits
							# to 1
							_UpperCamelCase							 =  (1 << len(__a)) - 1



		def 						UpperCAmelCase							(					self				,		__a				,		__a)       ->       Dict:






							'''simple docstring'''
							# if mask == self.finalmask all persons are distributed tasks, return 1
							if mask == self.final_mask:
												return 1

							# if not everyone gets the task and no more tasks are available, return 0
							if task_no > self.total_tasks:
												return 0

							# if case already considered
							if self.dp[mask][task_no] != -1:
												return self.dp[mask][task_no]

							# Number of ways when we don't this task in the arrangement
							_UpperCamelCase							 =  self.count_ways_until(__a				,		task_no + 1)

							# now assign the tasks one by one to all possible persons and recursively
							# assign for the remaining tasks.
							if task_no in self.task:
												for p in self.task[task_no]:
																	# if p is already given a task
																	if mask & (1 << p):
																						continue

																	# assign this task to p and change the mask value. And recursively
																	# assign tasks with the new mask value.
																	total_ways_util += self.count_ways_until(mask | (1 << p)				,		task_no + 1)

        # save the value.
							_UpperCamelCase							 =  total_ways_util

							return self.dp[mask][task_no]




		def 						UpperCAmelCase							(					self				,		__a)       ->       int:






							'''simple docstring'''
							# Store the list of persons for each task
							for i in range(len(__a)):
												for j in task_performed[i]:
																	self.task[j].append(__a)

        # call the function to fill the DP table, final answer is stored in dp[0][1]
							return self.count_ways_until(0				,		1)


if __name__ == "__main__":
				_a														=		5  # total no of tasks (the value of N)

				# the list of tasks that can be done by M persons.
				_a														=		[[1, 3, 4], [1, 2, 5], [3, 4]]
				print(
				    AssignmentUsingBitmask(task_performed, total_tasks).count_no_of_ways(
				        task_performed
				    )
				)






