



import argparse
import json
from typing import List

from ltp import LTP

from transformers 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.seg(lines[i : i + 100]  )[0]
						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""",
							    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_								=     parser.parse_args()
							main(args)









def __lowerCAmelCase (     SCREAMING_SNAKE_CASE_  ):
			if upper_limit < 0:
						raise ValueError("Limit for the Catalan sequence must be ≥ 0"  )

			lowercase__					  =				[0] * (upper_limit + 1)

			# Base case: C(0) = C(1) = 1
			lowercase__					  =				1
			if upper_limit > 0:
						lowercase__					  =				1

			# Recurrence relation: C(i) = sum(C(j).C(i-j-1)), from j = 0 to i
			for i in range(2						,  upper_limit + 1  ):
						for j in range(SCREAMING_SNAKE_CASE_  ):
									catalan_list[i] += catalan_list[j] * catalan_list[i - j - 1]

			return catalan_list


if __name__ == "__main__":
							print("""\n********* Catalan Numbers Using Dynamic Programming ************\n""")
							print("""\n*** Enter -1 at any time to quit ***""")
							print("""\nEnter the upper limit (≥ 0) for the Catalan number sequence: """, end="""""")
							try:
														while True:
																					lowercase_								=     int(input().strip())
																					if N < 0:
																												print("""\n********* Goodbye!! ************""")
																												break
																					else:
																												print(F'The Catalan numbers from 0 through {N} are:')
																												print(catalan_numbers(N))
																												print("""Try another upper limit for the sequence: """, end="""""")
							except (NameError, ValueError):
														print("""\n********* Invalid input, goodbye! ************\n""")

							import doctest

							doctest.testmod()




