





'''simple docstring'''






import json
import os
import re
import warnings
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__UpperCamelCase      :   str								=     logging.get_logger(__name__)

__UpperCamelCase      :   int								=     {
    '''source_spm''': '''source.spm''',
    '''target_spm''': '''target.spm''',
    '''vocab''': '''vocab.json''',
    '''target_vocab_file''': '''target_vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

__UpperCamelCase      :   Tuple								=     {
    '''source_spm''': {
        '''Helsinki-NLP/opus-mt-en-de''': '''https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm'''
    },
    '''target_spm''': {
        '''Helsinki-NLP/opus-mt-en-de''': '''https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm'''
    },
    '''vocab''': {
        '''Helsinki-NLP/opus-mt-en-de''': '''https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json'''
    },
    '''tokenizer_config_file''': {
        '''Helsinki-NLP/opus-mt-en-de''': (
            '''https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json'''
        )
    },
}

__UpperCamelCase      :   List[Any]								=     {'''Helsinki-NLP/opus-mt-en-de''': 512}
__UpperCamelCase      :   List[str]								=     {}



class  lowerCamelCase__				(						snake_case_						):


	"""simple docstring"""





	__magic_name__							   =		VOCAB_FILES_NAMES
	__magic_name__							   =		PRETRAINED_VOCAB_FILES_MAP
	__magic_name__							   =		PRETRAINED_INIT_CONFIGURATION
	__magic_name__							   =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__magic_name__							   =		["""input_ids""", """attention_mask"""]
	__magic_name__							   =		re.compile(""">>.+<<"""						)  # type: re.Pattern




	def __init__(					self   ,     UpperCAmelCase__   ,     UpperCAmelCase__   ,     UpperCAmelCase__   ,     UpperCAmelCase__=None   ,     UpperCAmelCase__=None   ,     UpperCAmelCase__=None   ,     UpperCAmelCase__="<unk>"   ,     UpperCAmelCase__="</s>"   ,     UpperCAmelCase__="<pad>"   ,     UpperCAmelCase__=5_1_2   ,     UpperCAmelCase__ = None   ,     UpperCAmelCase__=False   ,     **UpperCAmelCase__   ,     )       ->				None:
					_A :				List[Any]				=  {} if sp_model_kwargs is None else sp_model_kwargs

					super().__init__(
					    # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
					    source_lang=UpperCAmelCase__   ,     target_lang=UpperCAmelCase__   ,     unk_token=UpperCAmelCase__   ,     eos_token=UpperCAmelCase__   ,     pad_token=UpperCAmelCase__   ,     model_max_length=UpperCAmelCase__   ,     sp_model_kwargs=self.sp_model_kwargs   ,     target_vocab_file=UpperCAmelCase__   ,     separate_vocabs=UpperCAmelCase__   ,     **UpperCAmelCase__   ,     )
					assert Path(UpperCAmelCase__			).exists(), F"""cannot find spm source {source_spm}"""

					_A :				Dict				=  separate_vocabs
					_A :				str				=  load_json(UpperCAmelCase__			)
					if self.unk_token not in self.encoder:
									raise KeyError('''<unk> token must be in vocab'''			)
					assert self.pad_token in self.encoder

					if separate_vocabs:
									_A :				List[Any]				=  load_json(UpperCAmelCase__			)
									_A :				Optional[int]				=  {v: k for k, v in self.target_encoder.items()}
									_A :				Union[str, Any]				=  []
					else:
									_A :				Dict				=  {v: k for k, v in self.encoder.items()}
									_A :				list				=  [k for k in self.encoder if k.startswith('''>>'''			) and k.endswith('''<<'''			)]

					_A :				List[str]				=  source_lang
					_A :				int				=  target_lang
					_A :				Dict				=  [source_spm, target_spm]

					# load SentencePiece model for pre-processing
					_A :				Optional[Any]				=  load_spm(UpperCAmelCase__   ,     self.sp_model_kwargs			)
					_A :				Tuple				=  load_spm(UpperCAmelCase__   ,     self.sp_model_kwargs			)
					_A :				Dict				=  self.spm_source
					_A :				int				=  self.encoder

					# Multilingual target side: default to using first supported language code.

					self._setup_normalizer()




	def 				_lowerCamelCase				(					self			)       ->				str:
					try:
									from sacremoses import MosesPunctNormalizer

									_A :				Union[str, Any]				=  MosesPunctNormalizer(self.source_lang			).normalize
					except (ImportError, FileNotFoundError):
									warnings.warn('''Recommended: pip install sacremoses.'''			)
									_A :				Union[str, Any]				=  lambda UpperCAmelCase__			: x




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				str:
					return self.punc_normalizer(UpperCAmelCase__			) if x else ""




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				List[str]:
					return self.current_encoder.get(UpperCAmelCase__   ,     self.current_encoder[self.unk_token]			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				str:
					_A :				str				=  self.language_code_re.match(UpperCAmelCase__			)
					_A :				list				=  [match.group(0			)] if match else []
					return code, self.language_code_re.sub(''''''   ,     UpperCAmelCase__			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				List[str]:
					_A	,       _A :				Dict				=  self.remove_language_code(UpperCAmelCase__			)
					_A :				Tuple				=  self.current_spm.encode(UpperCAmelCase__   ,     out_type=UpperCAmelCase__			)
					return code + pieces




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				str:
					return self.decoder.get(UpperCAmelCase__   ,     self.unk_token			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__   ,     **UpperCAmelCase__			)       ->				List[Any]:
					return super().batch_decode(UpperCAmelCase__   ,     **UpperCAmelCase__			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__   ,     **UpperCAmelCase__			)       ->				Any:
					return super().decode(UpperCAmelCase__   ,     **UpperCAmelCase__			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				str:
					_A :				List[str]				=  self.spm_source if self._decode_use_source_tokenizer else self.spm_target
					_A :				Optional[Any]				=  []
					_A :				int				=  ''''''
					for token in tokens:
									# make sure that special tokens are not decoded using sentencepiece model
									if token in self.all_special_tokens:
													out_string += sp_model.decode_pieces(UpperCAmelCase__			) + token + " "
													_A :				Optional[int]				=  []
									else:
													current_sub_tokens.append(UpperCAmelCase__			)
					out_string += sp_model.decode_pieces(UpperCAmelCase__			)
					return out_string.strip()




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__   ,     UpperCAmelCase__=None			)       ->				List[int]:
					if token_ids_a is None:
									return token_ids_a + [self.eos_token_id]
					# We don't expect to process pairs, but leave the pair logic for API consistency
					return token_ids_a + token_ids_a + [self.eos_token_id]




	def 				_lowerCamelCase				(					self			)       ->				Tuple:
					_A :				str				=  self.spm_source
					_A :				Optional[Any]				=  self.encoder




	def 				_lowerCamelCase				(					self			)       ->				Union[str, Any]:
					_A :				Dict				=  self.spm_target
					if self.separate_vocabs:
									_A :				Union[str, Any]				=  self.target_encoder




	@property
	def 				_lowerCamelCase				(					self			)       ->				int:
					return len(self.encoder			)




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__   ,     UpperCAmelCase__ = None			)       ->				Tuple[str]:
					if not os.path.isdir(UpperCAmelCase__			):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""			)
									return
					_A :				Dict				=  []

					if self.separate_vocabs:
									_A :				int				=  os.path.join(
									    UpperCAmelCase__   ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']   ,     )
									_A :				Optional[int]				=  os.path.join(
									    UpperCAmelCase__   ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''target_vocab_file''']   ,     )
									save_json(self.encoder   ,     UpperCAmelCase__			)
									save_json(self.target_encoder   ,     UpperCAmelCase__			)
									saved_files.append(UpperCAmelCase__			)
									saved_files.append(UpperCAmelCase__			)
					else:
									_A :				Optional[int]				=  os.path.join(
									    UpperCAmelCase__   ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']			)
									save_json(self.encoder   ,     UpperCAmelCase__			)
									saved_files.append(UpperCAmelCase__			)

					for spm_save_filename, spm_orig_path, spm_model in zip(
					    [VOCAB_FILES_NAMES['''source_spm'''], VOCAB_FILES_NAMES['''target_spm''']]   ,     self.spm_files   ,     [self.spm_source, self.spm_target]   ,     ):
									_A :				int				=  os.path.join(
									    UpperCAmelCase__   ,     (filename_prefix + '''-''' if filename_prefix else '''''') + spm_save_filename			)
									if os.path.abspath(UpperCAmelCase__			) != os.path.abspath(UpperCAmelCase__			) and os.path.isfile(UpperCAmelCase__			):
													copyfile(UpperCAmelCase__   ,     UpperCAmelCase__			)
													saved_files.append(UpperCAmelCase__			)
									elif not os.path.isfile(UpperCAmelCase__			):
													with open(UpperCAmelCase__   ,     '''wb'''			) as fi:
																	_A :				List[str]				=  spm_model.serialized_model_proto()
																	fi.write(UpperCAmelCase__			)
													saved_files.append(UpperCAmelCase__			)

					return tuple(UpperCAmelCase__			)




	def 				_lowerCamelCase				(					self			)       ->				Dict:
					return self.get_src_vocab()




	def 				_lowerCamelCase				(					self			)       ->				int:
					return dict(self.encoder   ,     **self.added_tokens_encoder			)




	def 				_lowerCamelCase				(					self			)       ->				Tuple:
					return dict(self.target_encoder   ,     **self.added_tokens_decoder			)




	def __getstate__(					self			)       ->				Dict:
					_A :				Optional[int]				=  self.__dict__.copy()
					state.update(
					    {k: None for k in ['''spm_source''', '''spm_target''', '''current_spm''', '''punc_normalizer''', '''target_vocab_file''']}			)
					return state




	def __setstate__(					self   ,     UpperCAmelCase__			)       ->				None:
					_A :				Tuple				=  d

					# for backward compatibility
					if not hasattr(self   ,     '''sp_model_kwargs'''			):
									_A :				List[str]				=  {}

					_A	,       _A :				int				=  (load_spm(UpperCAmelCase__   ,     self.sp_model_kwargs			) for f in self.spm_files)
					_A :				int				=  self.spm_source
					self._setup_normalizer()




	def 				_lowerCamelCase				(					self   ,     *UpperCAmelCase__   ,     **UpperCAmelCase__			)       ->				List[str]:
					return 1




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__			)       ->				List[Any]:
					_A :				Optional[int]				=  set(self.all_special_ids			)  # call it once instead of inside list comp
					all_special_ids.remove(self.unk_token_id			)  # <unk> is only sometimes special
					return [1 if x in all_special_ids else 0 for x in seq]




	def 				_lowerCamelCase				(					self   ,     UpperCAmelCase__   ,     UpperCAmelCase__ = None   ,     UpperCAmelCase__ = False			)       ->				List[int]:
					if already_has_special_tokens:
									return self._special_token_mask(UpperCAmelCase__			)
					elif token_ids_a is None:
									return self._special_token_mask(UpperCAmelCase__			) + [1]
					else:
									return self._special_token_mask(token_ids_a + token_ids_a			) + [1]





def      lowercase  (  lowerCAmelCase :						str   , lowerCAmelCase :						Dict[str, Any]):



				"""simple docstring"""


				_A :				str				=  sentencepiece.SentencePieceProcessor(**lowerCAmelCase)
				spm.Load(lowerCAmelCase)
				return spm





def      lowercase  (  lowerCAmelCase :						Any   , lowerCAmelCase :						str):



				"""simple docstring"""


				with open(lowerCAmelCase   , '''w''') as f:
								json.dump(lowerCAmelCase   , lowerCAmelCase   , indent=2)





def      lowercase  (  lowerCAmelCase :						str):



				"""simple docstring"""


				with open(lowerCAmelCase   , '''r''') as f:
								return json.load(lowerCAmelCase)







'''simple docstring'''






import sys

sys.set_int_max_str_digits(0)  # type: ignore





def      lowercase  (  lowerCAmelCase :						int):



				"""simple docstring"""


				_A :				List[Any]				=  [0] * 11
				_A :				Optional[Any]				=  [0] * 11

				# mark last 9 numbers
				for _ in range(9):
								_A :				Dict				=  1
								_A :				Optional[int]				=  number // 10
				# flag
				_A :				str				=  True

				# check last 9 numbers for pandigitality

				for x in range(9):
								if not check_last[x + 1]:
												_A :				Dict				=  False
				if not f:
								return f

				# mark first 9 numbers
				_A :				str				=  int(str(lowerCAmelCase)[:9])

				for _ in range(9):
								_A :				Tuple				=  1
								_A :				Union[str, Any]				=  number // 10

				# check first 9 numbers for pandigitality

				for x in range(9):
								if not check_front[x + 1]:
												_A :				Union[str, Any]				=  False
				return f





def      lowercase  (  lowerCAmelCase :						int):



				"""simple docstring"""


				_A :				Tuple				=  [0] * 11

				# mark last 9 numbers
				for _ in range(9):
								_A :				int				=  1
								_A :				Optional[int]				=  number // 10
				# flag
				_A :				List[str]				=  True

				# check last 9 numbers for pandigitality

				for x in range(9):
								if not check_last[x + 1]:
												_A :				Any				=  False
				return f





def      lowercase  (  ):



				"""simple docstring"""


				_A :				Union[str, Any]				=  1
				_A :				Tuple				=  1
				_A :				List[str]				=  2
				# temporary Fibonacci numbers

				_A :				List[str]				=  1
				_A :				str				=  1
				_A :				List[str]				=  2
				# temporary Fibonacci numbers mod 1e9

				# mod m=1e9, done for fast optimisation
				_A :				Any				=  [0] * 100_0000
				_A :				List[Any]				=  10_0000_0000

				for x in range(100_0000):
								_A :				Dict				=  (aa + ba) % m
								_A :				str				=  ba % m
								_A :				Union[str, Any]				=  ca % m
								if checka(lowerCAmelCase):
												_A :				List[str]				=  1

				for x in range(100_0000):
								_A :				str				=  a + b
								_A :				List[str]				=  b
								_A :				int				=  c
								# perform check only if in tocheck
								if tocheck[x + 3] and check(lowerCAmelCase):
												return x + 3  # first 2 already done
				return -1


if __name__ == "__main__":
	print(f'{solution() = }')
