"""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       :    int									=			logging.get_logger(__name__)

UpperCAmelCase       :    List[str]									=			{
    "source_spm": "source.spm",
    "target_spm": "target.spm",
    "vocab": "vocab.json",
    "target_vocab_file": "target_vocab.json",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCAmelCase       :    Dict									=			{
    "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       :    Optional[Any]									=			{"Helsinki-NLP/opus-mt-en-de": 512}
UpperCAmelCase       :    Dict									=			{}

class        __SCREAMING_SNAKE_CASE     (   __lowerCamelCase							):
				UpperCAmelCase	=      VOCAB_FILES_NAMES
				UpperCAmelCase	=      PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase	=      PRETRAINED_INIT_CONFIGURATION
				UpperCAmelCase	=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase	=      ['''input_ids''', '''attention_mask''']
				UpperCAmelCase	=      re.compile('''>>.+<<'''							)  # type: re.Pattern







				def __init__(    self    :List[str]      ,__UpperCAmelCase    :Optional[int]      ,__UpperCAmelCase    :Dict      ,__UpperCAmelCase    :int      ,__UpperCAmelCase    :List[str]=None      ,__UpperCAmelCase    :Dict=None      ,__UpperCAmelCase    :Any=None      ,__UpperCAmelCase    :Union[str, Any]="<unk>"      ,__UpperCAmelCase    :str="</s>"      ,__UpperCAmelCase    :Optional[int]="<pad>"      ,__UpperCAmelCase    :Dict=5_12      ,__UpperCAmelCase    :Optional[Dict[str, Any]] = None      ,__UpperCAmelCase    :Tuple=False      ,**__UpperCAmelCase    :str      ,)      ->					Tuple:




									"""simple docstring"""



									lowerCamelCase__		:   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=lowerCamelCase_      ,target_lang=lowerCamelCase_      ,unk_token=lowerCamelCase_      ,eos_token=lowerCamelCase_      ,pad_token=lowerCamelCase_      ,model_max_length=lowerCamelCase_      ,sp_model_kwargs=self.sp_model_kwargs      ,target_vocab_file=lowerCamelCase_      ,separate_vocabs=lowerCamelCase_      ,**lowerCamelCase_      ,)
									assert Path(lowerCamelCase_  ).exists(), F"""cannot find spm source {source_spm}"""

									lowerCamelCase__		:   Any  				=					separate_vocabs
									lowerCamelCase__		:   List[str]  				=					load_json(lowerCamelCase_  )
									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:
														lowerCamelCase__		:   Tuple  				=					load_json(lowerCamelCase_  )
														lowerCamelCase__		:   Tuple  				=					{v: k for k, v in self.target_encoder.items()}
														lowerCamelCase__		:   List[str]  				=					[]
									else:
														lowerCamelCase__		:   List[str]  				=					{v: k for k, v in self.encoder.items()}
														lowerCamelCase__		:   list  				=					[k for k in self.encoder if k.startswith('''>>'''  ) and k.endswith('''<<'''  )]

									lowerCamelCase__		:   Tuple  				=					source_lang
									lowerCamelCase__		:   Optional[Any]  				=					target_lang
									lowerCamelCase__		:   List[str]  				=					[source_spm, target_spm]

									# load SentencePiece model for pre-processing
									lowerCamelCase__		:   Optional[int]  				=					load_spm(lowerCamelCase_      ,self.sp_model_kwargs  )
									lowerCamelCase__		:   Union[str, Any]  				=					load_spm(lowerCamelCase_      ,self.sp_model_kwargs  )
									lowerCamelCase__		:   Union[str, Any]  				=					self.spm_source
									lowerCamelCase__		:   Optional[int]  				=					self.encoder

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

									self._setup_normalizer()







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




									"""simple docstring"""



									try:
														from sacremoses import MosesPunctNormalizer

														lowerCamelCase__		:   Dict  				=					MosesPunctNormalizer(self.source_lang  ).normalize
									except (ImportError, FileNotFoundError):
														warnings.warn('''Recommended: pip install sacremoses.'''  )
														lowerCamelCase__		:   List[str]  				=					lambda __UpperCAmelCase  : x







				def   lowercase_		(    self    :List[Any]      ,__UpperCAmelCase    :str  )      ->					Optional[int]:




									"""simple docstring"""



									return self.punc_normalizer(lowerCamelCase_  ) if x else ""







				def   lowercase_		(    self    :List[str]      ,__UpperCAmelCase    :Dict  )      ->					Tuple:




									"""simple docstring"""



									return self.current_encoder.get(lowerCamelCase_      ,self.current_encoder[self.unk_token]  )







				def   lowercase_		(    self    :List[Any]      ,__UpperCAmelCase    :str  )      ->					int:




									"""simple docstring"""



									lowerCamelCase__		:   Union[str, Any]  				=					self.language_code_re.match(lowerCamelCase_  )
									lowerCamelCase__		:   list  				=					[match.group(0  )] if match else []
									return code, self.language_code_re.sub(''''''      ,lowerCamelCase_  )







				def   lowercase_		(    self    :Optional[Any]      ,__UpperCAmelCase    :str  )      ->					int:




									"""simple docstring"""



									lowerCamelCase__		:   List[str]  				=					self.remove_language_code(lowerCamelCase_  )
									lowerCamelCase__		:   Any  				=					self.current_spm.encode(lowerCamelCase_      ,out_type=lowerCamelCase_  )
									return code + pieces







				def   lowercase_		(    self    :Tuple      ,__UpperCAmelCase    :int  )      ->					List[str]:




									"""simple docstring"""



									return self.decoder.get(lowerCamelCase_      ,self.unk_token  )







				def   lowercase_		(    self    :str      ,__UpperCAmelCase    :Dict      ,**__UpperCAmelCase    :str  )      ->					Tuple:




									"""simple docstring"""



									return super().batch_decode(lowerCamelCase_      ,**lowerCamelCase_  )







				def   lowercase_		(    self    :List[str]      ,__UpperCAmelCase    :Optional[int]      ,**__UpperCAmelCase    :List[str]  )      ->					Optional[int]:




									"""simple docstring"""



									return super().decode(lowerCamelCase_      ,**lowerCamelCase_  )







				def   lowercase_		(    self    :List[Any]      ,__UpperCAmelCase    :List[str]  )      ->					Optional[int]:




									"""simple docstring"""



									lowerCamelCase__		:   str  				=					self.spm_source if self._decode_use_source_tokenizer else self.spm_target
									lowerCamelCase__		:   str  				=					[]
									lowerCamelCase__		:   List[str]  				=					''
									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(lowerCamelCase_  ) + token + " "
																			lowerCamelCase__		:   int  				=					[]
														else:
																			current_sub_tokens.append(lowerCamelCase_  )
									out_string += sp_model.decode_pieces(lowerCamelCase_  )
									return out_string.strip()







				def   lowercase_		(    self    :Dict      ,__UpperCAmelCase    :Union[str, Any]      ,__UpperCAmelCase    :List[str]=None  )      ->					Dict:




									"""simple docstring"""



									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   lowercase_		(    self    :Any  )      ->					Union[str, Any]:




									"""simple docstring"""



									lowerCamelCase__		:   Any  				=					self.spm_source
									lowerCamelCase__		:   str  				=					self.encoder







				def   lowercase_		(    self    :str  )      ->					List[str]:




									"""simple docstring"""



									lowerCamelCase__		:   int  				=					self.spm_target
									if self.separate_vocabs:
														lowerCamelCase__		:   List[Any]  				=					self.target_encoder







				@property
				def   lowercase_		(    self    :Optional[Any]  )      ->					Dict:




									"""simple docstring"""



									return len(self.encoder  )







				def   lowercase_		(    self    :str      ,__UpperCAmelCase    :str      ,__UpperCAmelCase    :Optional[str] = None  )      ->					Union[str, Any]:




									"""simple docstring"""



									if not os.path.isdir(lowerCamelCase_  ):
														logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""  )
														return
									lowerCamelCase__		:   Dict  				=					[]

									if self.separate_vocabs:
														lowerCamelCase__		:   List[Any]  				=					os.path.join(
														    lowerCamelCase_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']      ,)
														lowerCamelCase__		:   Optional[Any]  				=					os.path.join(
														    lowerCamelCase_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''target_vocab_file''']      ,)
														save_json(self.encoder      ,lowerCamelCase_  )
														save_json(self.target_encoder      ,lowerCamelCase_  )
														saved_files.append(lowerCamelCase_  )
														saved_files.append(lowerCamelCase_  )
									else:
														lowerCamelCase__		:   Dict  				=					os.path.join(
														    lowerCamelCase_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab''']  )
														save_json(self.encoder      ,lowerCamelCase_  )
														saved_files.append(lowerCamelCase_  )

									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]      ,):
														lowerCamelCase__		:   List[str]  				=					os.path.join(
														    lowerCamelCase_      ,(filename_prefix + '''-''' if filename_prefix else '''''') + spm_save_filename  )
														if os.path.abspath(lowerCamelCase_  ) != os.path.abspath(lowerCamelCase_  ) and os.path.isfile(lowerCamelCase_  ):
																			copyfile(lowerCamelCase_      ,lowerCamelCase_  )
																			saved_files.append(lowerCamelCase_  )
														elif not os.path.isfile(lowerCamelCase_  ):
																			with open(lowerCamelCase_      ,'''wb'''  ) as fi:
																								lowerCamelCase__		:   Optional[int]  				=					spm_model.serialized_model_proto()
																								fi.write(lowerCamelCase_  )
																			saved_files.append(lowerCamelCase_  )

									return tuple(lowerCamelCase_  )







				def   lowercase_		(    self    :Tuple  )      ->					Optional[Any]:




									"""simple docstring"""



									return self.get_src_vocab()







				def   lowercase_		(    self    :List[Any]  )      ->					Optional[Any]:




									"""simple docstring"""



									return dict(self.encoder      ,**self.added_tokens_encoder  )







				def   lowercase_		(    self    :Tuple  )      ->					List[str]:




									"""simple docstring"""



									return dict(self.target_encoder      ,**self.added_tokens_decoder  )







				def __getstate__(    self    :str  )      ->					Tuple:




									"""simple docstring"""



									lowerCamelCase__		:   Any  				=					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    :Tuple      ,__UpperCAmelCase    :Dict  )      ->					List[Any]:




									"""simple docstring"""



									lowerCamelCase__		:   List[Any]  				=					d

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

									lowerCamelCase__		:   Optional[Any]  				=					(load_spm(lowerCamelCase_      ,self.sp_model_kwargs  ) for f in self.spm_files)
									lowerCamelCase__		:   Tuple  				=					self.spm_source
									self._setup_normalizer()







				def   lowercase_		(    self    :List[str]      ,*__UpperCAmelCase    :Union[str, Any]      ,**__UpperCAmelCase    :Optional[Any]  )      ->					int:




									"""simple docstring"""



									return 1







				def   lowercase_		(    self    :List[Any]      ,__UpperCAmelCase    :Optional[int]  )      ->					int:




									"""simple docstring"""



									lowerCamelCase__		:   List[Any]  				=					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   lowercase_		(    self    :str      ,__UpperCAmelCase    :List      ,__UpperCAmelCase    :Optional[List] = None      ,__UpperCAmelCase    :bool = False  )      ->					Union[str, Any]:




									"""simple docstring"""



									if already_has_special_tokens:
														return self._special_token_mask(lowerCamelCase_  )
									elif token_ids_a is None:
														return self._special_token_mask(lowerCamelCase_  ) + [1]
									else:
														return self._special_token_mask(token_ids_a + token_ids_a  ) + [1]





def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





					lowerCamelCase__		:   Dict  				=					sentencepiece.SentencePieceProcessor(**__UpperCAmelCase						)
					spm.Load(__UpperCAmelCase						)
					return spm



def 				__a       (			_lowercase							, _lowercase						):







					"""simple docstring"""





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





def 				__a       (			_lowercase						):







					"""simple docstring"""





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







"""simple docstring"""







from __future__ import annotations

import random
from collections.abc import Iterable
from typing import Any, Generic, TypeVar

SCREAMING_SNAKE_CASE						=    TypeVar('T', bound=bool)



class 			_lowerCamelCase      (Generic[T]  ):







				def __init__(			self     :							Any      ,       lowerCamelCase_     :							T    ):

					"""simple docstring"""






					_lowercase			:     T      					=				value
					_lowercase			:     RandomizedHeapNode[T] | None      					=				None
					_lowercase			:     RandomizedHeapNode[T] | None      					=				None







				@property
				def 				__UpperCAmelCase       (			self     :							int    ):

					"""simple docstring"""






					return self._value







				@staticmethod
				def 				__UpperCAmelCase       (			lowerCamelCase_     :							RandomizedHeapNode[T] | None      ,       lowerCamelCase_     :							RandomizedHeapNode[T] | None    ):

					"""simple docstring"""






					if not roota:
						return roota

					if not roota:
						return roota

					if roota.value > roota.value:
						_lowercase					,   _lowercase			:     List[Any]      					=				roota, roota

					if random.choice([True, False]    ):
						_lowercase					,   _lowercase			:     Optional[int]      					=				roota.right, roota.left

					_lowercase			:     Tuple      					=				RandomizedHeapNode.merge(roota.left      ,       lowerCamelCase_    )

					return roota



class 			_lowerCamelCase      (Generic[T]  ):







				def __init__(			self     :							Optional[Any]      ,       lowerCamelCase_     :							Iterable[T] | None = ()    ):

					"""simple docstring"""






					_lowercase			:     RandomizedHeapNode[T] | None      					=				None

					if data:
						for item in data:
							self.insert(lowerCamelCase_    )







				def 				__UpperCAmelCase       (			self     :							Tuple      ,       lowerCamelCase_     :							T    ):

					"""simple docstring"""






					_lowercase			:     str      					=				RandomizedHeapNode.merge(self._root      ,       RandomizedHeapNode(lowerCamelCase_    )    )







				def 				__UpperCAmelCase       (			self     :							int    ):

					"""simple docstring"""






					_lowercase			:     Any      					=				self.top()

					if self._root is None:
						return None

					_lowercase			:     List[Any]      					=				RandomizedHeapNode.merge(self._root.left      ,       self._root.right    )

					return result







				def 				__UpperCAmelCase       (			self     :							List[Any]    ):

					"""simple docstring"""






					if not self._root:
						raise IndexError('Can\'t get top element for the empty heap.'    )
					return self._root.value







				def 				__UpperCAmelCase       (			self     :							Any    ):

					"""simple docstring"""






					_lowercase			:     List[Any]      					=				None







				def 				__UpperCAmelCase       (			self     :							Union[str, Any]    ):

					"""simple docstring"""






					_lowercase			:     List[Any]      					=				[]
					while self:
						result.append(self.pop()    )

					return result







				def __bool__(			self     :							List[str]    ):

					"""simple docstring"""






					return self._root is not None


if __name__ == "__main__":
						import doctest

						doctest.testmod()



