
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


a__				:      List[Any]    		=     logging.get_logger(__name__)

a__				:      Tuple    		=     {
    """source_spm""": """source.spm""",
    """target_spm""": """target.spm""",
    """vocab""": """vocab.json""",
    """target_vocab_file""": """target_vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

a__				:      List[Any]    		=     {
    """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"""
        )
    },
}

a__				:      Tuple    		=     {"""Helsinki-NLP/opus-mt-en-de""": 512}
a__				:      Any    		=     {}






class     a_       (			_snake_case							):



       """simple docstring"""
       __SCREAMING_SNAKE_CASE       :					Optional[Any]						=  VOCAB_FILES_NAMES
       __SCREAMING_SNAKE_CASE       :					str						=  PRETRAINED_VOCAB_FILES_MAP
       __SCREAMING_SNAKE_CASE       :					Dict						=  PRETRAINED_INIT_CONFIGURATION
       __SCREAMING_SNAKE_CASE       :					Optional[Any]						=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __SCREAMING_SNAKE_CASE       :					Optional[int]						=  ["""input_ids""", """attention_mask"""]
       __SCREAMING_SNAKE_CASE       :					List[str]						=  re.compile('>>.+<<'							)  # type: re.Pattern






       def __init__(		self				,       _lowerCamelCase				,       _lowerCamelCase				,       _lowerCamelCase				,       _lowerCamelCase=None				,       _lowerCamelCase=None				,       _lowerCamelCase=None				,       _lowerCamelCase="<unk>"				,       _lowerCamelCase="</s>"				,       _lowerCamelCase="<pad>"				,       _lowerCamelCase=512				,       _lowerCamelCase = None				,       _lowerCamelCase=False				,       **_lowerCamelCase				,       )					->Tuple:
           SCREAMING_SNAKE_CASE				:				Optional[int]				      = {} 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=snake_case_				,       target_lang=snake_case_				,       unk_token=snake_case_				,       eos_token=snake_case_				,       pad_token=snake_case_				,       model_max_length=snake_case_				,       sp_model_kwargs=self.sp_model_kwargs				,       target_vocab_file=snake_case_				,       separate_vocabs=snake_case_				,       **snake_case_				,       )
           assert Path(snake_case_   ).exists(), F"""cannot find spm source {source_spm}"""

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

           SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = source_lang
           SCREAMING_SNAKE_CASE				:				Optional[Any]				      = target_lang
           SCREAMING_SNAKE_CASE				:				str				      = [source_spm, target_spm]

           # load SentencePiece model for pre-processing
           SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = load_spm(snake_case_				,       self.sp_model_kwargs   )
           SCREAMING_SNAKE_CASE				:				Optional[Any]				      = load_spm(snake_case_				,       self.sp_model_kwargs   )
           SCREAMING_SNAKE_CASE				:				List[str]				      = self.spm_source
           SCREAMING_SNAKE_CASE				:				Dict				      = self.encoder

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

           self._setup_normalizer()






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

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






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->Optional[Any]:
           return self.punc_normalizer(snake_case_   ) if x else ""






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->Tuple:
           return self.current_encoder.get(snake_case_				,       self.current_encoder[self.unk_token]   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->Union[str, Any]:
           SCREAMING_SNAKE_CASE				:				str				      = self.language_code_re.match(snake_case_   )
           SCREAMING_SNAKE_CASE				:				list				      = [match.group(0   )] if match else []
           return code, self.language_code_re.sub(''''''				,       snake_case_   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->int:
           SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = self.remove_language_code(snake_case_   )
           SCREAMING_SNAKE_CASE				:				Any				      = self.current_spm.encode(snake_case_				,       out_type=snake_case_   )
           return code + pieces






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->Any:
           return self.decoder.get(snake_case_				,       self.unk_token   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase				,       **_lowerCamelCase   )					->int:
           return super().batch_decode(snake_case_				,       **snake_case_   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase				,       **_lowerCamelCase   )					->Optional[int]:
           return super().decode(snake_case_				,       **snake_case_   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->List[Any]:
           SCREAMING_SNAKE_CASE				:				str				      = self.spm_source if self._decode_use_source_tokenizer else self.spm_target
           SCREAMING_SNAKE_CASE				:				List[Any]				      = []
           SCREAMING_SNAKE_CASE				:				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(snake_case_   ) + token + " "
                   SCREAMING_SNAKE_CASE				:				Union[str, Any]				      = []
               else:
                   current_sub_tokens.append(snake_case_   )
           out_string += sp_model.decode_pieces(snake_case_   )
           return out_string.strip()






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase				,       _lowerCamelCase=None   )					->str:
           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   )					->Optional[Any]:
           SCREAMING_SNAKE_CASE				:				Optional[Any]				      = self.spm_source
           SCREAMING_SNAKE_CASE				:				Tuple				      = self.encoder






       def 	__lowerCAmelCase     (		self   )					->Optional[int]:
           SCREAMING_SNAKE_CASE				:				List[Any]				      = self.spm_target
           if self.separate_vocabs:
               SCREAMING_SNAKE_CASE				:				Dict				      = self.target_encoder






       @property
       def 	__lowerCAmelCase     (		self   )					->Union[str, Any]:
           return len(self.encoder   )






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase				,       _lowerCamelCase = None   )					->Union[str, Any]:
           if not os.path.isdir(snake_case_   ):
               logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""   )
               return
           SCREAMING_SNAKE_CASE				:				int				      = []

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

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

           return tuple(snake_case_   )






       def 	__lowerCAmelCase     (		self   )					->int:
           return self.get_src_vocab()






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






       def 	__lowerCAmelCase     (		self   )					->List[Any]:
           return dict(self.target_encoder				,       **self.added_tokens_decoder   )






       def __getstate__(		self   )					->Optional[Any]:
           SCREAMING_SNAKE_CASE				:				Optional[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				,       _lowerCamelCase   )					->Any:
           SCREAMING_SNAKE_CASE				:				int				      = d

           # for backward compatibility
           if not hasattr(self				,       '''sp_model_kwargs'''   ):
               SCREAMING_SNAKE_CASE				:				str				      = {}

           SCREAMING_SNAKE_CASE				:				str				      = (load_spm(snake_case_				,       self.sp_model_kwargs   ) for f in self.spm_files)
           SCREAMING_SNAKE_CASE				:				Optional[int]				      = self.spm_source
           self._setup_normalizer()






       def 	__lowerCAmelCase     (		self				,       *_lowerCamelCase				,       **_lowerCamelCase   )					->Optional[Any]:
           return 1






       def 	__lowerCAmelCase     (		self				,       _lowerCamelCase   )					->Any:
           SCREAMING_SNAKE_CASE				:				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 	__lowerCAmelCase     (		self				,       _lowerCamelCase				,       _lowerCamelCase = None				,       _lowerCamelCase = False   )					->Dict:
           if already_has_special_tokens:
               return self._special_token_mask(snake_case_   )
           elif token_ids_a is None:
               return self._special_token_mask(snake_case_   ) + [1]
           else:
               return self._special_token_mask(token_ids_a + token_ids_a   ) + [1]







def 				UpperCAmelCase_(    a__ ,						a__   ):



    """simple docstring"""



    SCREAMING_SNAKE_CASE				:				Tuple				      = sentencepiece.SentencePieceProcessor(**a__   )
    spm.Load(a__   )
    return spm







def 				UpperCAmelCase_(    a__ ,						a__   ):



    """simple docstring"""



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







def 				UpperCAmelCase_(    a__   ):



    """simple docstring"""



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


"""simple docstring"""
from ..utils import requires_backends


_a   :      List[str]       =				None






class   _UpperCAmelCase					:
    def __init__(     self    ,     *snake_case_    ,     **snake_case_  ):
      requires_backends(self    ,     ["detectron2"]  )


    @classmethod
    def        lowerCamelCase__						(     cls    ,     *snake_case_    ,     **snake_case_  ):
      requires_backends(cls    ,     ["detectron2"]  )

