"""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


SCREAMING_SNAKE_CASE__       =	logging.get_logger(__name__)

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

SCREAMING_SNAKE_CASE__       =	{
    "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"
        )
    },
}

SCREAMING_SNAKE_CASE__       =	{"Helsinki-NLP/opus-mt-en-de": 512}
SCREAMING_SNAKE_CASE__       =	{}



class 	lowerCAmelCase_     (      lowerCAmelCase       ):



				"""simple docstring"""
				_lowerCAmelCase  :     Optional[Any]      	=    VOCAB_FILES_NAMES
				_lowerCAmelCase  :     Optional[Any]      	=    PRETRAINED_VOCAB_FILES_MAP
				_lowerCAmelCase  :     Dict      	=    PRETRAINED_INIT_CONFIGURATION
				_lowerCAmelCase  :     Any      	=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_lowerCAmelCase  :     List[Any]      	=    ["""input_ids""", """attention_mask"""]
				_lowerCAmelCase  :     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=5_12		,     lowerCAmelCase = None		,     lowerCAmelCase=False		,     **lowerCAmelCase		,     ):






										"""simple docstring"""

										snake_case             =      {} 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}"""

										snake_case             =      separate_vocabs
										snake_case             =      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:
																snake_case             =      load_json(lowerCAmelCase     )
																snake_case             =      {v: k for k, v in self.target_encoder.items()}
																snake_case             =      []
										else:
																snake_case             =      {v: k for k, v in self.encoder.items()}
																snake_case             =      [k for k in self.encoder if k.startswith('>>'     ) and k.endswith('<<'     )]

										snake_case             =      source_lang
										snake_case             =      target_lang
										snake_case             =      [source_spm, target_spm]

										# load SentencePiece model for pre-processing
										snake_case             =      load_spm(lowerCAmelCase		,     self.sp_model_kwargs     )
										snake_case             =      load_spm(lowerCAmelCase		,     self.sp_model_kwargs     )
										snake_case             =      self.spm_source
										snake_case             =      self.encoder

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

										self._setup_normalizer()

				def 		snake_case			(					self     ):






										"""simple docstring"""

										try:
																from sacremoses import MosesPunctNormalizer

																snake_case             =      MosesPunctNormalizer(self.source_lang     ).normalize
										except (ImportError, FileNotFoundError):
																warnings.warn('Recommended: pip install sacremoses.'     )
																snake_case             =      lambda lowerCAmelCase     : x

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

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

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

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

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

										snake_case             =      self.language_code_re.match(lowerCAmelCase     )
										snake_case             =      [match.group(0     )] if match else []
										return code, self.language_code_re.sub(''		,     lowerCAmelCase     )

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

										snake_case       ,snake_case             =      self.remove_language_code(lowerCAmelCase     )
										snake_case             =      self.current_spm.encode(lowerCAmelCase		,     out_type=lowerCAmelCase     )
										return code + pieces

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

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

				def 		snake_case			(					self		,     lowerCAmelCase		,     **lowerCAmelCase     ):






										"""simple docstring"""

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

				def 		snake_case			(					self		,     lowerCAmelCase		,     **lowerCAmelCase     ):






										"""simple docstring"""

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

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

										snake_case             =      self.spm_source if self._decode_use_source_tokenizer else self.spm_target
										snake_case             =      []
										snake_case             =      ''
										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 + " "
																						snake_case             =      []
																else:
																						current_sub_tokens.append(lowerCAmelCase     )
										out_string += sp_model.decode_pieces(lowerCAmelCase     )
										return out_string.strip()

				def 		snake_case			(					self		,     lowerCAmelCase		,     lowerCAmelCase=None     ):






										"""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 		snake_case			(					self     ):






										"""simple docstring"""

										snake_case             =      self.spm_source
										snake_case             =      self.encoder

				def 		snake_case			(					self     ):






										"""simple docstring"""

										snake_case             =      self.spm_target
										if self.separate_vocabs:
																snake_case             =      self.target_encoder

				@property
				def 		snake_case			(					self     ):






										"""simple docstring"""

										return len(self.encoder     )

				def 		snake_case			(					self		,     lowerCAmelCase		,     lowerCAmelCase = None     ):






										"""simple docstring"""

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

										if self.separate_vocabs:
																snake_case             =      os.path.join(
																    lowerCAmelCase		,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab']		,     )
																snake_case             =      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:
																snake_case             =      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]		,     ):
																snake_case             =      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:
																												snake_case             =      spm_model.serialized_model_proto()
																												fi.write(lowerCAmelCase     )
																						saved_files.append(lowerCAmelCase     )

										return tuple(lowerCAmelCase     )

				def 		snake_case			(					self     ):






										"""simple docstring"""

										return self.get_src_vocab()

				def 		snake_case			(					self     ):






										"""simple docstring"""

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

				def 		snake_case			(					self     ):






										"""simple docstring"""

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

				def __getstate__(					self     ):






										"""simple docstring"""

										snake_case             =      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     ):






										"""simple docstring"""

										snake_case             =      d

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

										snake_case       ,snake_case             =      (load_spm(lowerCAmelCase		,     self.sp_model_kwargs     ) for f in self.spm_files)
										snake_case             =      self.spm_source
										self._setup_normalizer()

				def 		snake_case			(					self		,     *lowerCAmelCase		,     **lowerCAmelCase     ):






										"""simple docstring"""

										return 1

				def 		snake_case			(					self		,     lowerCAmelCase     ):






										"""simple docstring"""

										snake_case             =      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 		snake_case			(					self		,     lowerCAmelCase		,     lowerCAmelCase = None		,     lowerCAmelCase = False     ):






										"""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  lowerCAmelCase__     (      _UpperCamelCase							:					str			,      _UpperCamelCase							:					Dict[str, Any]       )       ->					sentencepiece.SentencePieceProcessor:





						"""simple docstring"""






						snake_case             =      sentencepiece.SentencePieceProcessor(**_UpperCamelCase       )
						spm.Load(_UpperCamelCase       )
						return spm





def  lowerCAmelCase__     (      _UpperCamelCase							:					List[Any]			,      _UpperCamelCase							:					str       )       ->					None:





						"""simple docstring"""






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





def  lowerCAmelCase__     (      _UpperCamelCase							:					str       )       ->					Union[Dict, List]:





						"""simple docstring"""






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



"""simple docstring"""
from typing import TYPE_CHECKING

from ...utils import _LazyModule


SCREAMING_SNAKE_CASE__       =	{"tokenization_bert_japanese": ["BertJapaneseTokenizer", "CharacterTokenizer", "MecabTokenizer"]}


if TYPE_CHECKING:
					from .tokenization_bert_japanese import BertJapaneseTokenizer, CharacterTokenizer, MecabTokenizer

else:
					import sys

					SCREAMING_SNAKE_CASE__       =	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)


