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




		def __init__(  self					:Any			,    _SCREAMING_SNAKE_CASE					:str			,    _SCREAMING_SNAKE_CASE					:Optional[Any]			,    _SCREAMING_SNAKE_CASE					:Union[str, Any]			,    _SCREAMING_SNAKE_CASE					:Any=None			,    _SCREAMING_SNAKE_CASE					:List[str]=None			,    _SCREAMING_SNAKE_CASE					:Optional[Any]=None			,    _SCREAMING_SNAKE_CASE					:str="<unk>"			,    _SCREAMING_SNAKE_CASE					:List[Any]="</s>"			,    _SCREAMING_SNAKE_CASE					:int="<pad>"			,    _SCREAMING_SNAKE_CASE					:int=5_1_2			,    _SCREAMING_SNAKE_CASE					:Optional[Dict[str, Any]] = None			,    _SCREAMING_SNAKE_CASE					:Optional[Any]=False			,    **_SCREAMING_SNAKE_CASE					:Optional[Any]			,    )					->			None:






								'''simple docstring'''






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

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

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

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

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

								self._setup_normalizer()




		def 	_snake_case	(  self					:Tuple)					->			str:






								'''simple docstring'''






								try:
														from sacremoses import MosesPunctNormalizer

														UpperCamelCase_     :	int					     =     MosesPunctNormalizer(self.source_lang).normalize
								except (ImportError, FileNotFoundError):
														warnings.warn("""Recommended: pip install sacremoses.""")
														UpperCamelCase_     :	Dict					     =     lambda _SCREAMING_SNAKE_CASE: x




		def 	_snake_case	(  self					:Any			,    _SCREAMING_SNAKE_CASE					:str)					->			str:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:Union[str, Any]			,    _SCREAMING_SNAKE_CASE					:Dict)					->			int:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:List[Any]			,    _SCREAMING_SNAKE_CASE					:str)					->			Union[str, Any]:






								'''simple docstring'''






								UpperCamelCase_     :	int					     =     self.language_code_re.match(_SCREAMING_SNAKE_CASE)
								UpperCamelCase_     :	list					     =     [match.group(0)] if match else []
								return code, self.language_code_re.sub(""""""			,    _SCREAMING_SNAKE_CASE)




		def 	_snake_case	(  self					:Any			,    _SCREAMING_SNAKE_CASE					:str)					->			List[str]:






								'''simple docstring'''






								UpperCamelCase_     ,UpperCamelCase_     :	Optional[Any]					     =     self.remove_language_code(_SCREAMING_SNAKE_CASE)
								UpperCamelCase_     :	Any					     =     self.current_spm.encode(_SCREAMING_SNAKE_CASE			,    out_type=_SCREAMING_SNAKE_CASE)
								return code + pieces




		def 	_snake_case	(  self					:int			,    _SCREAMING_SNAKE_CASE					:int)					->			str:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:List[str]			,    _SCREAMING_SNAKE_CASE					:Optional[Any]			,    **_SCREAMING_SNAKE_CASE					:Union[str, Any])					->			Tuple:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:Dict			,    _SCREAMING_SNAKE_CASE					:Optional[Any]			,    **_SCREAMING_SNAKE_CASE					:List[str])					->			int:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:Optional[Any]			,    _SCREAMING_SNAKE_CASE					:List[str])					->			str:






								'''simple docstring'''






								UpperCamelCase_     :	Optional[Any]					     =     self.spm_source if self._decode_use_source_tokenizer else self.spm_target
								UpperCamelCase_     :	Optional[Any]					     =     []
								UpperCamelCase_     :	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(_SCREAMING_SNAKE_CASE) + token + " "
																				UpperCamelCase_     :	Optional[Any]					     =     []
														else:
																				current_sub_tokens.append(_SCREAMING_SNAKE_CASE)
								out_string += sp_model.decode_pieces(_SCREAMING_SNAKE_CASE)
								return out_string.strip()




		def 	_snake_case	(  self					:int			,    _SCREAMING_SNAKE_CASE					:int			,    _SCREAMING_SNAKE_CASE					:Union[str, Any]=None)					->			List[int]:






								'''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					:Any)					->			Any:






								'''simple docstring'''






								UpperCamelCase_     :	Optional[int]					     =     self.spm_source
								UpperCamelCase_     :	Any					     =     self.encoder




		def 	_snake_case	(  self					:Dict)					->			List[str]:






								'''simple docstring'''






								UpperCamelCase_     :	Dict					     =     self.spm_target
								if self.separate_vocabs:
														UpperCamelCase_     :	Any					     =     self.target_encoder




		@property
		def 	_snake_case	(  self					:List[Any])					->			int:






								'''simple docstring'''






								return len(self.encoder)




		def 	_snake_case	(  self					:str			,    _SCREAMING_SNAKE_CASE					:str			,    _SCREAMING_SNAKE_CASE					:Optional[str] = None)					->			Tuple[str]:






								'''simple docstring'''






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

								if self.separate_vocabs:
														UpperCamelCase_     :	Union[str, Any]					     =     os.path.join(
														    _SCREAMING_SNAKE_CASE			,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab"""]			,    )
														UpperCamelCase_     :	int					     =     os.path.join(
														    _SCREAMING_SNAKE_CASE			,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""target_vocab_file"""]			,    )
														save_json(self.encoder			,    _SCREAMING_SNAKE_CASE)
														save_json(self.target_encoder			,    _SCREAMING_SNAKE_CASE)
														saved_files.append(_SCREAMING_SNAKE_CASE)
														saved_files.append(_SCREAMING_SNAKE_CASE)
								else:
														UpperCamelCase_     :	Dict					     =     os.path.join(
														    _SCREAMING_SNAKE_CASE			,    (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab"""])
														save_json(self.encoder			,    _SCREAMING_SNAKE_CASE)
														saved_files.append(_SCREAMING_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]			,    ):
														UpperCamelCase_     :	Union[str, Any]					     =     os.path.join(
														    _SCREAMING_SNAKE_CASE			,    (filename_prefix + """-""" if filename_prefix else """""") + spm_save_filename)
														if os.path.abspath(_SCREAMING_SNAKE_CASE) != os.path.abspath(_SCREAMING_SNAKE_CASE) and os.path.isfile(_SCREAMING_SNAKE_CASE):
																				copyfile(_SCREAMING_SNAKE_CASE			,    _SCREAMING_SNAKE_CASE)
																				saved_files.append(_SCREAMING_SNAKE_CASE)
														elif not os.path.isfile(_SCREAMING_SNAKE_CASE):
																				with open(_SCREAMING_SNAKE_CASE			,    """wb""") as fi:
																										UpperCamelCase_     :	Optional[Any]					     =     spm_model.serialized_model_proto()
																										fi.write(_SCREAMING_SNAKE_CASE)
																				saved_files.append(_SCREAMING_SNAKE_CASE)

								return tuple(_SCREAMING_SNAKE_CASE)




		def 	_snake_case	(  self					:Optional[Any])					->			Dict:






								'''simple docstring'''






								return self.get_src_vocab()




		def 	_snake_case	(  self					:List[Any])					->			Dict:






								'''simple docstring'''






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




		def 	_snake_case	(  self					:str)					->			Optional[int]:






								'''simple docstring'''






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




		def __getstate__(  self					:Optional[int])					->			Dict:






								'''simple docstring'''






								UpperCamelCase_     :	Tuple					     =     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					:List[str]			,    _SCREAMING_SNAKE_CASE					:Dict)					->			None:






								'''simple docstring'''






								UpperCamelCase_     :	Dict					     =     d

								# for backward compatibility
								if not hasattr(self			,    """sp_model_kwargs"""):
														UpperCamelCase_     :	Any					     =     {}

								UpperCamelCase_     ,UpperCamelCase_     :	Any					     =     (load_spm(_SCREAMING_SNAKE_CASE			,    self.sp_model_kwargs) for f in self.spm_files)
								UpperCamelCase_     :	Any					     =     self.spm_source
								self._setup_normalizer()




		def 	_snake_case	(  self					:Union[str, Any]			,    *_SCREAMING_SNAKE_CASE					:Any			,    **_SCREAMING_SNAKE_CASE					:Tuple)					->			Any:






								'''simple docstring'''






								return 1




		def 	_snake_case	(  self					:Tuple			,    _SCREAMING_SNAKE_CASE					:Optional[Any])					->			Tuple:






								'''simple docstring'''






								UpperCamelCase_     :	Tuple					     =     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					:List[Any]			,    _SCREAMING_SNAKE_CASE					:List			,    _SCREAMING_SNAKE_CASE					:Optional[List] = None			,    _SCREAMING_SNAKE_CASE					:bool = False)					->			List[int]:






								'''simple docstring'''






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







def 					__magic_name__(       UpperCAmelCase__ :       str							,				UpperCAmelCase__ :       Dict[str, Any]	):
						UpperCamelCase_     :	str					     =     sentencepiece.SentencePieceProcessor(**UpperCAmelCase__	)
						spm.Load(UpperCAmelCase__	)
						return spm
def 					__magic_name__(       UpperCAmelCase__ :       Any							,				UpperCAmelCase__ :       str	):
						with open(UpperCAmelCase__							,				"""w"""	) as f:
												json.dump(UpperCAmelCase__							,				UpperCAmelCase__							,				indent=2	)







def 					__magic_name__(       UpperCAmelCase__ :       str	):
						with open(UpperCAmelCase__							,				"""r"""	) as f:
												return json.load(UpperCAmelCase__	)






'''simple docstring'''


__SCREAMING_SNAKE_CASE						=      {hex(i)[2:]: i for i in range(16)}  # Use [:2] to strip off the leading '0x'
def 					__magic_name__(       UpperCAmelCase__ :       str	):
						UpperCamelCase_     :	str					     =     hex_string.strip().lower()
						if not hex_string:
												raise ValueError("""Empty string was passed to the function"""	)
						UpperCamelCase_     :	Dict					     =     hex_string[0] == """-"""
						if is_negative:
												UpperCamelCase_     :	List[str]					     =     hex_string[1:]
						if not all(char in hex_table for char in hex_string	):
												raise ValueError("""Non-hexadecimal value was passed to the function"""	)
						UpperCamelCase_     :	int					     =     0
						for char in hex_string:
												UpperCamelCase_     :	Any					     =     16 * decimal_number + hex_table[char]
						return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
	from doctest import testmod

	testmod()




