






'''simple docstring'''

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

import sentencepiece

from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging


UpperCamelCase      					=logging.get_logger(__name__)

UpperCamelCase      					="▁"

UpperCamelCase      					={
    "vocab_file": "vocab.json",
    "spm_file": "sentencepiece.bpe.model",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCamelCase      					={
    "vocab_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/vocab.json",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/vocab.json",
    },
    "spm_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/sentencepiece.bpe.model",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/sentencepiece.bpe.model",
    },
    "tokenizer_config_file": {
        "facebook/m2m100_418M": "https://huggingface.co/facebook/m2m100_418M/resolve/main/tokenizer_config.json",
        "facebook/m2m100_1.2B": "https://huggingface.co/facebook/m2m100_1.2B/resolve/main/tokenizer_config.json",
    },
}

UpperCamelCase      					={
    "facebook/m2m100_418M": 1024,
}

# fmt: off
UpperCamelCase      					={
    "m2m100": ["af", "am", "ar", "ast", "az", "ba", "be", "bg", "bn", "br", "bs", "ca", "ceb", "cs", "cy", "da", "de", "el", "en", "es", "et", "fa", "ff", "fi", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "he", "hi", "hr", "ht", "hu", "hy", "id", "ig", "ilo", "is", "it", "ja", "jv", "ka", "kk", "km", "kn", "ko", "lb", "lg", "ln", "lo", "lt", "lv", "mg", "mk", "ml", "mn", "mr", "ms", "my", "ne", "nl", "no", "ns", "oc", "or", "pa", "pl", "ps", "pt", "ro", "ru", "sd", "si", "sk", "sl", "so", "sq", "sr", "ss", "su", "sv", "sw", "ta", "th", "tl", "tn", "tr", "uk", "ur", "uz", "vi", "wo", "xh", "yi", "yo", "zh", "zu"],
    "wmt21": ["en", "ha", "is", "ja", "cs", "ru", "zh", "de"]
}




class      A     (   SCREAMING_SNAKE_CASE__    ):






 """simple docstring"""





 __a      :    Optional[Any]			  =    VOCAB_FILES_NAMES
 __a      :    Optional[Any]			  =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __a      :    Any			  =    PRETRAINED_VOCAB_FILES_MAP
 __a      :    Any			  =    ['''input_ids''', '''attention_mask''']

 __a      :    List[int]			  =    []
 __a      :    List[int]			  =    []
 def __init__(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase      ,  __lowerCAmelCase=None      ,  __lowerCAmelCase=None      ,  __lowerCAmelCase="<s>"      ,  __lowerCAmelCase="</s>"      ,  __lowerCAmelCase="</s>"      ,  __lowerCAmelCase="<pad>"      ,  __lowerCAmelCase="<unk>"      ,  __lowerCAmelCase="m2m100"      ,  __lowerCAmelCase = None      ,  __lowerCAmelCase=8      ,  **__lowerCAmelCase      ,  ):
       UpperCamelCase_					: Optional[Any]            =				{} if sp_model_kwargs is None else sp_model_kwargs

       UpperCamelCase_					: Optional[int]            =				language_codes
       UpperCamelCase_					: List[Any]            =				FAIRSEQ_LANGUAGE_CODES[language_codes]
       UpperCamelCase_					: Tuple            =				{lang_code: F"__{lang_code}__" for lang_code in fairseq_language_code}

       UpperCamelCase_					: Any            =				kwargs.get("""additional_special_tokens"""      ,  []			)
       kwargs["additional_special_tokens"] += [
           self.get_lang_token(__lowerCAmelCase			)
           for lang_code in fairseq_language_code
           if self.get_lang_token(__lowerCAmelCase			) not in kwargs["additional_special_tokens"]
       ]

       super().__init__(
           src_lang=__lowerCAmelCase      ,  tgt_lang=__lowerCAmelCase      ,  bos_token=__lowerCAmelCase      ,  eos_token=__lowerCAmelCase      ,  sep_token=__lowerCAmelCase      ,  unk_token=__lowerCAmelCase      ,  pad_token=__lowerCAmelCase      ,  language_codes=__lowerCAmelCase      ,  sp_model_kwargs=self.sp_model_kwargs      ,  num_madeup_words=__lowerCAmelCase      ,  **__lowerCAmelCase      ,  )

       UpperCamelCase_					: Optional[int]            =				vocab_file
       UpperCamelCase_					: Optional[Any]            =				load_json(__lowerCAmelCase			)
       UpperCamelCase_					: Optional[int]            =				{v: k for k, v in self.encoder.items()}
       UpperCamelCase_					: Union[str, Any]            =				spm_file
       UpperCamelCase_					: Tuple            =				load_spm(__lowerCAmelCase      ,  self.sp_model_kwargs			)

       UpperCamelCase_					: Union[str, Any]            =				len(self.encoder			)

       UpperCamelCase_					: Optional[int]            =				{
           self.get_lang_token(__lowerCAmelCase			): self.encoder_size + i for i, lang_code in enumerate(__lowerCAmelCase			)
       }
       UpperCamelCase_					: Any            =				{lang_code: self.encoder_size + i for i, lang_code in enumerate(__lowerCAmelCase			)}
       UpperCamelCase_					: Any            =				{v: k for k, v in self.lang_token_to_id.items()}

       UpperCamelCase_					: Optional[Any]            =				src_lang if src_lang is not None else """en"""
       UpperCamelCase_					: Union[str, Any]            =				tgt_lang
       UpperCamelCase_					: Optional[Any]            =				self.get_lang_id(self._src_lang			)
       self.set_src_lang_special_tokens(self._src_lang			)

       UpperCamelCase_					: str            =				num_madeup_words
 @property
 def 	_UpperCAmelCase							(				self			):
       return len(self.encoder			) + len(self.lang_token_to_id			)
 @property
 def 	_UpperCAmelCase							(				self			):
       return self._src_lang
 @src_lang.setter
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: List[Any]            =				new_src_lang
       self.set_src_lang_special_tokens(self._src_lang			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       return self.sp_model.encode(__lowerCAmelCase      ,  out_type=__lowerCAmelCase			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       if token in self.lang_token_to_id:
             return self.lang_token_to_id[token]
       return self.encoder.get(__lowerCAmelCase      ,  self.encoder[self.unk_token]			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       if index in self.id_to_lang_token:
             return self.id_to_lang_token[index]
       return self.decoder.get(__lowerCAmelCase      ,  self.unk_token			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: Optional[int]            =				[]
       UpperCamelCase_					: Optional[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 += self.sp_model.decode(__lowerCAmelCase			) + token
                   UpperCamelCase_					: str            =				[]
             else:
                   current_sub_tokens.append(__lowerCAmelCase			)
       out_string += self.sp_model.decode(__lowerCAmelCase			)
       return out_string.strip()
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase = None      ,  __lowerCAmelCase = False			):

       if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=__lowerCAmelCase      ,  token_ids_a=__lowerCAmelCase      ,  already_has_special_tokens=__lowerCAmelCase			)

       UpperCamelCase_					: Tuple            =				[1] * len(self.prefix_tokens			)
       UpperCamelCase_					: Optional[int]            =				[1] * len(self.suffix_tokens			)
       if token_ids_a is None:
             return prefix_ones + ([0] * len(__lowerCAmelCase			)) + suffix_ones
       return prefix_ones + ([0] * len(__lowerCAmelCase			)) + ([0] * len(__lowerCAmelCase			)) + suffix_ones
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase = None			):
       if token_ids_a is None:
             return self.prefix_tokens + token_ids_a + self.suffix_tokens
       # We don't expect to process pairs, but leave the pair logic for API consistency
       return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens
 def 	_UpperCAmelCase							(				self			):
       UpperCamelCase_					: List[Any]            =				{self.convert_ids_to_tokens(__lowerCAmelCase			): i for i in range(self.vocab_size			)}
       vocab.update(self.added_tokens_encoder			)
       return vocab
 def __getstate__(				self			):
       UpperCamelCase_					: Optional[Any]            =				self.__dict__.copy()
       UpperCamelCase_					: Dict            =				None
       return state
 def __setstate__(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: str            =				d

       # for backward compatibility
       if not hasattr(self      ,  """sp_model_kwargs"""			):
             UpperCamelCase_					: Optional[int]            =				{}

       UpperCamelCase_					: Optional[Any]            =				load_spm(self.spm_file      ,  self.sp_model_kwargs			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase = None			):
       UpperCamelCase_					: str            =				Path(__lowerCAmelCase			)
       if not save_dir.is_dir():
             raise OSError(F"{save_directory} should be a directory"			)
       UpperCamelCase_					: Optional[int]            =				save_dir / (
           (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
       )
       UpperCamelCase_					: Optional[Any]            =				save_dir / (
           (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
       )

       save_json(self.encoder      ,  __lowerCAmelCase			)

       if os.path.abspath(self.spm_file			) != os.path.abspath(__lowerCAmelCase			) and os.path.isfile(self.spm_file			):
             copyfile(self.spm_file      ,  __lowerCAmelCase			)
       elif not os.path.isfile(self.spm_file			):
             with open(__lowerCAmelCase      ,  """wb"""			) as fi:
                   UpperCamelCase_					: List[Any]            =				self.sp_model.serialized_model_proto()
                   fi.write(__lowerCAmelCase			)

       return (str(__lowerCAmelCase			), str(__lowerCAmelCase			))
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase = "en"      ,  __lowerCAmelCase = None      ,  __lowerCAmelCase = "ro"      ,  **__lowerCAmelCase      ,  ):
       UpperCamelCase_					: Dict            =				src_lang
       UpperCamelCase_					: Optional[Any]            =				tgt_lang
       self.set_src_lang_special_tokens(self.src_lang			)
       return super().prepare_seqaseq_batch(__lowerCAmelCase      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase      ,  __lowerCAmelCase      ,  __lowerCAmelCase      ,  **__lowerCAmelCase			):
       if src_lang is None or tgt_lang is None:
             raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model"""			)
       UpperCamelCase_					: List[Any]            =				src_lang
       UpperCamelCase_					: List[str]            =				self(__lowerCAmelCase      ,  add_special_tokens=__lowerCAmelCase      ,  **__lowerCAmelCase			)
       UpperCamelCase_					: str            =				self.get_lang_id(__lowerCAmelCase			)
       UpperCamelCase_					: Tuple            =				tgt_lang_id
       return inputs
 def 	_UpperCAmelCase							(				self			):
       self.set_src_lang_special_tokens(self.src_lang			)
 def 	_UpperCAmelCase							(				self			):
       self.set_tgt_lang_special_tokens(self.tgt_lang			)
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: Dict            =				self.get_lang_token(__lowerCAmelCase			)
       UpperCamelCase_					: Optional[Any]            =				self.lang_token_to_id[lang_token]
       UpperCamelCase_					: Optional[Any]            =				[self.cur_lang_id]
       UpperCamelCase_					: Any            =				[self.eos_token_id]
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: Any            =				self.get_lang_token(__lowerCAmelCase			)
       UpperCamelCase_					: Dict            =				self.lang_token_to_id[lang_token]
       UpperCamelCase_					: Tuple            =				[self.cur_lang_id]
       UpperCamelCase_					: Optional[Any]            =				[self.eos_token_id]
 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       return self.lang_code_to_token[lang]





 def 	_UpperCAmelCase							(				self      ,  __lowerCAmelCase			):
       UpperCamelCase_					: int            =				self.get_lang_token(__lowerCAmelCase			)
       return self.lang_token_to_id[lang_token]






def 				snake_case       (  a_				:			str     , a_				:			Dict[str, Any]						)							->					sentencepiece.SentencePieceProcessor:





      """simple docstring"""

      UpperCamelCase_					: str            =				sentencepiece.SentencePieceProcessor(**a_						)
      spm.Load(str(a_						)						)
      return spm



def 				snake_case       (  a_				:			str						)							->					Union[Dict, List]:





      """simple docstring"""

      with open(a_     , """r"""						) as f:
            return json.load(a_						)



def 				snake_case       (  a_				:			Any     , a_				:			str						)							->					None:





      """simple docstring"""

      with open(a_     , """w"""						) as f:
            json.dump(a_     , a_     , indent=2						)














'''simple docstring'''

# Lint as: python3
import itertools
import os
import re


UpperCamelCase      					=re.compile(R"([A-Z]+)([A-Z][a-z])")
UpperCamelCase      					=re.compile(R"([a-z\d])([A-Z])")

UpperCamelCase      					=re.compile(R"(?<!_)_(?!_)")
UpperCamelCase      					=re.compile(R"(_{2,})")

UpperCamelCase      					=R"^\w+(\.\w+)*$"

UpperCamelCase      					=R"<>:/\|?*"



def 				snake_case       (  a_				:			Union[str, Any]						)							->					List[Any]:





      """simple docstring"""

      UpperCamelCase_					: Tuple            =				_uppercase_uppercase_re.sub(r"""\1_\2"""     , a_						)
      UpperCamelCase_					: Any            =				_lowercase_uppercase_re.sub(r"""\1_\2"""     , a_						)
      return name.lower()



def 				snake_case       (  a_				:			str						)							->					Optional[int]:





      """simple docstring"""

      UpperCamelCase_					: Dict            =				_single_underscore_re.split(a_						)
      UpperCamelCase_					: Any            =				[_multiple_underscores_re.split(a_						) for n in name]
      return "".join(n.capitalize() for n in itertools.chain.from_iterable(a_						) if n != """"""						)



def 				snake_case       (  a_				:			str						)							->					List[Any]:





      """simple docstring"""

      if os.path.basename(a_						) != name:
            raise ValueError(f"Should be a dataset name, not a path: {name}"						)
      return camelcase_to_snakecase(a_						)



def 				snake_case       (  a_				:			int     , a_				:			List[Any]						)							->					List[Any]:





      """simple docstring"""

      if os.path.basename(a_						) != name:
            raise ValueError(f"Should be a dataset name, not a path: {name}"						)
      if not re.match(_split_re     , a_						):
            raise ValueError(f"Split name should match '{_split_re}'' but got '{split}'."						)
      return f"{filename_prefix_for_name(a_						)}-{split}"



def 				snake_case       (  a_				:			str     , a_				:			Optional[int]     , a_				:			List[Any]     , a_				:			Optional[int]=None						)							->					Tuple:





      """simple docstring"""

      UpperCamelCase_					: Tuple            =				filename_prefix_for_split(a_     , a_						)
      if filetype_suffix:
            prefix += f".{filetype_suffix}"
      UpperCamelCase_					: List[str]            =				os.path.join(a_     , a_						)
      return f"{filepath}*"



def 				snake_case       (  a_				:			List[Any]     , a_				:			Optional[int]     , a_				:			List[Any]     , a_				:			int=None     , a_				:			Dict=None						)							->					Any:





      """simple docstring"""

      UpperCamelCase_					: Union[str, Any]            =				filename_prefix_for_split(a_     , a_						)
      UpperCamelCase_					: Union[str, Any]            =				os.path.join(a_     , a_						)

      if shard_lengths:
            UpperCamelCase_					: List[Any]            =				len(a_						)
            UpperCamelCase_					: Optional[int]            =				[f"{prefix}-{shard_id:05d}-of-{num_shards:05d}" for shard_id in range(a_						)]
            if filetype_suffix:
                  UpperCamelCase_					: Tuple            =				[filename + f".{filetype_suffix}" for filename in filenames]
            return filenames
      else:
            UpperCamelCase_					: List[Any]            =				prefix
            if filetype_suffix:
                  filename += f".{filetype_suffix}"
            return [filename]






