


"""simple docstring"""


import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{"vocab_file": "spiece.model"}

_snake_case          =							{
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

_snake_case          =							{
    "google/bigbird-roberta-base": 4096,
    "google/bigbird-roberta-large": 4096,
    "google/bigbird-base-trivia-itc": 4096,
}



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				List[Any]             =    VOCAB_FILES_NAMES
    a_    :				List[Any]             =    PRETRAINED_VOCAB_FILES_MAP
    a_    :				Optional[Any]             =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    a_    :				int             =    ['input_ids', 'attention_mask']
    a_    :				List[int]             =    []
    def __init__( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					int="<unk>"							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="<s>"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]="</s>"							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]="<pad>"							,					SCREAMING_SNAKE_CASE__							:					Optional[int]="[SEP]"							,					SCREAMING_SNAKE_CASE__							:					int="[MASK]"							,					SCREAMING_SNAKE_CASE__							:					List[Any]="[CLS]"							,					SCREAMING_SNAKE_CASE__							:					Optional[Dict[str, Any]] = None							,					**SCREAMING_SNAKE_CASE__							:					List[str]							,					):
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else bos_token
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else eos_token
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else unk_token
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else pad_token
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else cls_token
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else sep_token

          # Mask token behave like a normal word, i.e. include the space before it
          lowerCamelCase__           =		AddedToken(SCREAMING_SNAKE_CASE__							,					lstrip=SCREAMING_SNAKE_CASE__							,					rstrip=SCREAMING_SNAKE_CASE__				) if isinstance(SCREAMING_SNAKE_CASE__							,					SCREAMING_SNAKE_CASE__				) else mask_token

          lowerCamelCase__           =		{} if sp_model_kwargs is None else sp_model_kwargs

          super().__init__(
              bos_token=SCREAMING_SNAKE_CASE__							,					eos_token=SCREAMING_SNAKE_CASE__							,					unk_token=SCREAMING_SNAKE_CASE__							,					pad_token=SCREAMING_SNAKE_CASE__							,					sep_token=SCREAMING_SNAKE_CASE__							,					mask_token=SCREAMING_SNAKE_CASE__							,					cls_token=SCREAMING_SNAKE_CASE__							,					sp_model_kwargs=self.sp_model_kwargs							,					**SCREAMING_SNAKE_CASE__							,					)

          lowerCamelCase__           =		vocab_file

          lowerCamelCase__           =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(SCREAMING_SNAKE_CASE__				)
    @property
    def      _UpperCamelCase       ( self							:					List[Any]				):
          return self.sp_model.get_piece_size()
    def      _UpperCamelCase       ( self							:					Union[str, Any]				):
          lowerCamelCase__           =		{self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__				): i for i in range(self.vocab_size				)}
          vocab.update(self.added_tokens_encoder				)
          return vocab
    def __getstate__( self							:					Any				):
          lowerCamelCase__           =		self.__dict__.copy()
          lowerCamelCase__           =		None
          return state
    def __setstate__( self							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[int]				):
          lowerCamelCase__           =		d

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

          lowerCamelCase__           =		spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(self.vocab_file				)
    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str				):
          return self.sp_model.encode(SCREAMING_SNAKE_CASE__							,					out_type=SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					List[Any]				):
          return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE__				)
    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					str				):
          lowerCamelCase__           =		self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE__				)
          return token
    def      _UpperCamelCase       ( self							:					str							,					SCREAMING_SNAKE_CASE__							:					List[str]				):
          lowerCamelCase__           =		[]
          lowerCamelCase__           =		''
          lowerCamelCase__           =		False
          for token in tokens:
                # make sure that special tokens are not decoded using sentencepiece model
                if token in self.all_special_tokens:
                      if not prev_is_special:
                            out_string += " "
                      out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				) + token
                      lowerCamelCase__           =		True
                      lowerCamelCase__           =		[]
                else:
                      current_sub_tokens.append(SCREAMING_SNAKE_CASE__				)
                      lowerCamelCase__           =		False
          out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE__				)
          return out_string.strip()
    def      _UpperCamelCase       ( self							:					int							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					bool = False							,					SCREAMING_SNAKE_CASE__							:					bool = None							,					SCREAMING_SNAKE_CASE__							:					bool = True							,					**SCREAMING_SNAKE_CASE__							:					Union[str, Any]							,					):
          lowerCamelCase__           =		kwargs.pop('use_source_tokenizer'							,					SCREAMING_SNAKE_CASE__				)

          lowerCamelCase__           =		self.convert_ids_to_tokens(SCREAMING_SNAKE_CASE__							,					skip_special_tokens=SCREAMING_SNAKE_CASE__				)

          # To avoid mixing byte-level and unicode for byte-level BPT
          # we need to build string separately for added tokens and byte-level tokens
          # cf. https://github.com/huggingface/transformers/issues/1133
          lowerCamelCase__           =		[]
          lowerCamelCase__           =		[]
          for token in filtered_tokens:
                if skip_special_tokens and token in self.all_special_ids:
                      continue
                if token in self.added_tokens_encoder:
                      if current_sub_text:
                            sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__				)				)
                            lowerCamelCase__           =		[]
                      sub_texts.append(SCREAMING_SNAKE_CASE__				)
                else:
                      current_sub_text.append(SCREAMING_SNAKE_CASE__				)
          if current_sub_text:
                sub_texts.append(self.convert_tokens_to_string(SCREAMING_SNAKE_CASE__				)				)

          # Mimic the behavior of the Rust tokenizer:
          # No space before [MASK] and [SEP]
          if spaces_between_special_tokens:
                lowerCamelCase__           =		re.sub(R' (\[(MASK|SEP)\])'							,					R'\1'							,					' '.join(SCREAMING_SNAKE_CASE__				)				)
          else:
                lowerCamelCase__           =		''.join(SCREAMING_SNAKE_CASE__				)

          lowerCamelCase__           =		(
              clean_up_tokenization_spaces
              if clean_up_tokenization_spaces is not None
              else self.clean_up_tokenization_spaces
          )
          if clean_up_tokenization_spaces:
                lowerCamelCase__           =		self.clean_up_tokenization(SCREAMING_SNAKE_CASE__				)
                return clean_text
          else:
                return text
    def      _UpperCamelCase       ( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					str							,					SCREAMING_SNAKE_CASE__							:					Optional[str] = None				):
          if not os.path.isdir(SCREAMING_SNAKE_CASE__				):
                logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
                return
          lowerCamelCase__           =		os.path.join(
              SCREAMING_SNAKE_CASE__							,					(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']				)

          if os.path.abspath(self.vocab_file				) != os.path.abspath(SCREAMING_SNAKE_CASE__				) and os.path.isfile(self.vocab_file				):
                copyfile(self.vocab_file							,					SCREAMING_SNAKE_CASE__				)
          elif not os.path.isfile(self.vocab_file				):
                with open(SCREAMING_SNAKE_CASE__							,					'wb'				) as fi:
                      lowerCamelCase__           =		self.sp_model.serialized_model_proto()
                      fi.write(SCREAMING_SNAKE_CASE__				)

          return (out_vocab_file,)
    def      _UpperCamelCase       ( self							:					Tuple							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          lowerCamelCase__           =		[self.cls_token_id]
          lowerCamelCase__           =		[self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep
    def      _UpperCamelCase       ( self							:					Any							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None							,					SCREAMING_SNAKE_CASE__							:					bool = False				):
          if already_has_special_tokens:
                return super().get_special_tokens_mask(
                    token_ids_a=SCREAMING_SNAKE_CASE__							,					token_ids_a=SCREAMING_SNAKE_CASE__							,					already_has_special_tokens=SCREAMING_SNAKE_CASE__				)

          if token_ids_a is None:
                return [1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1]
          return [1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1] + ([0] * len(SCREAMING_SNAKE_CASE__				)) + [1]


    def      _UpperCamelCase       ( self							:					Union[str, Any]							,					SCREAMING_SNAKE_CASE__							:					List[int]							,					SCREAMING_SNAKE_CASE__							:					Optional[List[int]] = None				):
          lowerCamelCase__           =		[self.sep_token_id]
          lowerCamelCase__           =		[self.cls_token_id]
          if token_ids_a is None:
                return len(cls + token_ids_a + sep				) * [0]
          return len(cls + token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]







"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case          =							{
    "configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
    "tokenization_m2m_100": ["M2M100Tokenizer"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case          =							[
       "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST",
       "M2M100ForConditionalGeneration",
       "M2M100Model",
       "M2M100PreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
   from .tokenization_mam_aaa import MaMaaaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mam_aaa import (
          M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
          MaMaaaForConditionalGeneration,
          MaMaaaModel,
          MaMaaaPreTrainedModel,
      )


else:
   import sys

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



