





"""simple docstring"""


class    __SCREAMING_SNAKE_CASE			:







  '''simple docstring'''


  def __init__(						self      :				Tuple		)						-> Union[str, Any]:
        _UpperCamelCase					:		Optional[Any]  =				[]
        _UpperCamelCase					:		Dict  =				0
        _UpperCamelCase					:		List[str]  =				0

  def __str__(						self      :				Optional[int]		)						-> List[Any]:
        _UpperCamelCase					:		Optional[int]  =				"<" + str(self.entries		)[1:-1] + ">"
        return printed

  def       __SCREAMING_SNAKE_CASE (						self      :				Dict    ,      __a      :				Optional[int]		)						-> str:
        self.entries.append(__a		)
        _UpperCamelCase					:		int  =				self.length + 1

  def       __SCREAMING_SNAKE_CASE (						self      :				str		)						-> Tuple:
        _UpperCamelCase					:		Tuple  =				self.length - 1
        _UpperCamelCase					:		Optional[int]  =				self.entries[self.front]
        # self.front-=1
        # self.entries = self.entries[self.front:]
        _UpperCamelCase					:		Union[str, Any]  =				self.entries[1:]
        return dequeued

  def       __SCREAMING_SNAKE_CASE (						self      :				List[str]    ,      __a      :				Optional[Any]		)						-> str:
        for _ in range(__a		):
              self.put(self.get()		)

  def       __SCREAMING_SNAKE_CASE (						self      :				List[str]		)						-> Any:
        return self.entries[0]

  def       __SCREAMING_SNAKE_CASE (						self      :				Any		)						-> List[Any]:
        return self.length







"""simple docstring"""


import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
  from .tokenization_reformer import ReformerTokenizer
else:
  lowerCamelCase__      =      None


lowerCamelCase__      =      logging.get_logger(__name__)


lowerCamelCase__      =      "▁"

lowerCamelCase__      =      {"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

lowerCamelCase__      =      {
    "vocab_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"
        )
    },
    "tokenizer_file": {
        "google/reformer-crime-and-punishment": (
            "https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"
        )
    },
}

lowerCamelCase__      =      {
    "google/reformer-crime-and-punishment": 52_4288,
}



class    __SCREAMING_SNAKE_CASE			(  _UpperCamelCase      ):







  '''simple docstring'''


  SCREAMING_SNAKE_CASE__							:List[str]		   =    VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__							:Any		   =    PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__							:List[Any]		   =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__							:List[Any]		   =    ["input_ids", "attention_mask"]
  SCREAMING_SNAKE_CASE__							:str		   =    ReformerTokenizer

  def __init__(						self      :				List[str]    ,      __a      :				str=None    ,      __a      :				List[Any]=None    ,      __a      :				Optional[int]="</s>"    ,      __a      :				str="<unk>"    ,      __a      :				Dict=[]    ,      **__a      :				Tuple    ,      )						-> Optional[int]:
        super().__init__(
            __a    ,      tokenizer_file=__a    ,      eos_token=__a    ,      unk_token=__a    ,      additional_special_tokens=__a    ,      **__a    ,      )

        _UpperCamelCase					:		Dict  =				vocab_file
        _UpperCamelCase					:		Optional[Any]  =				False if not self.vocab_file else True


  def       __SCREAMING_SNAKE_CASE (						self      :				Dict    ,      __a      :				str    ,      __a      :				Optional[str] = None		)						-> Tuple[str]:
        if not self.can_save_slow_tokenizer:
              raise ValueError(
                  "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
                  "tokenizer."		)

        if not os.path.isdir(__a		):
              logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''		)
              return
        _UpperCamelCase					:		Optional[Any]  =				os.path.join(
            __a    ,      (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

        if os.path.abspath(self.vocab_file		) != os.path.abspath(__a		):
              copyfile(self.vocab_file    ,      __a		)

        return (out_vocab_file,)
