


"""simple docstring"""

import os
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


UpperCAmelCase__					=logging.get_logger(__name__)

UpperCAmelCase__					={"vocab_file": "sentencepiece.bpe.model"}

UpperCAmelCase__					={
    "vocab_file": {
        "camembert-base": "https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model",
    }
}

UpperCAmelCase__					={
    "camembert-base": 512,
}

UpperCAmelCase__					="▁"





class  lowerCamelCase__    (		_a     ):
      a			:  List[Any]           =		VOCAB_FILES_NAMES
      a			:  Dict           =		PRETRAINED_VOCAB_FILES_MAP
      a			:  str           =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      a			:  Any           =		["""input_ids""", """attention_mask"""]
      def __init__(		self						:						Any   ,							A_						:						List[str]   ,							A_						:						Optional[int]="<s>"   ,							A_						:						Optional[Any]="</s>"   ,							A_						:						List[str]="</s>"   ,							A_						:						Tuple="<s>"   ,							A_						:						Dict="<unk>"   ,							A_						:						Tuple="<pad>"   ,							A_						:						str="<mask>"   ,							A_						:						List[Any]=["<s>NOTUSED", "</s>NOTUSED"]   ,							A_						:						Optional[Dict[str, Any]] = None   ,							**A_						:						Tuple   ,							):






       '''simple docstring'''


       __lowercase						=						AddedToken(A_   ,							lstrip=A_   ,							rstrip=A_				) if isinstance(A_   ,							A_				) else mask_token

       __lowercase						=						{} if sp_model_kwargs is None else sp_model_kwargs

       super().__init__(
           bos_token=A_   ,							eos_token=A_   ,							unk_token=A_   ,							sep_token=A_   ,							cls_token=A_   ,							pad_token=A_   ,							mask_token=A_   ,							additional_special_tokens=A_   ,							sp_model_kwargs=self.sp_model_kwargs   ,							**A_   ,							)
       __lowercase						=						spm.SentencePieceProcessor(**self.sp_model_kwargs				)
       self.sp_model.Load(str(A_				)				)
       __lowercase						=						vocab_file
       # HACK: These tokens were added by fairseq but don't seem to be actually used when duplicated in the actual
       # sentencepiece vocabulary (this is the case for <s> and </s>
       __lowercase						=						{"""<s>NOTUSED""": 0, """<pad>""": 1, """</s>NOTUSED""": 2, """<unk>""": 3}
       __lowercase						=						len(self.fairseq_tokens_to_ids				)
       __lowercase						=						len(self.sp_model				) + len(self.fairseq_tokens_to_ids				)
       __lowercase						=						{v: k for k, v in self.fairseq_tokens_to_ids.items()}
      def SCREAMING_SNAKE_CASE_						(		self						:						Any   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None				):






       '''simple docstring'''


       if token_ids_a is None:
        return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       __lowercase						=						[self.cls_token_id]
       __lowercase						=						[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None   ,							A_						:						bool = False				):






       '''simple docstring'''


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

       if token_ids_a is None:
        return [1] + ([0] * len(A_				)) + [1]
       return [1] + ([0] * len(A_				)) + [1, 1] + ([0] * len(A_				)) + [1]
      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[Any]   ,							A_						:						List[int]   ,							A_						:						Optional[List[int]] = None				):






       '''simple docstring'''


       __lowercase						=						[self.sep_token_id]
       __lowercase						=						[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 + sep + token_ids_a + sep				) * [0]
      @property
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       return len(self.fairseq_tokens_to_ids				) + len(self.sp_model				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict				):






       '''simple docstring'''


       __lowercase						=						{self.convert_ids_to_tokens(A_				): i for i in range(self.vocab_size				)}
       vocab.update(self.added_tokens_encoder				)
       return vocab
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						str				):






       '''simple docstring'''


       return self.sp_model.encode(A_   ,							out_type=A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						List[str]   ,							A_						:						int				):






       '''simple docstring'''


       if token in self.fairseq_tokens_to_ids:
        return self.fairseq_tokens_to_ids[token]
       elif self.sp_model.PieceToId(A_				) == 0:
        # Convert sentence piece unk token to fairseq unk token index
        return self.unk_token_id
       return self.fairseq_offset + self.sp_model.PieceToId(A_				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						Tuple				):






       '''simple docstring'''


       if index in self.fairseq_ids_to_tokens:
        return self.fairseq_ids_to_tokens[index]
       return self.sp_model.IdToPiece(index - self.fairseq_offset				)
      def SCREAMING_SNAKE_CASE_						(		self						:						Dict   ,							A_						:						Optional[Any]				):






       '''simple docstring'''


       __lowercase						=						[]
       __lowercase						=						""""""
       __lowercase						=						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(A_				) + token
         __lowercase						=						True
         __lowercase						=						[]
        else:
         current_sub_tokens.append(A_				)
         __lowercase						=						False
       out_string += self.sp_model.decode(A_				)
       return out_string.strip()
      def __getstate__(		self						:						List[str]				):






       '''simple docstring'''


       __lowercase						=						self.__dict__.copy()
       __lowercase						=						None
       return state
      def __setstate__(		self						:						Union[str, Any]   ,							A_						:						Union[str, Any]				):






       '''simple docstring'''


       __lowercase						=						d

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

       __lowercase						=						spm.SentencePieceProcessor(**self.sp_model_kwargs				)
       self.sp_model.Load(self.vocab_file				)






      def SCREAMING_SNAKE_CASE_						(		self						:						Optional[int]   ,							A_						:						str   ,							A_						:						Optional[str] = None				):






       '''simple docstring'''


       if not os.path.isdir(A_				):
        logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
        return
       __lowercase						=						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_				) and os.path.isfile(self.vocab_file				):
        copyfile(self.vocab_file   ,							A_				)
       elif not os.path.isfile(self.vocab_file				):
        with open(A_   ,							"""wb"""				) as fi:
         __lowercase						=						self.sp_model.serialized_model_proto()
         fi.write(A_				)

       return (out_vocab_file,)




"""simple docstring"""

import pytest
import requests

from datasets.utils.file_utils import http_head

from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline


@pytest.mark.integration
def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT			):
  with pytest.raises(UpperCamelCase__			):
   requests.request("""GET"""					, """https://huggingface.co"""			)
  with pytest.raises(requests.exceptions.ConnectTimeout			):
   requests.request("""GET"""					, """https://huggingface.co"""					, timeout=1.0			)


@pytest.mark.integration
def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.CONNECTION_FAILS			):
  with pytest.raises(requests.exceptions.ConnectionError			):
   requests.request("""GET"""					, """https://huggingface.co"""			)


def lowerCAmelCase_   (					):






 """simple docstring"""







 with offline(OfflineSimulationMode.HF_DATASETS_OFFLINE_SET_TO_1			):
  with pytest.raises(UpperCamelCase__			):
   http_head("""https://huggingface.co"""			)
