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

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


if is_sentencepiece_available():
    from .tokenization_camembert import CamembertTokenizer
else:
    lowerCamelCase_						     =					None


lowerCamelCase_						     =					logging.get_logger(__name__)

lowerCamelCase_						     =					{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCamelCase_						     =					{
    '''vocab_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/sentencepiece.bpe.model''',
    },
    '''tokenizer_file''': {
        '''camembert-base''': '''https://huggingface.co/camembert-base/resolve/main/tokenizer.json''',
    },
}

lowerCamelCase_						     =					{
    '''camembert-base''': 5_12,
}

lowerCamelCase_						     =					'''▁'''




class      __A(    __lowerCamelCase			):

  """simple docstring"""
  SCREAMING_SNAKE_CASE__         =      VOCAB_FILES_NAMES
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_VOCAB_FILES_MAP
  SCREAMING_SNAKE_CASE__         =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  SCREAMING_SNAKE_CASE__         =      ["""input_ids""", """attention_mask"""]
  SCREAMING_SNAKE_CASE__         =      CamembertTokenizer







  def __init__(self	,      SCREAMING_SNAKE_CASE_=None	,      SCREAMING_SNAKE_CASE_=None	,      SCREAMING_SNAKE_CASE_="<s>"	,      SCREAMING_SNAKE_CASE_="</s>"	,      SCREAMING_SNAKE_CASE_="</s>"	,      SCREAMING_SNAKE_CASE_="<s>"	,      SCREAMING_SNAKE_CASE_="<unk>"	,      SCREAMING_SNAKE_CASE_="<pad>"	,      SCREAMING_SNAKE_CASE_="<mask>"	,      SCREAMING_SNAKE_CASE_=["<s>NOTUSED", "</s>NOTUSED"]	,      **SCREAMING_SNAKE_CASE_	,      ):
       # Mask token behave like a normal word, i.e. include the space before it
       UpperCamelCase__				=    AddedToken(SCREAMING_SNAKE_CASE_	,      lstrip=SCREAMING_SNAKE_CASE_	,      rstrip=SCREAMING_SNAKE_CASE_						) if isinstance(SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_						) else mask_token

       super().__init__(
           SCREAMING_SNAKE_CASE_	,      tokenizer_file=SCREAMING_SNAKE_CASE_	,      bos_token=SCREAMING_SNAKE_CASE_	,      eos_token=SCREAMING_SNAKE_CASE_	,      sep_token=SCREAMING_SNAKE_CASE_	,      cls_token=SCREAMING_SNAKE_CASE_	,      unk_token=SCREAMING_SNAKE_CASE_	,      pad_token=SCREAMING_SNAKE_CASE_	,      mask_token=SCREAMING_SNAKE_CASE_	,      additional_special_tokens=SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_	,      )

       UpperCamelCase__				=    vocab_file
       UpperCamelCase__				=    False if not self.vocab_file else True







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):

       if token_ids_a is None:
            return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       UpperCamelCase__				=    [self.cls_token_id]
       UpperCamelCase__				=    [self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       UpperCamelCase__				=    [self.sep_token_id]
       UpperCamelCase__				=    [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]







  def 	UpperCAmelCase_ (self	,      SCREAMING_SNAKE_CASE_	,      SCREAMING_SNAKE_CASE_ = None						):
       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(SCREAMING_SNAKE_CASE_						):
            logger.error(F"Vocabulary path ({save_directory}) should be a directory"						)
            return
       UpperCamelCase__				=    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_						):
            copyfile(self.vocab_file	,      SCREAMING_SNAKE_CASE_						)

       return (out_vocab_file,)







import warnings

from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor


lowerCamelCase_						     =					logging.get_logger(__name__)




class      __A(    __lowerCamelCase			):

  """simple docstring"""







  def __init__(self	,      *SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						):
       warnings.warn(
           """The class SegformerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
           """ Please use SegformerImageProcessor instead."""	,      SCREAMING_SNAKE_CASE_	,      )
       super().__init__(*SCREAMING_SNAKE_CASE_	,      **SCREAMING_SNAKE_CASE_						)





