


import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


_snake_case             =     logging.get_logger(__name__)


_snake_case             =     {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all BART models at https://huggingface.co/models?filter=bart
_snake_case             =     {
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
}

_snake_case             =     {
    '''facebook/bart-base''': 10_24,
    '''facebook/bart-large''': 10_24,
    '''facebook/bart-large-mnli''': 10_24,
    '''facebook/bart-large-cnn''': 10_24,
    '''facebook/bart-large-xsum''': 10_24,
    '''yjernite/bart_eli5''': 10_24,
}






@lru_cache()
def 		lowercase_(  ):


  '''simple docstring'''

  lowerCamelCase :					Optional[Any]    =				(
      list(range(ord("!"	)      ,						ord("~"	) + 1	)	) + list(range(ord("¡"	)      ,						ord("¬"	) + 1	)	) + list(range(ord("®"	)      ,						ord("ÿ"	) + 1	)	)
  )
  lowerCamelCase :					Union[str, Any]    =				bs[:]
  lowerCamelCase :					List[Any]    =				0
  for b in range(2**8	):
    if b not in bs:
      bs.append(SCREAMING_SNAKE_CASE_	)
      cs.append(2**8 + n	)
      n += 1
  lowerCamelCase :					int    =				[chr(SCREAMING_SNAKE_CASE_	) for n in cs]
  return dict(zip(SCREAMING_SNAKE_CASE_      ,						SCREAMING_SNAKE_CASE_	)	)






def 		lowercase_(  SCREAMING_SNAKE_CASE_	):


  '''simple docstring'''

  lowerCamelCase :					Any    =				set()
  lowerCamelCase :					str    =				word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)	)
    lowerCamelCase :					Optional[int]    =				char
  return pairs







class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   __A :      str     		=		VOCAB_FILES_NAMES
   __A :      List[Any]     		=		PRETRAINED_VOCAB_FILES_MAP
   __A :      Dict     		=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A :      Optional[Any]     		=		["input_ids", "attention_mask"]






   def __init__(		self						,				__A						,				__A						,				__A="replace"						,				__A="<s>"						,				__A="</s>"						,				__A="</s>"						,				__A="<s>"						,				__A="<unk>"						,				__A="<pad>"						,				__A="<mask>"						,				__A=False						,				**__A						,				):






     """simple docstring"""





     lowerCamelCase :					int    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else bos_token
     lowerCamelCase :					List[Any]    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else eos_token
     lowerCamelCase :					List[str]    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else sep_token
     lowerCamelCase :					str    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else cls_token
     lowerCamelCase :					str    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else unk_token
     lowerCamelCase :					Tuple    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else pad_token

     # Mask token behave like a normal word, i.e. include the space before it
     lowerCamelCase :					List[Any]    =				AddedToken(__A						,				lstrip=__A						,				rstrip=__A ) if isinstance(__A						,				__A ) else mask_token

     super().__init__(
         errors=__A						,				bos_token=__A						,				eos_token=__A						,				unk_token=__A						,				sep_token=__A						,				cls_token=__A						,				pad_token=__A						,				mask_token=__A						,				add_prefix_space=__A						,				**__A						,				)

     with open(__A						,				encoding="utf-8" ) as vocab_handle:
       lowerCamelCase :					List[str]    =				json.load(__A )
     lowerCamelCase :					Union[str, Any]    =				{v: k for k, v in self.encoder.items()}
     lowerCamelCase :					List[Any]    =				errors  # how to handle errors in decoding
     lowerCamelCase :					Tuple    =				bytes_to_unicode()
     lowerCamelCase :					List[Any]    =				{v: k for k, v in self.byte_encoder.items()}
     with open(__A						,				encoding="utf-8" ) as merges_handle:
       lowerCamelCase :					int    =				merges_handle.read().split("\n" )[1:-1]
     lowerCamelCase :					List[str]    =				[tuple(merge.split() ) for merge in bpe_merges]
     lowerCamelCase :					List[Any]    =				dict(zip(__A						,				range(len(__A ) ) ) )
     lowerCamelCase :					Dict    =				{}
     lowerCamelCase :					Optional[int]    =				add_prefix_space

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     lowerCamelCase :					List[str]    =				re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+" )






   @property
   def _snake_case    (		self ):






     """simple docstring"""





     return len(self.encoder )






   def _snake_case    (		self ):






     """simple docstring"""





     return dict(self.encoder						,				**self.added_tokens_encoder )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     if token in self.cache:
       return self.cache[token]
     lowerCamelCase :					Tuple    =				tuple(__A )
     lowerCamelCase :					List[Any]    =				get_pairs(__A )

     if not pairs:
       return token

     while True:
       lowerCamelCase :					Optional[Any]    =				min(__A						,				key=lambda __A : self.bpe_ranks.get(__A						,				float("inf" ) ) )
       if bigram not in self.bpe_ranks:
         break
       lowerCamelCase    ,	lowerCamelCase :					Dict    =				bigram
       lowerCamelCase :					Tuple    =				[]
       lowerCamelCase :					str    =				0
       while i < len(__A ):
         try:
           lowerCamelCase :					str    =				word.index(__A						,				__A )
         except ValueError:
           new_word.extend(word[i:] )
           break
         else:
           new_word.extend(word[i:j] )
           lowerCamelCase :					Optional[Any]    =				j

         if word[i] == first and i < len(__A ) - 1 and word[i + 1] == second:
           new_word.append(first + second )
           i += 2
         else:
           new_word.append(word[i] )
           i += 1
       lowerCamelCase :					Optional[int]    =				tuple(__A )
       lowerCamelCase :					int    =				new_word
       if len(__A ) == 1:
         break
       else:
         lowerCamelCase :					List[str]    =				get_pairs(__A )
     lowerCamelCase :					Optional[int]    =				" ".join(__A )
     lowerCamelCase :					List[Any]    =				word
     return word






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					Any    =				[]
     for token in re.findall(self.pat						,				__A ):
       lowerCamelCase :					str    =				"".join(
           self.byte_encoder[b] for b in token.encode("utf-8" ) )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
       bpe_tokens.extend(bpe_token for bpe_token in self.bpe(__A ).split(" " ) )
     return bpe_tokens






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.encoder.get(__A						,				self.encoder.get(self.unk_token ) )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     return self.decoder.get(__A )






   def _snake_case    (		self						,				__A ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				"".join(__A )
     lowerCamelCase :					Tuple    =				bytearray([self.byte_decoder[c] for c in text] ).decode("utf-8"						,				errors=self.errors )
     return text






   def _snake_case    (		self						,				__A						,				__A = None ):






     """simple docstring"""





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

     with open(__A						,				"w"						,				encoding="utf-8" ) as f:
       f.write(json.dumps(self.encoder						,				indent=2						,				sort_keys=__A						,				ensure_ascii=__A ) + "\n" )

     lowerCamelCase :					Optional[Any]    =				0
     with open(__A						,				"w"						,				encoding="utf-8" ) as writer:
       writer.write("#version: 0.2\n" )
       for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,				key=lambda __A : kv[1] ):
         if index != token_index:
           logger.warning(
               F"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
               " Please check that the tokenizer is not corrupted!" )
           lowerCamelCase :					Any    =				token_index
         writer.write(" ".join(__A ) + "\n" )
         index += 1

     return vocab_file, merge_file






   def _snake_case    (		self						,				__A						,				__A = None ):






     """simple docstring"""





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






   def _snake_case    (		self						,				__A						,				__A = None						,				__A = 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 _snake_case    (		self						,				__A						,				__A = None ):






     """simple docstring"""





     lowerCamelCase :					Dict    =				[self.sep_token_id]
     lowerCamelCase :					Dict    =				[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 _snake_case    (		self						,				__A						,				__A=False						,				**__A ):






     """simple docstring"""





     lowerCamelCase :					List[str]    =				kwargs.pop("add_prefix_space"						,				self.add_prefix_space )
     if (is_split_into_words or add_prefix_space) and (len(__A ) > 0 and not text[0].isspace()):
       lowerCamelCase :					Optional[int]    =				" " + text
     return (text, kwargs)







import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


_snake_case             =     logging.get_logger(__name__)
class 	UpperCAmelCase_					(					UpperCamelCase    ):

   '''simple docstring'''




   def __init__(		self						,				*__A						,				**__A ):






     """simple docstring"""





     warnings.warn(
         "The class DPTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
         " use DPTImageProcessor instead."						,				__A						,				)
     super().__init__(*__A						,				**__A )



