'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

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


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation

a=  logging.get_logger(__name__)


a=  {
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

a=  {
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

a=  {'''facebook/blenderbot-3B''': 1_2_8}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def  _UpperCamelCase (     ):




    """simple docstring"""



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







def  _UpperCamelCase (     _a	:	Dict			):




    """simple docstring"""



    __UpperCamelCase	:	int		    =  set()
    __UpperCamelCase	:	List[Any]		    =  word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)			)
        __UpperCamelCase	:	Tuple		    =  char
    return pairs






class 			__lowercase		(						_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''']







     def __init__(		self     ,			_lowerCamelCase     ,			_lowerCamelCase     ,			_lowerCamelCase="replace"     ,			_lowerCamelCase="<s>"     ,			_lowerCamelCase="</s>"     ,			_lowerCamelCase="</s>"     ,			_lowerCamelCase="<s>"     ,			_lowerCamelCase="<unk>"     ,			_lowerCamelCase="<pad>"     ,			_lowerCamelCase="<mask>"     ,			_lowerCamelCase=False     ,			**_lowerCamelCase     ,			):
         __UpperCamelCase	:	Dict		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else bos_token
         __UpperCamelCase	:	List[Any]		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else eos_token
         __UpperCamelCase	:	Optional[int]		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else sep_token
         __UpperCamelCase	:	int		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else cls_token
         __UpperCamelCase	:	Optional[Any]		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else unk_token
         __UpperCamelCase	:	List[str]		    =  AddedToken(_lowerCamelCase     ,			lstrip=_lowerCamelCase     ,			rstrip=_lowerCamelCase    ) if isinstance(_lowerCamelCase     ,			_lowerCamelCase    ) else pad_token

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

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

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

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







     @property
     # Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
     def lowerCAmelCase     (		self    ):
         return len(self.encoder    )







     def lowerCAmelCase     (		self    ):
         return dict(self.encoder     ,			**self.added_tokens_encoder    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         if token in self.cache:
             return self.cache[token]
         __UpperCamelCase	:	int		    =  tuple(_lowerCamelCase    )
         __UpperCamelCase	:	List[Any]		    =  get_pairs(_lowerCamelCase    )

         if not pairs:
             return token

         while True:
             __UpperCamelCase	:	int		    =  min(_lowerCamelCase     ,			key=lambda _lowerCamelCase    : self.bpe_ranks.get(_lowerCamelCase     ,			float('inf'    )    )    )
             if bigram not in self.bpe_ranks:
                 break
             __UpperCamelCase    ,					__UpperCamelCase	:	Any		    =  bigram
             __UpperCamelCase	:	Optional[int]		    =  []
             __UpperCamelCase	:	List[str]		    =  0
             while i < len(_lowerCamelCase    ):
                 try:
                     __UpperCamelCase	:	str		    =  word.index(_lowerCamelCase     ,			_lowerCamelCase    )
                 except ValueError:
                     new_word.extend(word[i:]    )
                     break
                 else:
                     new_word.extend(word[i:j]    )
                     __UpperCamelCase	:	int		    =  j

                 if word[i] == first and i < len(_lowerCamelCase    ) - 1 and word[i + 1] == second:
                     new_word.append(first + second    )
                     i += 2
                 else:
                     new_word.append(word[i]    )
                     i += 1
             __UpperCamelCase	:	Tuple		    =  tuple(_lowerCamelCase    )
             __UpperCamelCase	:	Union[str, Any]		    =  new_word
             if len(_lowerCamelCase    ) == 1:
                 break
             else:
                 __UpperCamelCase	:	List[Any]		    =  get_pairs(_lowerCamelCase    )
         __UpperCamelCase	:	Optional[int]		    =  ' '.join(_lowerCamelCase    )
         __UpperCamelCase	:	List[Any]		    =  word
         return word







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	str		    =  []
         for token in re.findall(self.pat     ,			_lowerCamelCase    ):
             __UpperCamelCase	:	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(_lowerCamelCase    ).split(' '    )    )
         return bpe_tokens







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return self.encoder.get(_lowerCamelCase     ,			self.encoder.get(self.unk_token    )    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return self.decoder.get(_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	Union[str, Any]		    =  ''.join(_lowerCamelCase    )
         __UpperCamelCase	:	List[Any]		    =  bytearray([self.byte_decoder[c] for c in text]    ).decode('utf-8'     ,			errors=self.errors    )
         return text







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase = None    ):
         if not os.path.isdir(_lowerCamelCase    ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""    )
             return
         __UpperCamelCase	:	Any		    =  os.path.join(
             _lowerCamelCase     ,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )
         __UpperCamelCase	:	int		    =  os.path.join(
             _lowerCamelCase     ,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file']    )

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

         __UpperCamelCase	:	str		    =  0
         with open(_lowerCamelCase     ,			'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 _lowerCamelCase    : 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!'    )
                     __UpperCamelCase	:	Any		    =  token_index
                 writer.write(' '.join(_lowerCamelCase    ) + '\n'    )
                 index += 1

         return vocab_file, merge_file







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase = None     ,			_lowerCamelCase = False    ):
         if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=_lowerCamelCase     ,			token_ids_a=_lowerCamelCase     ,			already_has_special_tokens=_lowerCamelCase    )

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







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase = None    ):
         __UpperCamelCase	:	List[str]		    =  [self.sep_token_id]
         __UpperCamelCase	:	Optional[int]		    =  [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 lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase=False     ,			**_lowerCamelCase    ):
         __UpperCamelCase	:	Union[str, Any]		    =  kwargs.pop('add_prefix_space'     ,			self.add_prefix_space    )
         if (is_split_into_words or add_prefix_space) and (len(_lowerCamelCase    ) > 0 and not text[0].isspace()):
             __UpperCamelCase	:	Tuple		    =  ' ' + text
         return (text, kwargs)







     def lowerCAmelCase     (		self     ,			_lowerCamelCase     ,			_lowerCamelCase = None    ):
         return token_ids_a + [self.eos_token_id]







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         __UpperCamelCase	:	Optional[Any]		    =  []
         for is_user, text in conversation.iter_texts():
             if is_user:
                 # We need to space prefix as it's being done within blenderbot
                 inputs.append(' ' + text    )
             else:
                 # Generated responses should contain them already.
                 inputs.append(_lowerCamelCase    )

         __UpperCamelCase	:	List[str]		    =  '  '.join(_lowerCamelCase    )
         __UpperCamelCase	:	int		    =  self.encode(_lowerCamelCase    )
         if len(_lowerCamelCase    ) > self.model_max_length:
             __UpperCamelCase	:	Tuple		    =  input_ids[-self.model_max_length :]
             logger.warning(f"""Trimmed input from conversation as it was longer than {self.model_max_length} tokens."""    )
         return input_ids




'''simple docstring'''
import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class 			__lowercase		(						_lowerCamelCase			,							unittest.TestCase						):







     """simple docstring"""






     SCREAMING_SNAKE_CASE__		   =						OpenAIGPTTokenizer
     SCREAMING_SNAKE_CASE__		   =						OpenAIGPTTokenizerFast
     SCREAMING_SNAKE_CASE__		   =						True
     SCREAMING_SNAKE_CASE__		   =						False







     def lowerCAmelCase     (		self    ):
         super().setUp()

         # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
         __UpperCamelCase	:	List[Any]		    =  [
             'l',
             'o',
             'w',
             'e',
             'r',
             's',
             't',
             'i',
             'd',
             'n',
             'w</w>',
             'r</w>',
             't</w>',
             'lo',
             'low',
             'er</w>',
             'low</w>',
             'lowest</w>',
             'newer</w>',
             'wider</w>',
             '<unk>',
         ]
         __UpperCamelCase	:	List[str]		    =  dict(zip(_lowerCamelCase     ,			range(len(_lowerCamelCase    )    )    )    )
         __UpperCamelCase	:	Union[str, Any]		    =  ['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

         __UpperCamelCase	:	Optional[int]		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['vocab_file']    )
         __UpperCamelCase	:	Tuple		    =  os.path.join(self.tmpdirname     ,			VOCAB_FILES_NAMES['merges_file']    )
         with open(self.vocab_file     ,			'w'    ) as fp:
             fp.write(json.dumps(_lowerCamelCase    )    )
         with open(self.merges_file     ,			'w'    ) as fp:
             fp.write('\n'.join(_lowerCamelCase    )    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase    ):
         return "lower newer", "lower newer"







     def lowerCAmelCase     (		self    ):
         __UpperCamelCase	:	Dict		    =  OpenAIGPTTokenizer(self.vocab_file     ,			self.merges_file    )

         __UpperCamelCase	:	List[Any]		    =  'lower'
         __UpperCamelCase	:	Union[str, Any]		    =  ['low', 'er</w>']
         __UpperCamelCase	:	Tuple		    =  tokenizer.tokenize(_lowerCamelCase    )
         self.assertListEqual(_lowerCamelCase     ,			_lowerCamelCase    )

         __UpperCamelCase	:	List[str]		    =  tokens + ['<unk>']
         __UpperCamelCase	:	Optional[Any]		    =  [1_4, 1_5, 2_0]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase    )     ,			_lowerCamelCase    )







     def lowerCAmelCase     (		self     ,			_lowerCamelCase=1_5    ):
         for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
             with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""    ):
                 __UpperCamelCase	:	Dict		    =  self.rust_tokenizer_class.from_pretrained(_lowerCamelCase     ,			**_lowerCamelCase    )

                 # Simple input
                 __UpperCamelCase	:	int		    =  'This is a simple input'
                 __UpperCamelCase	:	Any		    =  ['This is a simple input 1', 'This is a simple input 2']
                 __UpperCamelCase	:	Union[str, Any]		    =  ('This is a simple input', 'This is a pair')
                 __UpperCamelCase	:	Any		    =  [
                     ('This is a simple input 1', 'This is a simple input 2'),
                     ('This is a simple pair 1', 'This is a simple pair 2'),
                 ]

                 # Simple input tests
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Simple input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Simple input
                 self.assertRaises(
                     _lowerCamelCase     ,			tokenizer_r.batch_encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'     ,			)

                 # Pair input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Pair input
                 self.assertRaises(_lowerCamelCase     ,			tokenizer_r.encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'    )

                 # Pair input
                 self.assertRaises(
                     _lowerCamelCase     ,			tokenizer_r.batch_encode_plus     ,			_lowerCamelCase     ,			max_length=_lowerCamelCase     ,			padding='max_length'     ,			)







     def lowerCAmelCase     (		self    ):
         pass






@require_ftfy
@require_spacy
@require_tokenizers
class 			__lowercase		(						_lowerCamelCase						):







     """simple docstring"""






     pass



