





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": 128}





@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def   lowerCAmelCase_				( )  ->	int:







  """simple docstring"""





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





def   lowerCAmelCase_				( __a	)  ->	Tuple:







  """simple docstring"""





  lowerCamelCase__:   Union[str, Any]    						=set()
  lowerCamelCase__:   Any    						=word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)	)
    lowerCamelCase__:   List[Any]    						=char
  return pairs






class      _SCREAMING_SNAKE_CASE		(			__SCREAMING_SNAKE_CASE					):







 '''simple docstring'''
 lowercase_	=    VOCAB_FILES_NAMES
 lowercase_	=    PRETRAINED_VOCAB_FILES_MAP
 lowercase_	=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_	=    ["input_ids", "attention_mask"]

 def __init__(self       :     str ,				UpperCAmelCase_       :     Tuple ,				UpperCAmelCase_       :     Tuple ,				UpperCAmelCase_       :     Optional[int]="replace" ,				UpperCAmelCase_       :     List[Any]="<s>" ,				UpperCAmelCase_       :     Tuple="</s>" ,				UpperCAmelCase_       :     Tuple="</s>" ,				UpperCAmelCase_       :     Dict="<s>" ,				UpperCAmelCase_       :     Optional[int]="<unk>" ,				UpperCAmelCase_       :     int="<pad>" ,				UpperCAmelCase_       :     Any="<mask>" ,				UpperCAmelCase_       :     Optional[Any]=False ,				**UpperCAmelCase_       :     Any ,				) ->Any:



   '''simple docstring'''



   lowerCamelCase__:   List[Any]    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else bos_token
   lowerCamelCase__:   str    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else eos_token
   lowerCamelCase__:   Dict    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else sep_token
   lowerCamelCase__:   str    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else cls_token
   lowerCamelCase__:   Any    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else unk_token
   lowerCamelCase__:   int    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else pad_token

   # Mask token behave like a normal word, i.e. include the space before it
   lowerCamelCase__:   int    						=AddedToken(UpperCAmelCase_ ,				lstrip=UpperCAmelCase_ ,				rstrip=UpperCAmelCase_) if isinstance(UpperCAmelCase_ ,				UpperCAmelCase_) else mask_token

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

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

   # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
   lowerCamelCase__:   Tuple    						=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 							SCREAMING_SNAKE_CASE_      (self       :     List[Any]) ->List[Any]:



   '''simple docstring'''



   return len(self.encoder)

 def 							SCREAMING_SNAKE_CASE_      (self       :     Tuple) ->List[str]:



   '''simple docstring'''



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

 def 							SCREAMING_SNAKE_CASE_      (self       :     List[Any] ,				UpperCAmelCase_       :     List[str]) ->List[str]:



   '''simple docstring'''



   if token in self.cache:
     return self.cache[token]
   lowerCamelCase__:   Union[str, Any]    						=tuple(UpperCAmelCase_)
   lowerCamelCase__:   Union[str, Any]    						=get_pairs(UpperCAmelCase_)

   if not pairs:
     return token

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

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

 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[int] ,				UpperCAmelCase_       :     Union[str, Any]) ->str:



   '''simple docstring'''



   lowerCamelCase__:   Optional[Any]    						=[]
   for token in re.findall(self.pat ,				UpperCAmelCase_):
     lowerCamelCase__:   Union[str, Any]    						="".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(UpperCAmelCase_).split(" "))
   return bpe_tokens

 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[Any] ,				UpperCAmelCase_       :     List[str]) ->List[Any]:



   '''simple docstring'''



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

 def 							SCREAMING_SNAKE_CASE_      (self       :     int ,				UpperCAmelCase_       :     Dict) ->Dict:



   '''simple docstring'''



   return self.decoder.get(UpperCAmelCase_)

 def 							SCREAMING_SNAKE_CASE_      (self       :     List[Any] ,				UpperCAmelCase_       :     int) ->Optional[int]:



   '''simple docstring'''



   lowerCamelCase__:   Any    						="".join(UpperCAmelCase_)
   lowerCamelCase__:   Dict    						=bytearray([self.byte_decoder[c] for c in text]).decode("utf-8" ,				errors=self.errors)
   return text

 def 							SCREAMING_SNAKE_CASE_      (self       :     Dict ,				UpperCAmelCase_       :     str ,				UpperCAmelCase_       :     Optional[str] = None) ->Tuple[str]:



   '''simple docstring'''



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

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

   lowerCamelCase__:   Optional[int]    						=0
   with open(UpperCAmelCase_ ,				"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 UpperCAmelCase_: 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(UpperCAmelCase_) + "\n")
       index += 1

   return vocab_file, merge_file

 def 							SCREAMING_SNAKE_CASE_      (self       :     List[str] ,				UpperCAmelCase_       :     List[int] ,				UpperCAmelCase_       :     Optional[List[int]] = None ,				UpperCAmelCase_       :     bool = False) ->List[int]:



   '''simple docstring'''



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

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

 def 							SCREAMING_SNAKE_CASE_      (self       :     Optional[int] ,				UpperCAmelCase_       :     List[int] ,				UpperCAmelCase_       :     Optional[List[int]] = None) ->List[int]:



   '''simple docstring'''



   lowerCamelCase__:   Tuple    						=[self.sep_token_id]
   lowerCamelCase__:   Optional[Any]    						=[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 							SCREAMING_SNAKE_CASE_      (self       :     Dict ,				UpperCAmelCase_       :     Optional[Any] ,				UpperCAmelCase_       :     str=False ,				**UpperCAmelCase_       :     Union[str, Any]) ->Dict:



   '''simple docstring'''



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

 def 							SCREAMING_SNAKE_CASE_      (self       :     str ,				UpperCAmelCase_       :     List[int] ,				UpperCAmelCase_       :     Optional[List[int]] = None) ->str:



   '''simple docstring'''



   return token_ids_a + [self.eos_token_id]







 def 							SCREAMING_SNAKE_CASE_      (self       :     List[str] ,				UpperCAmelCase_       :     "Conversation") ->List[int]:



   '''simple docstring'''



   lowerCamelCase__:   Union[str, 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(UpperCAmelCase_)

   lowerCamelCase__:   Union[str, Any]    						="  ".join(UpperCAmelCase_)
   lowerCamelCase__:   Optional[Any]    						=self.encode(UpperCAmelCase_)
   if len(UpperCAmelCase_) > self.model_max_length:
     lowerCamelCase__:   Dict    						=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












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A             =       {
    "configuration_jukebox": [
        "JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "JukeboxConfig",
        "JukeboxPriorConfig",
        "JukeboxVQVAEConfig",
    ],
    "tokenization_jukebox": ["JukeboxTokenizer"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     __A             =       [
         "JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST",
         "JukeboxModel",
         "JukeboxPreTrainedModel",
         "JukeboxVQVAE",
         "JukeboxPrior",
     ]

if TYPE_CHECKING:
     from .configuration_jukebox import (
         JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP,
         JukeboxConfig,
         JukeboxPriorConfig,
         JukeboxVQVAEConfig,
     )
     from .tokenization_jukebox import JukeboxTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_jukebox import (
              JUKEBOX_PRETRAINED_MODEL_ARCHIVE_LIST,
              JukeboxModel,
              JukeboxPreTrainedModel,
              JukeboxPrior,
              JukeboxVQVAE,
          )

else:
     import sys

     __A             =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

