




'''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

_SCREAMING_SNAKE_CASE							:       Union[str, Any]						=			logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE							:       Any						=			{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

_SCREAMING_SNAKE_CASE							:       Tuple						=			{
    "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"
    },
}

_SCREAMING_SNAKE_CASE							:       Dict						=			{"facebook/blenderbot-3B": 128}


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

       '''simple docstring'''






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


def 					UpperCamelCase_(     snake_case							:	Any					):

       '''simple docstring'''






       snake_case_      =				set()
       snake_case_      =				word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)					)
              snake_case_      =				char
       return pairs




class 			_snake_case		(     lowercase_							):
   lowerCAmelCase_					:				Union[str, Any]							=   VOCAB_FILES_NAMES
   lowerCAmelCase_					:				int							=   PRETRAINED_VOCAB_FILES_MAP
   lowerCAmelCase_					:				List[Any]							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCAmelCase_					:				Union[str, 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__    ,							)    ->    Any:

          '''simple docstring'''




          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else bos_token
          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else eos_token
          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else sep_token
          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else cls_token
          snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else unk_token
          snake_case_      =				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
          snake_case_      =				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:
                 snake_case_      =				json.load(a__							)
          snake_case_      =				{v: k for k, v in self.encoder.items()}
          snake_case_      =				errors  # how to handle errors in decoding
          snake_case_      =				bytes_to_unicode()
          snake_case_      =				{v: k for k, v in self.byte_encoder.items()}
          with open(a__    ,							encoding="utf-8"							) as merges_handle:
                 snake_case_      =				merges_handle.read().split("\n"							)[1:-1]
          snake_case_      =				[tuple(merge.split()							) for merge in bpe_merges]
          snake_case_      =				dict(zip(a__    ,							range(len(a__							)							)							)							)
          snake_case_      =				{}
          snake_case_      =				add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          snake_case_      =				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							)    ->    Tuple:

          '''simple docstring'''




          return len(self.encoder							)




   def        lowerCAmelCase__    ( self							)    ->    str:

          '''simple docstring'''




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




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Any:

          '''simple docstring'''




          if token in self.cache:
                 return self.cache[token]
          snake_case_      =				tuple(a__							)
          snake_case_      =				get_pairs(a__							)

          if not pairs:
                 return token

          while True:
                 snake_case_      =				min(a__    ,							key=lambda a__							: self.bpe_ranks.get(a__    ,							float("inf"							)							)							)
                 if bigram not in self.bpe_ranks:
                        break
                 snake_case_ ,				snake_case_      =				bigram
                 snake_case_      =				[]
                 snake_case_      =				0
                 while i < len(a__							):
                        try:
                               snake_case_      =				word.index(a__    ,							a__							)
                        except ValueError:
                               new_word.extend(word[i:]							)
                               break
                        else:
                               new_word.extend(word[i:j]							)
                               snake_case_      =				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
                 snake_case_      =				tuple(a__							)
                 snake_case_      =				new_word
                 if len(a__							) == 1:
                        break
                 else:
                        snake_case_      =				get_pairs(a__							)
          snake_case_      =				" ".join(a__							)
          snake_case_      =				word
          return word




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[int]:

          '''simple docstring'''




          snake_case_      =				[]
          for token in re.findall(self.pat    ,							a__							):
                 snake_case_      =				"".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        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[Any]:

          '''simple docstring'''




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




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    Union[str, Any]:

          '''simple docstring'''




          return self.decoder.get(a__							)




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[str]:

          '''simple docstring'''




          snake_case_      =				"".join(a__							)
          snake_case_      =				bytearray([self.byte_decoder[c] for c in text]							).decode("utf-8"    ,							errors=self.errors							)
          return text




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

          '''simple docstring'''




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

          snake_case_      =				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!"							)
                               snake_case_      =				token_index
                        writer.write(" ".join(a__							) + "\n"							)
                        index += 1

          return vocab_file, merge_file




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

          '''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        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

          '''simple docstring'''




          snake_case_      =				[self.sep_token_id]
          snake_case_      =				[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    ,							a__    ,							a__=False    ,							**a__							)    ->    Optional[Any]:

          '''simple docstring'''




          snake_case_      =				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()):
                 snake_case_      =				" " + text
          return (text, kwargs)




   def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    str:

          '''simple docstring'''




          return token_ids_a + [self.eos_token_id]




   def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[int]:

          '''simple docstring'''




          snake_case_      =				[]
          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(a__							)

          snake_case_      =				"  ".join(a__							)
          snake_case_      =				self.encode(a__							)
          if len(a__							) > self.model_max_length:
                 snake_case_      =				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 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


_SCREAMING_SNAKE_CASE							:       Tuple						=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:       List[Any]						=			{"vocab_file": "sentencepiece.bpe.model"}

_SCREAMING_SNAKE_CASE							:       Tuple						=			{
    "vocab_file": {
        "moussaKam/mbarthez": "https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez": "https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model",
        "moussaKam/barthez-orangesum-title": (
            "https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"
        ),
    },
}

_SCREAMING_SNAKE_CASE							:       List[Any]						=			{
    "moussaKam/mbarthez": 1024,
    "moussaKam/barthez": 1024,
    "moussaKam/barthez-orangesum-title": 1024,
}

_SCREAMING_SNAKE_CASE							:       Any						=			"▁"




class 			_snake_case		(     lowercase_							):
			lowerCAmelCase_					:				List[Any]							=   VOCAB_FILES_NAMES
			lowerCAmelCase_					:				Optional[Any]							=   PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_					:				int							=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_					:				Tuple							=   ["input_ids", "attention_mask"]




			def __init__( self    ,							a__    ,							a__="<s>"    ,							a__="</s>"    ,							a__="</s>"    ,							a__="<s>"    ,							a__="<unk>"    ,							a__="<pad>"    ,							a__="<mask>"    ,							a__ = None    ,							**a__    ,							)    ->    None:

										'''simple docstring'''




										snake_case_      =				AddedToken(a__    ,							lstrip=a__    ,							rstrip=a__							) if isinstance(a__    ,							a__							) else mask_token

										snake_case_      =				{} 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__    ,							sp_model_kwargs=self.sp_model_kwargs    ,							**a__    ,							)

										snake_case_      =				vocab_file
										snake_case_      =				spm.SentencePieceProcessor(**self.sp_model_kwargs							)
										self.sp_model.Load(str(a__							)							)

										snake_case_      =				{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

										snake_case_      =				len(self.sp_model							) - 1
										snake_case_      =				{v: k for k, v in self.fairseq_tokens_to_ids.items()}




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

										'''simple docstring'''




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




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None    ,							a__ = False							)    ->    List[int]:

										'''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        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    List[int]:

										'''simple docstring'''




										snake_case_      =				[self.sep_token_id]
										snake_case_      =				[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        lowerCAmelCase__    ( self							)    ->    List[Any]:

										'''simple docstring'''




										return len(self.sp_model							)




			def        lowerCAmelCase__    ( self							)    ->    int:

										'''simple docstring'''




										snake_case_      =				{self.convert_ids_to_tokens(a__							): i for i in range(self.vocab_size							)}
										vocab.update(self.added_tokens_encoder							)
										return vocab




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    List[str]:

										'''simple docstring'''




										return self.sp_model.encode(a__    ,							out_type=a__							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    int:

										'''simple docstring'''




										if token in self.fairseq_tokens_to_ids:
																	return self.fairseq_tokens_to_ids[token]
										snake_case_      =				self.sp_model.PieceToId(a__							)

										return spm_id if spm_id else self.unk_token_id




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    Tuple:

										'''simple docstring'''




										if index in self.fairseq_ids_to_tokens:
																	return self.fairseq_ids_to_tokens[index]
										return self.sp_model.IdToPiece(a__							)




			def        lowerCAmelCase__    ( self    ,							a__							)    ->    Optional[Any]:

										'''simple docstring'''




										snake_case_      =				[]
										snake_case_      =				""
										snake_case_      =				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
																								snake_case_      =				True
																								snake_case_      =				[]
																	else:
																								current_sub_tokens.append(a__							)
																								snake_case_      =				False
										out_string += self.sp_model.decode(a__							)
										return out_string.strip()




			def __getstate__( self							)    ->    Dict:

										'''simple docstring'''




										snake_case_      =				self.__dict__.copy()
										snake_case_      =				None
										return state




			def __setstate__( self    ,							a__							)    ->    str:

										'''simple docstring'''




										snake_case_      =				d

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

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




			def        lowerCAmelCase__    ( self    ,							a__    ,							a__ = None							)    ->    Tuple[str]:

										'''simple docstring'''




										if not os.path.isdir(a__							):
																	logger.error(F'Vocabulary path ({save_directory}) should be a directory'							)
																	return
										snake_case_      =				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:
																								snake_case_      =				self.sp_model.serialized_model_proto()
																								fi.write(a__							)

										return (out_vocab_file,)




