

"""simple docstring"""


import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import BlenderbotTokenizer


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}





class     snake_case	(				__lowercase  ):
				SCREAMING_SNAKE_CASE_   :      List[Any]         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Optional[int]         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      str         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Optional[Any]         =  ['''input_ids''', '''attention_mask''']
				SCREAMING_SNAKE_CASE_   :      List[Any]         =  BlenderbotTokenizer

				def __init__(	self							:				Union[str, Any]     ,  UpperCamelCase__							:				Tuple=None     ,  UpperCamelCase__							:				Tuple=None     ,  UpperCamelCase__							:				List[Any]=None     ,  UpperCamelCase__							:				str="replace"     ,  UpperCamelCase__							:				Dict="<s>"     ,  UpperCamelCase__							:				Tuple="</s>"     ,  UpperCamelCase__							:				Optional[Any]="</s>"     ,  UpperCamelCase__							:				Any="<s>"     ,  UpperCamelCase__							:				List[str]="<unk>"     ,  UpperCamelCase__							:				int="<pad>"     ,  UpperCamelCase__							:				Union[str, Any]="<mask>"     ,  UpperCamelCase__							:				str=False     ,  UpperCamelCase__							:				Union[str, Any]=True     ,  **UpperCamelCase__							:				Optional[int]     ,  )->   int:



						'''simple docstring'''


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

						__lowerCAmelCase:       List[Any]          =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__())
						if pre_tok_state.get("add_prefix_space"     ,  UpperCAmelCase__) != add_prefix_space:
								__lowerCAmelCase:       str          =			getattr(UpperCAmelCase__     ,  pre_tok_state.pop("type"))
								__lowerCAmelCase:       Any          =			add_prefix_space
								__lowerCAmelCase:       List[Any]          =			pre_tok_class(**UpperCAmelCase__)

						__lowerCAmelCase:       Tuple          =			add_prefix_space

						__lowerCAmelCase:       Any          =			"post_processor"
						__lowerCAmelCase:       int          =			getattr(self.backend_tokenizer     ,  UpperCAmelCase__     ,  UpperCAmelCase__)
						if tokenizer_component_instance:
								__lowerCAmelCase:       Union[str, Any]          =			json.loads(tokenizer_component_instance.__getstate__())

								# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
								if "sep" in state:
										__lowerCAmelCase:       Optional[Any]          =			tuple(state["sep"])
								if "cls" in state:
										__lowerCAmelCase:       List[str]          =			tuple(state["cls"])

								__lowerCAmelCase:       Dict          =			False

								if state.get("add_prefix_space"     ,  UpperCAmelCase__) != add_prefix_space:
										__lowerCAmelCase:       str          =			add_prefix_space
										__lowerCAmelCase:       Optional[Any]          =			True

								if state.get("trim_offsets"     ,  UpperCAmelCase__) != trim_offsets:
										__lowerCAmelCase:       Union[str, Any]          =			trim_offsets
										__lowerCAmelCase:       List[str]          =			True

								if changes_to_apply:
										__lowerCAmelCase:       int          =			getattr(UpperCAmelCase__     ,  state.pop("type"))
										__lowerCAmelCase:       Dict          =			component_class(**UpperCAmelCase__)
										setattr(self.backend_tokenizer     ,  UpperCAmelCase__     ,  UpperCAmelCase__)

				@property
				# Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
				def 							lowercase_     (	self							:				Union[str, Any])->   str:



						'''simple docstring'''


						if self._mask_token is None:
								if self.verbose:
										logger.error("Using mask_token, but it is not set yet.")
								return None
						return str(self._mask_token)

				@mask_token.setter
				def 							lowercase_     (	self							:				int     ,  UpperCamelCase__							:				Optional[Any])->   Tuple:



						'''simple docstring'''


						__lowerCAmelCase:       List[str]          =			AddedToken(UpperCAmelCase__     ,  lstrip=UpperCAmelCase__     ,  rstrip=UpperCAmelCase__) if isinstance(UpperCAmelCase__     ,  UpperCAmelCase__) else value
						__lowerCAmelCase:       Any          =			value

				def 							lowercase_     (	self							:				Optional[Any]     ,  *UpperCamelCase__							:				Union[str, Any]     ,  **UpperCamelCase__							:				List[str])->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			kwargs.get("is_split_into_words"     ,  UpperCAmelCase__)
						assert self.add_prefix_space or not is_split_into_words, (
						    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
						    "to use it with pretokenized inputs."
						)

						return super()._batch_encode_plus(*UpperCAmelCase__     ,  **UpperCAmelCase__)

				def 							lowercase_     (	self							:				List[str]     ,  *UpperCamelCase__							:				str     ,  **UpperCamelCase__							:				List[str])->   BatchEncoding:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			kwargs.get("is_split_into_words"     ,  UpperCAmelCase__)

						assert self.add_prefix_space or not is_split_into_words, (
						    f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
						    "to use it with pretokenized inputs."
						)

						return super()._encode_plus(*UpperCAmelCase__     ,  **UpperCAmelCase__)

				def 							lowercase_     (	self							:				str     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						__lowerCAmelCase:       str          =			self._tokenizer.model.save(UpperCAmelCase__     ,  name=UpperCAmelCase__)
						return tuple(UpperCAmelCase__)

				def 							lowercase_     (	self							:				Optional[int]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			[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 							lowercase_     (	self							:				List[str]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   Any:



						'''simple docstring'''


						return token_ids_a + [self.eos_token_id]




				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				"Conversation")->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Tuple          =			[]
						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:       int          =			"  ".join(UpperCAmelCase__)
						__lowerCAmelCase:       List[Any]          =			self.encode(UpperCAmelCase__)
						if len(UpperCAmelCase__) > self.model_max_length:
								__lowerCAmelCase:       Any          =			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'''




print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))





