
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

lowercase        =  logging.get_logger(__name__)


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

lowercase        =  {
    '''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'''
    },
}

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





class       __A(				UpperCAmelCase       ):
					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''']
					SCREAMING_SNAKE_CASE			    =    BlenderbotTokenizer

					def __init__(	self					:     str   ,					__UpperCamelCase					:     Any=None   ,					__UpperCamelCase					:     int=None   ,					__UpperCamelCase					:     Optional[int]=None   ,					__UpperCamelCase					:     List[Any]="replace"   ,					__UpperCamelCase					:     int="<s>"   ,					__UpperCamelCase					:     Tuple="</s>"   ,					__UpperCamelCase					:     Dict="</s>"   ,					__UpperCamelCase					:     Any="<s>"   ,					__UpperCamelCase					:     Dict="<unk>"   ,					__UpperCamelCase					:     Dict="<pad>"   ,					__UpperCamelCase					:     Dict="<mask>"   ,					__UpperCamelCase					:     List[str]=False   ,					__UpperCamelCase					:     Union[str, Any]=True   ,					**__UpperCamelCase					:     List[Any]   ,					):
												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_							  =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()   )
												if pre_tok_state.get("""add_prefix_space"""   ,					__UpperCamelCase   ) != add_prefix_space:
																			lowerCamelCase_							  =					getattr(__UpperCamelCase   ,					pre_tok_state.pop("""type"""   )   )
																			lowerCamelCase_							  =					add_prefix_space
																			lowerCamelCase_							  =					pre_tok_class(**__UpperCamelCase   )

												lowerCamelCase_							  =					add_prefix_space

												lowerCamelCase_							  =					"""post_processor"""
												lowerCamelCase_							  =					getattr(self.backend_tokenizer   ,					__UpperCamelCase   ,					__UpperCamelCase   )
												if tokenizer_component_instance:
																			lowerCamelCase_							  =					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_							  =					tuple(state["""sep"""]   )
																			if "cls" in state:
																										lowerCamelCase_							  =					tuple(state["""cls"""]   )

																			lowerCamelCase_							  =					False

																			if state.get("""add_prefix_space"""   ,					__UpperCamelCase   ) != add_prefix_space:
																										lowerCamelCase_							  =					add_prefix_space
																										lowerCamelCase_							  =					True

																			if state.get("""trim_offsets"""   ,					__UpperCamelCase   ) != trim_offsets:
																										lowerCamelCase_							  =					trim_offsets
																										lowerCamelCase_							  =					True

																			if changes_to_apply:
																										lowerCamelCase_							  =					getattr(__UpperCamelCase   ,					state.pop("""type"""   )   )
																										lowerCamelCase_							  =					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					:     Optional[int]   ):
												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					:     Any   ,					__UpperCamelCase					:     List[Any]   ):
												lowerCamelCase_							  =					AddedToken(__UpperCamelCase   ,					lstrip=__UpperCamelCase   ,					rstrip=__UpperCamelCase   ) if isinstance(__UpperCamelCase   ,					__UpperCamelCase   ) else value
												lowerCamelCase_							  =					value

					def    lowercase__      (	self					:     Tuple   ,					*__UpperCamelCase					:     Dict   ,					**__UpperCamelCase					:     Optional[int]   ):
												lowerCamelCase_							  =					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					:     Dict   ,					*__UpperCamelCase					:     List[str]   ,					**__UpperCamelCase					:     Union[str, Any]   ):
												lowerCamelCase_							  =					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					:     Optional[Any]   ,					__UpperCamelCase					:     str   ,					__UpperCamelCase					:     Optional[str] = None   ):
												lowerCamelCase_							  =					self._tokenizer.model.save(__UpperCamelCase   ,					name=__UpperCamelCase   )
												return tuple(__UpperCamelCase   )

					def    lowercase__      (	self					:     Dict   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ):
												lowerCamelCase_							  =					[self.sep_token_id]
												lowerCamelCase_							  =					[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					:     str   ,					__UpperCamelCase					:     List[int]   ,					__UpperCamelCase					:     Optional[List[int]] = None   ):
												return token_ids_a + [self.eos_token_id]



					def    lowercase__      (	self					:     List[str]   ,					__UpperCamelCase					:     "Conversation"   ):
												lowerCamelCase_							  =					[]
												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_							  =					"""  """.join(__UpperCamelCase   )
												lowerCamelCase_							  =					self.encode(__UpperCamelCase   )
												if len(__UpperCamelCase   ) > self.model_max_length:
																			lowerCamelCase_							  =					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







def      __lowerCAmelCase						(							UpperCAmelCase__				:      int = 4_0_0_0_0_0_0       )  ->    int:
							lowerCamelCase_							  =					[]
							lowerCamelCase_  ,   lowerCamelCase_							  =					0, 1
							while b <= n:
														if b % 2 == 0:
																					even_fibs.append(UpperCAmelCase__       )
														lowerCamelCase_  ,   lowerCamelCase_							  =					b, a + b
							return sum(UpperCAmelCase__       )


if __name__ == "__main__":
		print(F"""{solution() = }""")





