






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

SCREAMING_SNAKE_CASE__      :			Dict							=		logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__      :			Optional[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__      :			Any							=		{"""facebook/blenderbot-3B""": 1_28}
class 						lowerCamelCase_				(      lowerCamelCase ):
				a__					       =  VOCAB_FILES_NAMES
				a__					       =  PRETRAINED_VOCAB_FILES_MAP
				a__					       =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				a__					       =  ['''input_ids''', '''attention_mask''']
				a__					       =  BlenderbotTokenizer







				def __init__(						self       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase=None       ,					__lowerCAmelCase="replace"       ,					__lowerCAmelCase="<s>"       ,					__lowerCAmelCase="</s>"       ,					__lowerCAmelCase="</s>"       ,					__lowerCAmelCase="<s>"       ,					__lowerCAmelCase="<unk>"       ,					__lowerCAmelCase="<pad>"       ,					__lowerCAmelCase="<mask>"       ,					__lowerCAmelCase=False       ,					__lowerCAmelCase=True       ,					**__lowerCAmelCase       ,					):
								"""simple docstring"""
								super().__init__(
								    __lowerCAmelCase       ,					__lowerCAmelCase       ,					tokenizer_file=__lowerCAmelCase       ,					errors=__lowerCAmelCase       ,					bos_token=__lowerCAmelCase       ,					eos_token=__lowerCAmelCase       ,					sep_token=__lowerCAmelCase       ,					cls_token=__lowerCAmelCase       ,					unk_token=__lowerCAmelCase       ,					pad_token=__lowerCAmelCase       ,					mask_token=__lowerCAmelCase       ,					add_prefix_space=__lowerCAmelCase       ,					trim_offsets=__lowerCAmelCase       ,					**__lowerCAmelCase       ,					)

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

								__magic_name__		:Union[str, Any]        =      add_prefix_space

								__magic_name__		:str        =      '''post_processor'''
								__magic_name__		:int        =      getattr(self.backend_tokenizer       ,					__lowerCAmelCase       ,					__lowerCAmelCase     )
								if tokenizer_component_instance:
												__magic_name__		:List[str]        =      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:
																__magic_name__		:Dict        =      tuple(state['''sep''']     )
												if "cls" in state:
																__magic_name__		:Optional[Any]        =      tuple(state['''cls''']     )

												__magic_name__		:int        =      False

												if state.get('''add_prefix_space'''       ,					__lowerCAmelCase     ) != add_prefix_space:
																__magic_name__		:str        =      add_prefix_space
																__magic_name__		:Tuple        =      True

												if state.get('''trim_offsets'''       ,					__lowerCAmelCase     ) != trim_offsets:
																__magic_name__		:Optional[Any]        =      trim_offsets
																__magic_name__		:Tuple        =      True

												if changes_to_apply:
																__magic_name__		:str        =      getattr(__lowerCAmelCase       ,					state.pop('''type'''     )     )
																__magic_name__		:List[str]        =      component_class(**__lowerCAmelCase     )
																setattr(self.backend_tokenizer       ,					__lowerCAmelCase       ,					__lowerCAmelCase     )







				@property
				# Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
				def 			A	(						self     ):
								"""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 			A	(						self       ,					__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__		:int        =      AddedToken(__lowerCAmelCase       ,					lstrip=__lowerCAmelCase       ,					rstrip=__lowerCAmelCase     ) if isinstance(__lowerCAmelCase       ,					__lowerCAmelCase     ) else value
								__magic_name__		:List[str]        =      value







				def 			A	(						self       ,					*__lowerCAmelCase       ,					**__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__		:Union[str, Any]        =      kwargs.get('''is_split_into_words'''       ,					__lowerCAmelCase     )
								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(*__lowerCAmelCase       ,					**__lowerCAmelCase     )







				def 			A	(						self       ,					*__lowerCAmelCase       ,					**__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__		:Optional[Any]        =      kwargs.get('''is_split_into_words'''       ,					__lowerCAmelCase     )

								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(*__lowerCAmelCase       ,					**__lowerCAmelCase     )







				def 			A	(						self       ,					__lowerCAmelCase       ,					__lowerCAmelCase = None     ):
								"""simple docstring"""
								__magic_name__		:int        =      self._tokenizer.model.save(__lowerCAmelCase       ,					name=__lowerCAmelCase     )
								return tuple(__lowerCAmelCase     )







				def 			A	(						self       ,					__lowerCAmelCase       ,					__lowerCAmelCase = None     ):
								"""simple docstring"""
								__magic_name__		:int        =      [self.sep_token_id]
								__magic_name__		:str        =      [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 			A	(						self       ,					__lowerCAmelCase       ,					__lowerCAmelCase = None     ):
								"""simple docstring"""
								return token_ids_a + [self.eos_token_id]







				def 			A	(						self       ,					__lowerCAmelCase     ):
								"""simple docstring"""
								__magic_name__		:List[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     )

								__magic_name__		:Any        =      '''  '''.join(__lowerCAmelCase     )
								__magic_name__		:Optional[Any]        =      self.encode(__lowerCAmelCase     )
								if len(__lowerCAmelCase     ) > self.model_max_length:
												__magic_name__		:Optional[int]        =      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














SCREAMING_SNAKE_CASE__      :			str							=		"""Alexander Joslin"""

import operator as op

from .stack import Stack

def      __lowercase					( snake_case ):







				"""simple docstring"""






				__magic_name__		:Optional[int]        =      {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}

				__magic_name__		:Stack[int]        =      Stack()
				__magic_name__		:Stack[str]        =      Stack()

				for i in equation:
								if i.isdigit():
												# RULE 1
												operand_stack.push(int(snake_case ) )
								elif i in operators:
												# RULE 2
												operator_stack.push(snake_case )
								elif i == ")":
												# RULE 4
												__magic_name__		:Optional[int]        =      operator_stack.peek()
												operator_stack.pop()
												__magic_name__		:List[str]        =      operand_stack.peek()
												operand_stack.pop()
												__magic_name__		:Optional[Any]        =      operand_stack.peek()
												operand_stack.pop()

												__magic_name__		:Optional[int]        =      operators[opr](snake_case,  snake_case )
												operand_stack.push(snake_case )

    # RULE 5
				return operand_stack.peek()


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE__      :			Any							=		"""(5 + ((4 * 2) * (2 + 3)))"""
					# answer = 45
					print(f"{equation} = {dijkstras_two_stack_algorithm(equation)}")






