



"""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

snake_case   					=				logging.get_logger(__name__)


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

snake_case   					=				{
    '''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'''
    },
}

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



class     UpperCAmelCase    (	__SCREAMING_SNAKE_CASE  ):
   A__		:	Dict           =  VOCAB_FILES_NAMES
   A__		:	Optional[int]           =  PRETRAINED_VOCAB_FILES_MAP
   A__		:	str           =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A__		:	int           =  ['''input_ids''', '''attention_mask''']
   A__		:	int           =  BlenderbotTokenizer



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



     """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							,       )

     _snake_case   	=      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()				)
     if pre_tok_state.get('''add_prefix_space'''							,       __lowerCamelCase				) != add_prefix_space:
       _snake_case   	=      getattr(__lowerCamelCase							,       pre_tok_state.pop('''type'''				)				)
       _snake_case   	=      add_prefix_space
       _snake_case   	=      pre_tok_class(**__lowerCamelCase				)

     _snake_case   	=      add_prefix_space

     _snake_case   	=      '''post_processor'''
     _snake_case   	=      getattr(self.backend_tokenizer							,       __lowerCamelCase							,       __lowerCamelCase				)
     if tokenizer_component_instance:
       _snake_case   	=      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:
         _snake_case   	=      tuple(state['''sep''']				)
       if "cls" in state:
         _snake_case   	=      tuple(state['''cls''']				)

       _snake_case   	=      False

       if state.get('''add_prefix_space'''							,       __lowerCamelCase				) != add_prefix_space:
         _snake_case   	=      add_prefix_space
         _snake_case   	=      True

       if state.get('''trim_offsets'''							,       __lowerCamelCase				) != trim_offsets:
         _snake_case   	=      trim_offsets
         _snake_case   	=      True

       if changes_to_apply:
         _snake_case   	=      getattr(__lowerCamelCase							,       state.pop('''type'''				)				)
         _snake_case   	=      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    __UpperCAmelCase    (       self    :	Union[str, Any]				):



     """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    __UpperCAmelCase    (       self    :	List[Any]							,       __lowerCamelCase    :	Any				):



     """simple docstring"""
     _snake_case   	=      AddedToken(__lowerCamelCase							,       lstrip=__lowerCamelCase							,       rstrip=__lowerCamelCase				) if isinstance(__lowerCamelCase							,       __lowerCamelCase				) else value
     _snake_case   	=      value



   def    __UpperCAmelCase    (       self    :	Optional[int]							,       *__lowerCamelCase    :	Optional[int]							,       **__lowerCamelCase    :	Optional[Any]				):



     """simple docstring"""
     _snake_case   	=      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    __UpperCAmelCase    (       self    :	int							,       *__lowerCamelCase    :	Optional[Any]							,       **__lowerCamelCase    :	Optional[int]				):



     """simple docstring"""
     _snake_case   	=      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    __UpperCAmelCase    (       self    :	Optional[int]							,       __lowerCamelCase    :	str							,       __lowerCamelCase    :	Optional[str] = None				):



     """simple docstring"""
     _snake_case   	=      self._tokenizer.model.save(__lowerCamelCase							,       name=__lowerCamelCase				)
     return tuple(__lowerCamelCase				)



   def    __UpperCAmelCase    (       self    :	List[Any]							,       __lowerCamelCase    :	List[int]							,       __lowerCamelCase    :	Optional[List[int]] = None				):



     """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    __UpperCAmelCase    (       self    :	List[Any]							,       __lowerCamelCase    :	List[int]							,       __lowerCamelCase    :	Optional[List[int]] = None				):



     """simple docstring"""
     return token_ids_a + [self.eos_token_id]





   def    __UpperCAmelCase    (       self    :	str							,       __lowerCamelCase    :	"Conversation"				):



     """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(__lowerCamelCase				)

     _snake_case   	=      '''  '''.join(__lowerCamelCase				)
     _snake_case   	=      self.encode(__lowerCamelCase				)
     if len(__lowerCamelCase				) > 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













lowerCamelCase__       		=  8.3_1_4_4_5_9_8






def 	UpperCamelCase	(							snake_case__  : float						,snake_case__  : float	):




     '''simple docstring'''






     if temperature < 0:
          raise Exception("""Temperature cannot be less than 0 K"""	)
     if molar_mass <= 0:
          raise Exception("""Molar mass cannot be less than or equal to 0 kg/mol"""	)
     else:
          return (3 * UNIVERSAL_GAS_CONSTANT * temperature / molar_mass) ** 0.5


if __name__ == "__main__":
     import doctest

     # run doctest
     doctest.testmod()

     # example
     lowerCamelCase__       		=  300
     lowerCamelCase__       		=  28
     lowerCamelCase__       		=  rms_speed_of_molecule(temperature, molar_mass)
     print(f'''Vrms of Nitrogen gas at 300 K is {vrms} m/s''')


