





'''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

lowerCAmelCase :					Optional[int] 							=logging.get_logger(__name__)


lowerCAmelCase :					List[Any] 							={
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCAmelCase :					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'''
    },
}

lowerCAmelCase :					Tuple 							={'''facebook/blenderbot-3B''': 128}
class 				a_       (    _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		: Union[str, Any]     ,				lowercase		: Any=None     ,				lowercase		: Optional[Any]=None     ,				lowercase		: Union[str, Any]=None     ,				lowercase		: Tuple="replace"     ,				lowercase		: Optional[int]="<s>"     ,				lowercase		: int="</s>"     ,				lowercase		: int="</s>"     ,				lowercase		: Optional[int]="<s>"     ,				lowercase		: List[Any]="<unk>"     ,				lowercase		: int="<pad>"     ,				lowercase		: Union[str, Any]="<mask>"     ,				lowercase		: str=False     ,				lowercase		: int=True     ,				**lowercase		: List[Any]     ,				):





        """simple docstring"""




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

        lowercase_      :Optional[Any]         =			json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
        if pre_tok_state.get("add_prefix_space"     ,				lowercase						) != add_prefix_space:
           lowercase_      :str         =			getattr(lowercase     ,				pre_tok_state.pop("type"						)						)
           lowercase_      :int         =			add_prefix_space
           lowercase_      :Optional[int]         =			pre_tok_class(**lowercase						)

        lowercase_      :List[str]         =			add_prefix_space

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

           lowercase_      :List[Any]         =			False

           if state.get("add_prefix_space"     ,				lowercase						) != add_prefix_space:
              lowercase_      :Optional[int]         =			add_prefix_space
              lowercase_      :List[str]         =			True

           if state.get("trim_offsets"     ,				lowercase						) != trim_offsets:
              lowercase_      :Optional[Any]         =			trim_offsets
              lowercase_      :Optional[Any]         =			True

           if changes_to_apply:
              lowercase_      :Any         =			getattr(lowercase     ,				state.pop("type"						)						)
              lowercase_      :Optional[int]         =			component_class(**lowercase						)
              setattr(self.backend_tokenizer     ,				lowercase     ,				lowercase						)





     @property
     # Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
     def 							lowercase__				(			self		: List[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     ,				lowercase		: Optional[int]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			AddedToken(lowercase     ,				lstrip=lowercase     ,				rstrip=lowercase						) if isinstance(lowercase     ,				lowercase						) else value
        lowercase_      :List[str]         =			value





     def 							lowercase__				(			self		: Tuple     ,				*lowercase		: Optional[int]     ,				**lowercase		: Optional[Any]						):





        """simple docstring"""




        lowercase_      :Union[str, Any]         =			kwargs.get("is_split_into_words"     ,				lowercase						)
        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(*lowercase     ,				**lowercase						)





     def 							lowercase__				(			self		: Any     ,				*lowercase		: Dict     ,				**lowercase		: Tuple						):





        """simple docstring"""




        lowercase_      :str         =			kwargs.get("is_split_into_words"     ,				lowercase						)

        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(*lowercase     ,				**lowercase						)





     def 							lowercase__				(			self		: str     ,				lowercase		: str     ,				lowercase		: Optional[str] = None						):





        """simple docstring"""




        lowercase_      :Optional[int]         =			self._tokenizer.model.save(lowercase     ,				name=lowercase						)
        return tuple(lowercase						)





     def 							lowercase__				(			self		: List[str]     ,				lowercase		: List[int]     ,				lowercase		: Optional[List[int]] = None						):





        """simple docstring"""




        lowercase_      :Any         =			[self.sep_token_id]
        lowercase_      :Any         =			[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		: Tuple     ,				lowercase		: List[int]     ,				lowercase		: Optional[List[int]] = None						):





        """simple docstring"""




        return token_ids_a + [self.eos_token_id]







     def 							lowercase__				(			self		: Any     ,				lowercase		: "Conversation"						):





        """simple docstring"""




        lowercase_      :Optional[int]         =			[]
        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(lowercase						)

        lowercase_      :str         =			"  ".join(lowercase						)
        lowercase_      :Any         =			self.encode(lowercase						)
        if len(lowercase						) > self.model_max_length:
           lowercase_      :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









'''simple docstring'''


import numpy as np
def 							UpperCAmelCase_  (						__lowerCamelCase : str     ,__lowerCamelCase : Optional[Any]     ,__lowerCamelCase : int     ,__lowerCamelCase : List[str]     ,__lowerCamelCase : List[Any]			):
   lowercase_      :Dict         =			int(np.ceil((x_end - xa) / h			)			)
   lowercase_      :Optional[int]         =			np.zeros((n + 1,)			)
   lowercase_      :Tuple         =			ya
   lowercase_      :List[str]         =			xa

   for k in range(__lowerCamelCase			):
      lowercase_      :Any         =			f(__lowerCamelCase     ,y[k]			)
      lowercase_      :Optional[Any]         =			f(x + 0.5 * h     ,y[k] + 0.5 * h * ka			)
      lowercase_      :Optional[Any]         =			f(x + 0.5 * h     ,y[k] + 0.5 * h * ka			)
      lowercase_      :Any         =			f(x + h     ,y[k] + h * ka			)
      lowercase_      :Tuple         =			y[k] + (1 / 6) * h * (ka + 2 * ka + 2 * ka + ka)
      x += h

   return y


if __name__ == "__main__":
 import doctest

 doctest.testmod()


