"""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": 1_2_8}


class     UpperCAmelCase						(_UpperCAmelCase  ):



    """simple docstring"""

    _UpperCAmelCase	:Any						    = VOCAB_FILES_NAMES
    _UpperCAmelCase	:List[Any]						    = PRETRAINED_VOCAB_FILES_MAP
    _UpperCAmelCase	:int						    = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _UpperCAmelCase	:List[Any]						    = ["input_ids", "attention_mask"]
    _UpperCAmelCase	:Tuple						    = BlenderbotTokenizer






    def __init__(   self    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase=None    ,			_UpperCAmelCase="replace"    ,			_UpperCAmelCase="<s>"    ,			_UpperCAmelCase="</s>"    ,			_UpperCAmelCase="</s>"    ,			_UpperCAmelCase="<s>"    ,			_UpperCAmelCase="<unk>"    ,			_UpperCAmelCase="<pad>"    ,			_UpperCAmelCase="<mask>"    ,			_UpperCAmelCase=False    ,			_UpperCAmelCase=True    ,			**_UpperCAmelCase    ,			):
       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    ,			)

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

       lowercase__:   int					=      add_prefix_space

       lowercase__:   Union[str, Any]					=      '''post_processor'''
       lowercase__:   Union[str, Any]					=      getattr(self.backend_tokenizer    ,			_UpperCAmelCase    ,			_UpperCAmelCase							)
       if tokenizer_component_instance:
          lowercase__:   int					=      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__:   Any					=      tuple(state['''sep''']							)
          if "cls" in state:
             lowercase__:   Optional[Any]					=      tuple(state['''cls''']							)

          lowercase__:   str					=      False

          if state.get('''add_prefix_space'''    ,			_UpperCAmelCase							) != add_prefix_space:
             lowercase__:   Optional[int]					=      add_prefix_space
             lowercase__:   int					=      True

          if state.get('''trim_offsets'''    ,			_UpperCAmelCase							) != trim_offsets:
             lowercase__:   Optional[int]					=      trim_offsets
             lowercase__:   Tuple					=      True

          if changes_to_apply:
             lowercase__:   Optional[int]					=      getattr(_UpperCAmelCase    ,			state.pop('''type'''							)							)
             lowercase__:   List[Any]					=      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 _snake_case			(   self							):
       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 _snake_case			(   self    ,			_UpperCAmelCase							):
       lowercase__:   str					=      AddedToken(_UpperCAmelCase    ,			lstrip=_UpperCAmelCase    ,			rstrip=_UpperCAmelCase							) if isinstance(_UpperCAmelCase    ,			_UpperCAmelCase							) else value
       lowercase__:   int					=      value






    def _snake_case			(   self    ,			*_UpperCAmelCase    ,			**_UpperCAmelCase							):
       lowercase__:   List[Any]					=      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 _snake_case			(   self    ,			*_UpperCAmelCase    ,			**_UpperCAmelCase							):
       lowercase__:   Optional[Any]					=      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 _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   int					=      self._tokenizer.model.save(_UpperCAmelCase    ,			name=_UpperCAmelCase							)
       return tuple(_UpperCAmelCase							)






    def _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       lowercase__:   Tuple					=      [self.sep_token_id]
       lowercase__:   List[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 _snake_case			(   self    ,			_UpperCAmelCase    ,			_UpperCAmelCase = None							):
       return token_ids_a + [self.eos_token_id]






    def _snake_case			(   self    ,			_UpperCAmelCase							):
       lowercase__:   Union[str, 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(_UpperCAmelCase							)

       lowercase__:   Union[str, Any]					=      '''  '''.join(_UpperCAmelCase							)
       lowercase__:   str					=      self.encode(_UpperCAmelCase							)
       if len(_UpperCAmelCase							) > self.model_max_length:
          lowercase__:   str					=      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"""






from collections.abc import Sequence



def SCREAMING_SNAKE_CASE__			(   __UpperCAmelCase       ,    __UpperCAmelCase = False )  ->  float:
   if not arr:
      return 0

   lowercase__:   Any					=      0 if allow_empty_subarrays else float('''-inf''' )
   lowercase__:   Union[str, Any]					=      0.0
   for num in arr:
      lowercase__:   List[str]					=      max(0 if allow_empty_subarrays else num       ,    curr_sum + num )
      lowercase__:   int					=      max(__UpperCAmelCase       ,    __UpperCAmelCase )

   return max_sum


if __name__ == "__main__":
       from doctest import testmod

       testmod()

       __A			   = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
       print(f'''{max_subarray_sum(nums) = }''')
