





"""simple docstring"""




import json
from typing import 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_bart import BartTokenizer


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


a		:					Optional[Any]	      =     {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

# See all BART models at https://huggingface.co/models?filter=bart
a		:					List[str]	      =     {
    '''vocab_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/vocab.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/vocab.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/merges.txt''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/merges.txt''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt''',
    },
    '''tokenizer_file''': {
        '''facebook/bart-base''': '''https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json''',
        '''facebook/bart-large''': '''https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json''',
        '''facebook/bart-large-mnli''': '''https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json''',
        '''facebook/bart-large-cnn''': '''https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json''',
        '''facebook/bart-large-xsum''': '''https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json''',
        '''yjernite/bart_eli5''': '''https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json''',
    },
}

a		:					List[Any]	      =     {
    '''facebook/bart-base''': 1024,
    '''facebook/bart-large''': 1024,
    '''facebook/bart-large-mnli''': 1024,
    '''facebook/bart-large-cnn''': 1024,
    '''facebook/bart-large-xsum''': 1024,
    '''yjernite/bart_eli5''': 1024,
}


class 			__UpperCamelCase							(		a__		):
							lowerCamelCase  :   Dict    =VOCAB_FILES_NAMES
							lowerCamelCase  :   List[str]    =PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase  :   int    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase  :   str    =["""input_ids""", """attention_mask"""]
							lowerCamelCase  :   Union[str, Any]    =BartTokenizer






							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__ ,   )      ->					Union[str, Any]:
								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__ ,   )

								a :						List[Any]      =							json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__() )
								if pre_tok_state.get("add_prefix_space" ,   lowerCAmelCase__ ) != add_prefix_space:
									a :						str      =							getattr(lowerCAmelCase__ ,   pre_tok_state.pop("type" ) )
									a :						List[str]      =							add_prefix_space
									a :						str      =							pre_tok_class(**lowerCAmelCase__ )

								a :						Any      =							add_prefix_space

								# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
								a :						Union[str, Any]      =							"post_processor"
								a :						Optional[int]      =							getattr(self.backend_tokenizer ,   lowerCAmelCase__ ,   lowerCAmelCase__ )
								if tokenizer_component_instance:
									a :						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:
										a :						List[str]      =							tuple(state["sep"] )
									if "cls" in state:
										a :						List[str]      =							tuple(state["cls"] )

									a :						Optional[Any]      =							False

									if state.get("add_prefix_space" ,   lowerCAmelCase__ ) != add_prefix_space:
										a :						Tuple      =							add_prefix_space
										a :						List[str]      =							True

									if state.get("trim_offsets" ,   lowerCAmelCase__ ) != trim_offsets:
										a :						List[str]      =							trim_offsets
										a :						int      =							True

									if changes_to_apply:
										a :						Union[str, Any]      =							getattr(lowerCAmelCase__ ,   state.pop("type" ) )
										a :						Tuple      =							component_class(**lowerCAmelCase__ )
										setattr(self.backend_tokenizer ,   lowerCAmelCase__ ,   lowerCAmelCase__ )






							@property
							def        __a  (  self )      ->					str:
								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__ )      ->					Optional[int]:
								a :						Optional[Any]      =							AddedToken(lowerCAmelCase__ ,   lstrip=lowerCAmelCase__ ,   rstrip=lowerCAmelCase__ ) if isinstance(lowerCAmelCase__ ,   lowerCAmelCase__ ) else value
								a :						Optional[int]      =							value






							def        __a  (  self ,   *lowerCAmelCase__ ,   **lowerCAmelCase__ )      ->					BatchEncoding:
								a :						Tuple      =							kwargs.get("is_split_into_words" ,   lowerCAmelCase__ )

								if is_split_into_words and not self.add_prefix_space:
									raise ValueError(
									    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__ )      ->					BatchEncoding:
								a :						Any      =							kwargs.get("is_split_into_words" ,   lowerCAmelCase__ )

								if is_split_into_words and not self.add_prefix_space:
									raise ValueError(
									    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 )      ->					Tuple[str]:
								a :						int      =							self._tokenizer.model.save(lowerCAmelCase__ ,   name=lowerCAmelCase__ )
								return tuple(lowerCAmelCase__ )






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__=None )      ->					Union[str, Any]:
								a :						Dict      =							[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = None )      ->					List[int]:
								a :						Optional[Any]      =							[self.sep_token_id]
								a :						Tuple      =							[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]









"""simple docstring"""




from numpy import exp, pi, sqrt






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       Tuple       ,			_lowercase		:       float = 0.0       ,			_lowercase		:       float = 1.0   )					->int:






	'''simple docstring'''






	return 1 / sqrt(2 * pi * sigma**2   ) * exp(-((x - mu) ** 2) / (2 * sigma**2)   )


if __name__ == "__main__":
		import doctest

		doctest.testmod()


