

"""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_roberta import RobertaTokenizer


SCREAMING_SNAKE_CASE_					:	Tuple							  =						logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_					:	int							  =						{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE_					:	Any							  =						{
    'vocab_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/vocab.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/vocab.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/vocab.json',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json'
        ),
    },
    'merges_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/merges.txt',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/merges.txt',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/merges.txt',
        'roberta-base-openai-detector': 'https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt',
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt'
        ),
    },
    'tokenizer_file': {
        'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/tokenizer.json',
        'roberta-large': 'https://huggingface.co/roberta-large/resolve/main/tokenizer.json',
        'roberta-large-mnli': 'https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json',
        'distilroberta-base': 'https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json',
        'roberta-base-openai-detector': (
            'https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json'
        ),
        'roberta-large-openai-detector': (
            'https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json'
        ),
    },
}

SCREAMING_SNAKE_CASE_					:	Tuple							  =						{
    'roberta-base': 5_1_2,
    'roberta-large': 5_1_2,
    'roberta-large-mnli': 5_1_2,
    'distilroberta-base': 5_1_2,
    'roberta-base-openai-detector': 5_1_2,
    'roberta-large-openai-detector': 5_1_2,
}



class 					a						(       _lowerCamelCase				):



				"""simple docstring"""



				UpperCAmelCase						 =					VOCAB_FILES_NAMES
				UpperCAmelCase						 =					PRETRAINED_VOCAB_FILES_MAP
				UpperCAmelCase						 =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				UpperCAmelCase						 =					["input_ids", "attention_mask"]
				UpperCAmelCase						 =					RobertaTokenizer

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






									"""simple docstring"""


									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    ,						)

									A__										=  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
									if pre_tok_state.get("""add_prefix_space"""    ,						UpperCamelCase       ) != add_prefix_space:
														A__										=  getattr(UpperCamelCase    ,						pre_tok_state.pop("""type"""       )       )
														A__										=  add_prefix_space
														A__										=  pre_tok_class(**UpperCamelCase       )

									A__										=  add_prefix_space

									A__										=  """post_processor"""
									A__										=  getattr(self.backend_tokenizer    ,						UpperCamelCase    ,						UpperCamelCase       )
									if tokenizer_component_instance:
														A__										=  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__										=  tuple(state["""sep"""]       )
														if "cls" in state:
																			A__										=  tuple(state["""cls"""]       )

														A__										=  False

														if state.get("""add_prefix_space"""    ,						UpperCamelCase       ) != add_prefix_space:
																			A__										=  add_prefix_space
																			A__										=  True

														if state.get("""trim_offsets"""    ,						UpperCamelCase       ) != trim_offsets:
																			A__										=  trim_offsets
																			A__										=  True

														if changes_to_apply:
																			A__										=  getattr(UpperCamelCase    ,						state.pop("""type"""       )       )
																			A__										=  component_class(**UpperCamelCase       )
																			setattr(self.backend_tokenizer    ,						UpperCamelCase    ,						UpperCamelCase       )

				@property
				def 				UpperCamelCase	(     self: Tuple       ):






									"""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: Tuple    ,						UpperCamelCase: Union[str, Any]       ):






									"""simple docstring"""


									A__										=  AddedToken(UpperCamelCase    ,						lstrip=UpperCamelCase    ,						rstrip=UpperCamelCase       ) if isinstance(UpperCamelCase    ,						UpperCamelCase       ) else value
									A__										=  value

				def 				UpperCamelCase	(     self: Any    ,						*UpperCamelCase: Optional[Any]    ,						**UpperCamelCase: List[Any]       ):






									"""simple docstring"""


									A__										=  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 				UpperCamelCase	(     self: List[str]    ,						*UpperCamelCase: List[str]    ,						**UpperCamelCase: List[str]       ):






									"""simple docstring"""


									A__										=  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 				UpperCamelCase	(     self: Dict    ,						UpperCamelCase: str    ,						UpperCamelCase: Optional[str] = None       ):






									"""simple docstring"""


									A__										=  self._tokenizer.model.save(UpperCamelCase    ,						name=UpperCamelCase       )
									return tuple(UpperCamelCase       )

				def 				UpperCamelCase	(     self: Optional[Any]    ,						UpperCamelCase: List[str]    ,						UpperCamelCase: Union[str, Any]=None       ):






									"""simple docstring"""


									A__										=  [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 				UpperCamelCase	(     self: Tuple    ,						UpperCamelCase: List[int]    ,						UpperCamelCase: Optional[List[int]] = None       ):






									"""simple docstring"""


									A__										=  [self.sep_token_id]
									A__										=  [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"""



import baseaa





def  _snake_case     (    UpperCAmelCase_  :					str			):
     return baseaa.aaaencode(string.encode("""utf-8"""			)			)





def  _snake_case     (    UpperCAmelCase_  :					bytes			):
     return baseaa.aaadecode(UpperCAmelCase_			).decode("""utf-8"""			)


if __name__ == "__main__":
 import doctest

 doctest.testmod()






