


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


_UpperCAmelCase			:  str     =logging.get_logger(__name__)

_UpperCAmelCase			:  int     ={"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

_UpperCAmelCase			:  Dict     ={
    """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"""
        ),
    },
}

_UpperCAmelCase			:  List[str]     ={
    """roberta-base""": 512,
    """roberta-large""": 512,
    """roberta-large-mnli""": 512,
    """distilroberta-base""": 512,
    """roberta-base-openai-detector""": 512,
    """roberta-large-openai-detector""": 512,
}







class 				snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						SCREAMING_SNAKE_CASE__      :  Dict					=							VOCAB_FILES_NAMES
						SCREAMING_SNAKE_CASE__      :  Optional[int]					=							PRETRAINED_VOCAB_FILES_MAP
						SCREAMING_SNAKE_CASE__      :  Any					=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						SCREAMING_SNAKE_CASE__      :  str					=							["""input_ids""", """attention_mask"""]
						SCREAMING_SNAKE_CASE__      :  Tuple					=							RobertaTokenizer




						def __init__(				self   ,						__lowercase=None   ,						__lowercase=None   ,						__lowercase=None   ,						__lowercase="replace"   ,						__lowercase="<s>"   ,						__lowercase="</s>"   ,						__lowercase="</s>"   ,						__lowercase="<s>"   ,						__lowercase="<unk>"   ,						__lowercase="<pad>"   ,						__lowercase="<mask>"   ,						__lowercase=False   ,						__lowercase=True   ,						**__lowercase   ,						)					->    Optional[Any]:
										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   ,						)

										lowerCAmelCase_ :      List[Any]    				=				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
										if pre_tok_state.get('''add_prefix_space'''   ,						__lowercase							) != add_prefix_space:
														lowerCAmelCase_ :      Optional[Any]    				=				getattr(__lowercase   ,						pre_tok_state.pop('''type'''							)							)
														lowerCAmelCase_ :      List[str]    				=				add_prefix_space
														lowerCAmelCase_ :      List[Any]    				=				pre_tok_class(**__lowercase							)

										lowerCAmelCase_ :      int    				=				add_prefix_space

										lowerCAmelCase_ :      Tuple    				=				'''post_processor'''
										lowerCAmelCase_ :      Optional[int]    				=				getattr(self.backend_tokenizer   ,						__lowercase   ,						__lowercase							)
										if tokenizer_component_instance:
														lowerCAmelCase_ :      Optional[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:
																		lowerCAmelCase_ :      Tuple    				=				tuple(state['''sep''']							)
														if "cls" in state:
																		lowerCAmelCase_ :      Any    				=				tuple(state['''cls''']							)

														lowerCAmelCase_ :      Dict    				=				False

														if state.get('''add_prefix_space'''   ,						__lowercase							) != add_prefix_space:
																		lowerCAmelCase_ :      int    				=				add_prefix_space
																		lowerCAmelCase_ :      List[Any]    				=				True

														if state.get('''trim_offsets'''   ,						__lowercase							) != trim_offsets:
																		lowerCAmelCase_ :      Optional[int]    				=				trim_offsets
																		lowerCAmelCase_ :      Optional[Any]    				=				True

														if changes_to_apply:
																		lowerCAmelCase_ :      str    				=				getattr(__lowercase   ,						state.pop('''type'''							)							)
																		lowerCAmelCase_ :      Union[str, Any]    				=				component_class(**__lowercase							)
																		setattr(self.backend_tokenizer   ,						__lowercase   ,						__lowercase							)




						@property
						def 						lowercase_ (				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 						lowercase_ (				self   ,						__lowercase							)					->    int:
										lowerCAmelCase_ :      Optional[Any]    				=				AddedToken(__lowercase   ,						lstrip=__lowercase   ,						rstrip=__lowercase							) if isinstance(__lowercase   ,						__lowercase							) else value
										lowerCAmelCase_ :      Optional[Any]    				=				value




						def 						lowercase_ (				self   ,						*__lowercase   ,						**__lowercase							)					->    BatchEncoding:
										lowerCAmelCase_ :      List[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()._batch_encode_plus(*__lowercase   ,						**__lowercase							)




						def 						lowercase_ (				self   ,						*__lowercase   ,						**__lowercase							)					->    BatchEncoding:
										lowerCAmelCase_ :      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()._encode_plus(*__lowercase   ,						**__lowercase							)




						def 						lowercase_ (				self   ,						__lowercase   ,						__lowercase = None							)					->    Tuple[str]:
										lowerCAmelCase_ :      str    				=				self._tokenizer.model.save(__lowercase   ,						name=__lowercase							)
										return tuple(__lowercase							)




						def 						lowercase_ (				self   ,						__lowercase   ,						__lowercase=None							)					->    List[str]:
										lowerCAmelCase_ :      List[str]    				=				[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 						lowercase_ (				self   ,						__lowercase   ,						__lowercase = None							)					->    List[int]:
										lowerCAmelCase_ :      List[Any]    				=				[self.sep_token_id]
										lowerCAmelCase_ :      List[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]



_UpperCAmelCase			:  Dict     =[
    (1000, """M"""),
    (900, """CM"""),
    (500, """D"""),
    (400, """CD"""),
    (100, """C"""),
    (90, """XC"""),
    (50, """L"""),
    (40, """XL"""),
    (10, """X"""),
    (9, """IX"""),
    (5, """V"""),
    (4, """IV"""),
    (1, """I"""),
]



def 			lowerCAmelCase (		lowerCAmelCase_ )-> int:
				lowerCAmelCase_ :      Any    				=				{'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1_000}
				lowerCAmelCase_ :      Optional[int]    				=				0
				lowerCAmelCase_ :      List[str]    				=				0
				while place < len(lowerCAmelCase_ ):
								if (place + 1 < len(lowerCAmelCase_ )) and (vals[roman[place]] < vals[roman[place + 1]]):
												total += vals[roman[place + 1]] - vals[roman[place]]
												place += 2
								else:
												total += vals[roman[place]]
												place += 1
				return total



def 			lowerCAmelCase (		lowerCAmelCase_ )-> str:
				lowerCAmelCase_ :      List[Any]    				=				[]
				for arabic, roman in ROMAN:
								((lowerCAmelCase_)				,  (lowerCAmelCase_)) :      Optional[int]    				=				divmod(lowerCAmelCase_ ,   lowerCAmelCase_ )
								result.append(roman * factor )
								if number == 0:
												break
				return "".join(lowerCAmelCase_ )


if __name__ == "__main__":
						import doctest

						doctest.testmod()