'''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


_A								=   logging.get_logger(__name__)

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

_A								=   {
    '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'
        ),
    },
}

_A								=   {
    '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       UpperCAmelCase__  (       _UpperCAmelCase			):






   """simple docstring"""
   A							:       int     =    VOCAB_FILES_NAMES
   A							:       Optional[Any]     =    PRETRAINED_VOCAB_FILES_MAP
   A							:       List[str]     =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A							:       Tuple     =    ['''input_ids''', '''attention_mask''']
   A							:       List[Any]     =    RobertaTokenizer
   def __init__(self       ,				_a=None       ,				_a=None       ,				_a=None       ,				_a="replace"       ,				_a="<s>"       ,				_a="</s>"       ,				_a="</s>"       ,				_a="<s>"       ,				_a="<unk>"       ,				_a="<pad>"       ,				_a="<mask>"       ,				_a=False       ,				_a=True       ,				**_a       ,				)    ->     Union[str, 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__       ,				)

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

        lowercase_					:       List[Any]     				=					add_prefix_space

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

             lowercase_					:       Optional[int]     				=					False

             if state.get('add_prefix_space'       ,				lowercase__				) != add_prefix_space:
                  lowercase_					:       Dict     				=					add_prefix_space
                  lowercase_					:       Any     				=					True

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

             if changes_to_apply:
                  lowercase_					:       Optional[int]     				=					getattr(lowercase__       ,				state.pop('type'				)				)
                  lowercase_					:       str     				=					component_class(**lowercase__				)
                  setattr(self.backend_tokenizer       ,				lowercase__       ,				lowercase__				)
   @property
   def 		_lowerCamelCase (self				)    ->     Union[str, Any]:






        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 		_lowerCamelCase (self       ,				_a				)    ->     Optional[Any]:
        lowercase_					:       List[str]     				=					AddedToken(lowercase__       ,				lstrip=lowercase__       ,				rstrip=lowercase__				) if isinstance(lowercase__       ,				lowercase__				) else value
        lowercase_					:       List[str]     				=					value
   def 		_lowerCamelCase (self       ,				*_a       ,				**_a				)    ->     List[Any]:
        lowercase_					:       Optional[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 		_lowerCamelCase (self       ,				*_a       ,				**_a				)    ->     str:
        lowercase_					:       List[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 		_lowerCamelCase (self       ,				_a       ,				_a = None				)    ->     Union[str, Any]:
        lowercase_					:       Union[str, Any]     				=					self._tokenizer.model.save(lowercase__       ,				name=lowercase__				)
        return tuple(lowercase__				)
   def 		_lowerCamelCase (self       ,				_a       ,				_a=None				)    ->     List[Any]:
        lowercase_					:       Tuple     				=					[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 		_lowerCamelCase (self       ,				_a       ,				_a = None				)    ->     Dict:
        lowercase_					:       List[str]     				=					[self.sep_token_id]
        lowercase_					:       Optional[int]     				=					[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 ...configuration_utils import PretrainedConfig
from ...utils import logging


_A								=   logging.get_logger(__name__)

_A								=   {
    'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}


class       UpperCAmelCase__  (       _snake_case			):






   """simple docstring"""
   A							:       Any     =    '''mra'''
   def __init__(self       ,				_a=50_265       ,				_a=768       ,				_a=12       ,				_a=12       ,				_a=3_072       ,				_a="gelu"       ,				_a=0.1       ,				_a=0.1       ,				_a=512       ,				_a=1       ,				_a=0.02       ,				_a=1e-5       ,				_a="absolute"       ,				_a=4       ,				_a="full"       ,				_a=0       ,				_a=0       ,				_a=1       ,				_a=0       ,				_a=2       ,				**_a       ,				)    ->     int:
        super().__init__(pad_token_id=_a       ,				bos_token_id=_a       ,				eos_token_id=_a       ,				**_a				)

        lowercase_					:       Union[str, Any]     				=					vocab_size
        lowercase_					:       List[str]     				=					max_position_embeddings
        lowercase_					:       Optional[Any]     				=					hidden_size
        lowercase_					:       Optional[int]     				=					num_hidden_layers
        lowercase_					:       Dict     				=					num_attention_heads
        lowercase_					:       Optional[int]     				=					intermediate_size
        lowercase_					:       Dict     				=					hidden_act
        lowercase_					:       str     				=					hidden_dropout_prob
        lowercase_					:       int     				=					attention_probs_dropout_prob
        lowercase_					:       str     				=					initializer_range
        lowercase_					:       Union[str, Any]     				=					type_vocab_size
        lowercase_					:       Any     				=					layer_norm_eps
        lowercase_					:       Union[str, Any]     				=					position_embedding_type
        lowercase_					:       Any     				=					block_per_row
        lowercase_					:       Optional[int]     				=					approx_mode
        lowercase_					:       int     				=					initial_prior_first_n_blocks
        lowercase_					:       str     				=					initial_prior_diagonal_n_blocks




