



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


__snake_case       :	Dict            =logging.get_logger(__name__)

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

__snake_case       :	int            ={
    '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'
        ),
    },
}

__snake_case       :	Union[str, Any]            ={
    '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  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



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



		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	,)  ->    Optional[int]:

						"""simple docstring"""






						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	,)

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

						lowerCAmelCase__  :       Tuple				=  add_prefix_space

						lowerCAmelCase__  :       List[Any]				=  '''post_processor'''
						lowerCAmelCase__  :       str				=  getattr(self.backend_tokenizer	,__lowerCamelCase	,__lowerCamelCase				)
						if tokenizer_component_instance:
										lowerCAmelCase__  :       Union[str, Any]				=  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__  :       str				=  tuple(state['''sep''']				)
										if "cls" in state:
														lowerCAmelCase__  :       Union[str, Any]				=  tuple(state['''cls''']				)

										lowerCAmelCase__  :       Optional[Any]				=  False

										if state.get('''add_prefix_space'''	,__lowerCamelCase				) != add_prefix_space:
														lowerCAmelCase__  :       Dict				=  add_prefix_space
														lowerCAmelCase__  :       Any				=  True

										if state.get('''trim_offsets'''	,__lowerCamelCase				) != trim_offsets:
														lowerCAmelCase__  :       str				=  trim_offsets
														lowerCAmelCase__  :       List[str]				=  True

										if changes_to_apply:
														lowerCAmelCase__  :       Optional[int]				=  getattr(__lowerCamelCase	,state.pop('''type'''				)				)
														lowerCAmelCase__  :       Any				=  component_class(**__lowerCamelCase				)
														setattr(self.backend_tokenizer	,__lowerCamelCase	,__lowerCamelCase				)



		@property
		def 	lowerCAmelCase__   (self				)  ->    str:

						"""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 	lowerCAmelCase__   (self	,__lowerCamelCase				)  ->    Any:

						"""simple docstring"""






						lowerCAmelCase__  :       str				=  AddedToken(__lowerCamelCase	,lstrip=__lowerCamelCase	,rstrip=__lowerCamelCase				) if isinstance(__lowerCamelCase	,__lowerCamelCase				) else value
						lowerCAmelCase__  :       Dict				=  value



		def 	lowerCAmelCase__   (self	,*__lowerCamelCase	,**__lowerCamelCase				)  ->    BatchEncoding:

						"""simple docstring"""






						lowerCAmelCase__  :       List[str]				=  kwargs.get('''is_split_into_words'''	,__lowerCamelCase				)
						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(*__lowerCamelCase	,**__lowerCamelCase				)



		def 	lowerCAmelCase__   (self	,*__lowerCamelCase	,**__lowerCamelCase				)  ->    BatchEncoding:

						"""simple docstring"""






						lowerCAmelCase__  :       Optional[Any]				=  kwargs.get('''is_split_into_words'''	,__lowerCamelCase				)

						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(*__lowerCamelCase	,**__lowerCamelCase				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase = None				)  ->    Tuple[str]:

						"""simple docstring"""






						lowerCAmelCase__  :       Dict				=  self._tokenizer.model.save(__lowerCamelCase	,name=__lowerCamelCase				)
						return tuple(__lowerCamelCase				)



		def 	lowerCAmelCase__   (self	,__lowerCamelCase	,__lowerCamelCase=None				)  ->    Optional[int]:

						"""simple docstring"""






						lowerCAmelCase__  :       Union[str, Any]				=  [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	,__lowerCamelCase	,__lowerCamelCase = None				)  ->    List[int]:

						"""simple docstring"""






						lowerCAmelCase__  :       str				=  [self.sep_token_id]
						lowerCAmelCase__  :       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]






import warnings

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case       :	List[Any]            =logging.get_logger(__name__)

__snake_case       :	str            ={
    'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}



class  lowerCamelCase__    (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_			="""mvp"""
		snake_case_			=["""past_key_values"""]
		snake_case_			={"""num_attention_heads""": """encoder_attention_heads""", """hidden_size""": """d_model"""}



		def __init__(self	,__lowerCamelCase=5_02_67	,__lowerCamelCase=10_24	,__lowerCamelCase=12	,__lowerCamelCase=40_96	,__lowerCamelCase=16	,__lowerCamelCase=12	,__lowerCamelCase=40_96	,__lowerCamelCase=16	,__lowerCamelCase=0.0	,__lowerCamelCase=0.0	,__lowerCamelCase="gelu"	,__lowerCamelCase=10_24	,__lowerCamelCase=0.1	,__lowerCamelCase=0.0	,__lowerCamelCase=0.0	,__lowerCamelCase=0.02	,__lowerCamelCase=0.0	,__lowerCamelCase=False	,__lowerCamelCase=True	,__lowerCamelCase=1	,__lowerCamelCase=0	,__lowerCamelCase=2	,__lowerCamelCase=True	,__lowerCamelCase=2	,__lowerCamelCase=2	,__lowerCamelCase=False	,__lowerCamelCase=1_00	,__lowerCamelCase=8_00	,**__lowerCamelCase	,)  ->    Optional[Any]:

						"""simple docstring"""






						lowerCAmelCase__  :       Union[str, Any]				=  vocab_size
						lowerCAmelCase__  :       Dict				=  max_position_embeddings
						lowerCAmelCase__  :       Optional[int]				=  d_model
						lowerCAmelCase__  :       Any				=  encoder_ffn_dim
						lowerCAmelCase__  :       str				=  encoder_layers
						lowerCAmelCase__  :       Union[str, Any]				=  encoder_attention_heads
						lowerCAmelCase__  :       Dict				=  decoder_ffn_dim
						lowerCAmelCase__  :       Optional[int]				=  decoder_layers
						lowerCAmelCase__  :       int				=  decoder_attention_heads
						lowerCAmelCase__  :       str				=  dropout
						lowerCAmelCase__  :       int				=  attention_dropout
						lowerCAmelCase__  :       Optional[Any]				=  activation_dropout
						lowerCAmelCase__  :       Optional[int]				=  activation_function
						lowerCAmelCase__  :       int				=  init_std
						lowerCAmelCase__  :       List[Any]				=  encoder_layerdrop
						lowerCAmelCase__  :       Union[str, Any]				=  decoder_layerdrop
						lowerCAmelCase__  :       Tuple				=  classifier_dropout
						lowerCAmelCase__  :       Optional[int]				=  use_cache
						lowerCAmelCase__  :       List[Any]				=  encoder_layers
						lowerCAmelCase__  :       List[str]				=  scale_embedding  # scale factor will be sqrt(d_model) if True
						lowerCAmelCase__  :       Any				=  use_prompt
						lowerCAmelCase__  :       Optional[Any]				=  prompt_length
						lowerCAmelCase__  :       int				=  prompt_mid_dim

						super().__init__(
						    pad_token_id=__lowerCamelCase	,bos_token_id=__lowerCamelCase	,eos_token_id=__lowerCamelCase	,is_encoder_decoder=__lowerCamelCase	,decoder_start_token_id=__lowerCamelCase	,forced_eos_token_id=__lowerCamelCase	,**__lowerCamelCase	,)

						if self.forced_bos_token_id is None and kwargs.get('''force_bos_token_to_be_generated'''	,__lowerCamelCase				):
										lowerCAmelCase__  :       Union[str, Any]				=  self.bos_token_id
										warnings.warn(
										    f"""Please make sure the config includes `forced_bos_token_id={self.bos_token_id}` in future versions. """
										    '''The config can simply be saved and uploaded again to be fixed.'''				)

