





import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
					from transformers.pipelines.conversational import Conversation


UpperCAmelCase_												=   logging.get_logger(__name__)

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

UpperCAmelCase_												=   {
    """vocab_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """microsoft/deberta-base""": """https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt""",
        """microsoft/deberta-large""": """https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge""": """https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt""",
        """microsoft/deberta-base-mnli""": """https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-large-mnli""": """https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt""",
        """microsoft/deberta-xlarge-mnli""": (
            """https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt"""
        ),
    },
}

UpperCAmelCase_												=   {
    """microsoft/deberta-base""": 512,
    """microsoft/deberta-large""": 512,
    """microsoft/deberta-xlarge""": 512,
    """microsoft/deberta-base-mnli""": 512,
    """microsoft/deberta-large-mnli""": 512,
    """microsoft/deberta-xlarge-mnli""": 512,
}

UpperCAmelCase_												=   {
    """microsoft/deberta-base""": {"""do_lower_case""": False},
    """microsoft/deberta-large""": {"""do_lower_case""": False},
}
class 	UpperCamelCase_						(     __lowerCAmelCase    ):
					lowerCAmelCase_							=		VOCAB_FILES_NAMES
					lowerCAmelCase_							=		PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase_							=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase_							=		['''input_ids''', '''attention_mask''', '''token_type_ids''']
					lowerCAmelCase_							=		DebertaTokenizer




					def __init__(						self ,  lowerCAmelCase_=None ,  lowerCAmelCase_=None ,  lowerCAmelCase_=None ,  lowerCAmelCase_="replace" ,  lowerCAmelCase_="[CLS]" ,  lowerCAmelCase_="[SEP]" ,  lowerCAmelCase_="[SEP]" ,  lowerCAmelCase_="[CLS]" ,  lowerCAmelCase_="[UNK]" ,  lowerCAmelCase_="[PAD]" ,  lowerCAmelCase_="[MASK]" ,  lowerCAmelCase_=False ,  **lowerCAmelCase_ ,  )						->							Union[str, Any]:
										super().__init__(
										    _lowerCamelCase ,  _lowerCamelCase ,  tokenizer_file=_lowerCamelCase ,  errors=_lowerCamelCase ,  bos_token=_lowerCamelCase ,  eos_token=_lowerCamelCase ,  unk_token=_lowerCamelCase ,  sep_token=_lowerCamelCase ,  cls_token=_lowerCamelCase ,  pad_token=_lowerCamelCase ,  mask_token=_lowerCamelCase ,  add_prefix_space=_lowerCamelCase ,  **_lowerCamelCase ,  )
										_snake_case													= kwargs.pop('add_bos_token' ,  _lowerCamelCase     )

										_snake_case													= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
										if pre_tok_state.get('add_prefix_space' ,  _lowerCamelCase     ) != add_prefix_space:
															_snake_case													= getattr(_lowerCamelCase ,  pre_tok_state.pop('type'     )     )
															_snake_case													= add_prefix_space
															_snake_case													= pre_tok_class(**_lowerCamelCase     )

										_snake_case													= add_prefix_space




					@property
					def 		lowerCAmelCase	(						self     )						->							Optional[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 ,  lowerCAmelCase_     )						->							Union[str, Any]:
										_snake_case													= AddedToken(_lowerCamelCase ,  lstrip=_lowerCamelCase ,  rstrip=_lowerCamelCase     ) if isinstance(_lowerCamelCase ,  _lowerCamelCase     ) else value
										_snake_case													= value




					def 		lowerCAmelCase	(						self ,  lowerCAmelCase_ ,  lowerCAmelCase_ = None     )						->							List[Any]:
										if token_ids_a is None:
															return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
										_snake_case													= [self.cls_token_id]
										_snake_case													= [self.sep_token_id]
										return cls + token_ids_a + sep + token_ids_a + sep




					def 		lowerCAmelCase	(						self ,  lowerCAmelCase_ ,  lowerCAmelCase_ = None     )						->							Tuple:
										_snake_case													= [self.sep_token_id]
										_snake_case													= [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     ) * [0] + len(token_ids_a + sep     ) * [1]




					def 		lowerCAmelCase	(						self ,  *lowerCAmelCase_ ,  **lowerCAmelCase_     )						->							Optional[Any]:
										_snake_case													= 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_     )						->							Any:
										_snake_case													= 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     )						->							Any:
										_snake_case													= self._tokenizer.model.save(_lowerCamelCase ,  name=_lowerCamelCase     )
										return tuple(_lowerCamelCase     )






					def 		lowerCAmelCase	(						self ,  lowerCAmelCase_     )						->							Optional[int]:
										_snake_case													= []
										for is_user, text in conversation.iter_texts():
															input_ids.extend(self.encode(_lowerCamelCase ,  add_special_tokens=_lowerCamelCase     ) + [self.eos_token_id]     )

										if len(_lowerCamelCase     ) > self.model_max_length:
															_snake_case													= input_ids[-self.model_max_length :]
										return input_ids




"""simple docstring"""


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


a							=logging.get_logger(__name__)

a							={
    'microsoft/mpnet-base': 'https://huggingface.co/microsoft/mpnet-base/resolve/main/config.json',
}






class    __UpperCAmelCase						(	__lowerCAmelCase	):
				A__      :   Optional[int]  							=       '''mpnet'''

				def __init__(      self	, _lowerCamelCase=30527	, _lowerCamelCase=768	, _lowerCamelCase=12	, _lowerCamelCase=12	, _lowerCamelCase=3072	, _lowerCamelCase="gelu"	, _lowerCamelCase=0.1	, _lowerCamelCase=0.1	, _lowerCamelCase=512	, _lowerCamelCase=0.0_2	, _lowerCamelCase=1E-12	, _lowerCamelCase=32	, _lowerCamelCase=1	, _lowerCamelCase=0	, _lowerCamelCase=2	, **_lowerCamelCase	, ):
										super().__init__(pad_token_id=_lowerCamelCase	, bos_token_id=_lowerCamelCase	, eos_token_id=_lowerCamelCase	, **_lowerCamelCase      )

										lowerCamelCase__					=vocab_size
										lowerCamelCase__					=hidden_size
										lowerCamelCase__					=num_hidden_layers
										lowerCamelCase__					=num_attention_heads
										lowerCamelCase__					=hidden_act
										lowerCamelCase__					=intermediate_size
										lowerCamelCase__					=hidden_dropout_prob
										lowerCamelCase__					=attention_probs_dropout_prob
										lowerCamelCase__					=max_position_embeddings
										lowerCamelCase__					=initializer_range
										lowerCamelCase__					=layer_norm_eps
										lowerCamelCase__					=relative_attention_num_buckets


