

"""simple docstring"""





import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding

class      __a (   snake_case__     ):

			"""simple docstring"""

			SCREAMING_SNAKE_CASE_      =    ['image_processor', 'tokenizer']
			SCREAMING_SNAKE_CASE_      =    'AutoImageProcessor'
			SCREAMING_SNAKE_CASE_      =    'AutoTokenizer'






			def __init__(				self  :       Optional[int]    ,	lowercase_  :       str=None    ,	lowercase_  :       int=None    ,	**lowercase_  :       int    ):
								UpperCamelCase__		:     int								=None
								if "feature_extractor" in kwargs:
													warnings.warn(
													    '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
													    ''' instead.'''    ,	lowercase_    ,	)
													UpperCamelCase__		:     str								=kwargs.pop('''feature_extractor'''    )

								UpperCamelCase__		:     Optional[Any]								=image_processor if image_processor is not None else feature_extractor
								if image_processor is None:
													raise ValueError('''You have to specify an image_processor.'''    )
								if tokenizer is None:
													raise ValueError('''You have to specify a tokenizer.'''    )

								super().__init__(lowercase_    ,	lowercase_    )
								UpperCamelCase__		:     Any								=self.image_processor






			def __call__(				self  :       Optional[Any]    ,	lowercase_  :       Any=None    ,	lowercase_  :       Tuple=None    ,	lowercase_  :       Union[str, Any]=None    ,	**lowercase_  :       str    ):

								if text is None and images is None:
													raise ValueError('''You have to specify either text or images. Both cannot be none.'''    )

								if text is not None:
													UpperCamelCase__		:     Optional[int]								=self.tokenizer(lowercase_    ,	return_tensors=lowercase_    ,	**lowercase_    )

								if images is not None:
													UpperCamelCase__		:     Optional[Any]								=self.image_processor(lowercase_    ,	return_tensors=lowercase_    ,	**lowercase_    )

								if text is not None and images is not None:
													UpperCamelCase__		:     List[str]								=image_features.pixel_values
													return encoding
								elif text is not None:
													return encoding
								else:
													return BatchEncoding(data=dict(**lowercase_    )    ,	tensor_type=lowercase_    )






			def  _lowerCAmelCase      (				self  :       Union[str, Any]    ,	*lowercase_  :       Tuple    ,	**lowercase_  :       Tuple    ):
								return self.tokenizer.batch_decode(*lowercase_    ,	**lowercase_    )






			def  _lowerCAmelCase      (				self  :       Optional[Any]    ,	*lowercase_  :       Optional[int]    ,	**lowercase_  :       Dict    ):
								return self.tokenizer.decode(*lowercase_    ,	**lowercase_    )






			@property
			def  _lowerCAmelCase      (				self  :       List[Any]    ):
								UpperCamelCase__		:     List[str]								=self.tokenizer.model_input_names
								UpperCamelCase__		:     Any								=self.image_processor.model_input_names
								return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names    )    )






			@property
			def  _lowerCAmelCase      (				self  :       str    ):
								warnings.warn(
								    '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'''    ,	lowercase_    ,	)
								return self.image_processor_class






			@property
			def  _lowerCAmelCase      (				self  :       int    ):
								warnings.warn(
								    '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'''    ,	lowercase_    ,	)
								return self.image_processor





"""simple docstring"""





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


_SCREAMING_SNAKE_CASE							:	Union[str, Any]										=			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:	Union[str, Any]										=			{"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_SCREAMING_SNAKE_CASE							:	List[Any]										=			{
    """vocab_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt""",
    },
    """tokenizer_file""": {
        """microsoft/mpnet-base""": """https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json""",
    },
}

_SCREAMING_SNAKE_CASE							:	List[Any]										=			{
    """microsoft/mpnet-base""": 5_1_2,
}

_SCREAMING_SNAKE_CASE							:	Optional[int]										=			{
    """microsoft/mpnet-base""": {"""do_lower_case""": True},
}

class      __a (   snake_case__     ):

			"""simple docstring"""

			SCREAMING_SNAKE_CASE_      =    VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_INIT_CONFIGURATION
			SCREAMING_SNAKE_CASE_      =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE_      =    MPNetTokenizer
			SCREAMING_SNAKE_CASE_      =    ['input_ids', 'attention_mask']






			def __init__(				self  :       List[str]    ,	lowercase_  :       List[Any]=None    ,	lowercase_  :       Optional[int]=None    ,	lowercase_  :       Optional[int]=True    ,	lowercase_  :       str="<s>"    ,	lowercase_  :       str="</s>"    ,	lowercase_  :       List[Any]="</s>"    ,	lowercase_  :       Tuple="<s>"    ,	lowercase_  :       Any="[UNK]"    ,	lowercase_  :       Dict="<pad>"    ,	lowercase_  :       Optional[Any]="<mask>"    ,	lowercase_  :       List[str]=True    ,	lowercase_  :       Optional[Any]=None    ,	**lowercase_  :       Dict    ,	):
								super().__init__(
								    lowercase_    ,	tokenizer_file=lowercase_    ,	do_lower_case=lowercase_    ,	bos_token=lowercase_    ,	eos_token=lowercase_    ,	sep_token=lowercase_    ,	cls_token=lowercase_    ,	unk_token=lowercase_    ,	pad_token=lowercase_    ,	mask_token=lowercase_    ,	tokenize_chinese_chars=lowercase_    ,	strip_accents=lowercase_    ,	**lowercase_    ,	)

								UpperCamelCase__		:     List[str]								=json.loads(self.backend_tokenizer.normalizer.__getstate__()    )
								if (
								    pre_tok_state.get('''lowercase'''    ,	lowercase_    ) != do_lower_case
								    or pre_tok_state.get('''strip_accents'''    ,	lowercase_    ) != strip_accents
								):
													UpperCamelCase__		:     int								=getattr(lowercase_    ,	pre_tok_state.pop('''type'''    )    )
													UpperCamelCase__		:     List[Any]								=do_lower_case
													UpperCamelCase__		:     Optional[Any]								=strip_accents
													UpperCamelCase__		:     Optional[int]								=pre_tok_class(**lowercase_    )

								UpperCamelCase__		:     Tuple								=do_lower_case






			@property
			def  _lowerCAmelCase      (				self  :       List[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  _lowerCAmelCase      (				self  :       int    ,	lowercase_  :       str    ):
								UpperCamelCase__		:     int								=AddedToken(lowercase_    ,	lstrip=lowercase_    ,	rstrip=lowercase_    ) if isinstance(lowercase_    ,	lowercase_    ) else value
								UpperCamelCase__		:     str								=value






			def  _lowerCAmelCase      (				self  :       Tuple    ,	lowercase_  :       Any    ,	lowercase_  :       Tuple=None    ):
								UpperCamelCase__		:     int								=[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  :       List[str]    ,	lowercase_  :       List[int]    ,	lowercase_  :       Optional[List[int]] = None    ):
								UpperCamelCase__		:     str								=[self.sep_token_id]
								UpperCamelCase__		:     List[str]								=[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]






			def  _lowerCAmelCase      (				self  :       str    ,	lowercase_  :       str    ,	lowercase_  :       Optional[str] = None    ):
								UpperCamelCase__		:     List[Any]								=self._tokenizer.model.save(lowercase_    ,	name=lowercase_    )
								return tuple(lowercase_    )


