



import warnings

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





class 		__SCREAMING_SNAKE_CASE      (				snake_case__      ):






				"""simple docstring"""

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







				def __init__(				self						,	SCREAMING_SNAKE_CASE__=None						,	SCREAMING_SNAKE_CASE__=None						,	**SCREAMING_SNAKE_CASE__      ):






					"""simple docstring"""

					_snake_case					:							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_						,	)
						_snake_case					:							str					     =   kwargs.pop("""feature_extractor"""      )

					_snake_case					:							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_      )
					_snake_case					:							Any					     =   self.image_processor







				def __call__(				self						,	SCREAMING_SNAKE_CASE__=None						,	SCREAMING_SNAKE_CASE__=None						,	SCREAMING_SNAKE_CASE__=None						,	**SCREAMING_SNAKE_CASE__      ):






					"""simple docstring"""

					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:
						_snake_case					:							Optional[int]					     =   self.tokenizer(lowercase_						,	return_tensors=lowercase_						,	**lowercase_      )

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

					if text is not None and images is not None:
						_snake_case					:							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						,	*SCREAMING_SNAKE_CASE__						,	**SCREAMING_SNAKE_CASE__      ):






					"""simple docstring"""

					return self.tokenizer.batch_decode(*lowercase_						,	**lowercase_      )







				def 		__lowerCamelCase(				self						,	*SCREAMING_SNAKE_CASE__						,	**SCREAMING_SNAKE_CASE__      ):






					"""simple docstring"""

					return self.tokenizer.decode(*lowercase_						,	**lowercase_      )







				@property
				def 		__lowerCamelCase(				self      ):






					"""simple docstring"""

					_snake_case					:							List[str]					     =   self.tokenizer.model_input_names
					_snake_case					:							Any					     =   self.image_processor.model_input_names
					return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names      )      )







				@property
				def 		__lowerCamelCase(				self      ):






					"""simple docstring"""

					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      ):






					"""simple docstring"""

					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_    )


