


"""simple docstring"""







from typing import List, Optional, Union

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType




class 			UpperCamelCase_     (			UpperCamelCase):

	"""simple docstring"""





	snake_case__    :  Tuple    =      ["image_processor", "tokenizer"]
	snake_case__    :  int    =      "BridgeTowerImageProcessor"
	snake_case__    :  str    =      ("RobertaTokenizer", "RobertaTokenizerFast")




	def __init__(			self      :    int      ,      UpperCAmelCase__      :    Tuple      ,      UpperCAmelCase__      :    List[Any]       )	->     Tuple:
						super().__init__(UpperCAmelCase__      ,      UpperCAmelCase__       )




	def __call__(			self      :    int      ,      UpperCAmelCase__      :    Dict      ,      UpperCAmelCase__      :    Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None      ,      UpperCAmelCase__      :    bool = True      ,      UpperCAmelCase__      :    Union[bool, str, PaddingStrategy] = False      ,      UpperCAmelCase__      :    Union[bool, str, TruncationStrategy] = None      ,      UpperCAmelCase__      :    Optional[int] = None      ,      UpperCAmelCase__      :    int = 0      ,      UpperCAmelCase__      :    Optional[int] = None      ,      UpperCAmelCase__      :    Optional[bool] = None      ,      UpperCAmelCase__      :    Optional[bool] = None      ,      UpperCAmelCase__      :    bool = False      ,      UpperCAmelCase__      :    bool = False      ,      UpperCAmelCase__      :    bool = False      ,      UpperCAmelCase__      :    bool = False      ,      UpperCAmelCase__      :    bool = True      ,      UpperCAmelCase__      :    Optional[Union[str, TensorType]] = None      ,      **UpperCAmelCase__      :    int      ,      )	->     BatchEncoding:
						__SCREAMING_SNAKE_CASE						       =    self.tokenizer(
						    text=UpperCAmelCase__      ,      add_special_tokens=UpperCAmelCase__      ,      padding=UpperCAmelCase__      ,      truncation=UpperCAmelCase__      ,      max_length=UpperCAmelCase__      ,      stride=UpperCAmelCase__      ,      pad_to_multiple_of=UpperCAmelCase__      ,      return_token_type_ids=UpperCAmelCase__      ,      return_attention_mask=UpperCAmelCase__      ,      return_overflowing_tokens=UpperCAmelCase__      ,      return_special_tokens_mask=UpperCAmelCase__      ,      return_offsets_mapping=UpperCAmelCase__      ,      return_length=UpperCAmelCase__      ,      verbose=UpperCAmelCase__      ,      return_tensors=UpperCAmelCase__      ,      **UpperCAmelCase__      ,      )
						# add pixel_values + pixel_mask
						__SCREAMING_SNAKE_CASE						       =    self.image_processor(
						    UpperCAmelCase__      ,      return_tensors=UpperCAmelCase__      ,      do_normalize=UpperCAmelCase__      ,      do_center_crop=UpperCAmelCase__      ,      **UpperCAmelCase__       )
						encoding.update(UpperCAmelCase__       )

						return encoding




	def   UpperCAmelCase_				(			self      :    str      ,      *UpperCAmelCase__      :    Dict      ,      **UpperCAmelCase__      :    Optional[Any]       )	->     Optional[int]:
						return self.tokenizer.batch_decode(*UpperCAmelCase__      ,      **UpperCAmelCase__       )




	def   UpperCAmelCase_				(			self      :    Any      ,      *UpperCAmelCase__      :    Optional[Any]      ,      **UpperCAmelCase__      :    List[str]       )	->     Union[str, Any]:
						return self.tokenizer.decode(*UpperCAmelCase__      ,      **UpperCAmelCase__       )




	@property
	def   UpperCAmelCase_				(			self      :    Optional[int]       )	->     Optional[Any]:
						__SCREAMING_SNAKE_CASE						       =    self.tokenizer.model_input_names
						__SCREAMING_SNAKE_CASE						       =    self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names       )       )




"""simple docstring"""







def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


					return " ".join(
					    "".join(word[::-1]       ) if len(lowerCAmelCase_       ) > 4 else word for word in sentence.split()       )


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(reverse_long_words('''Hey wollef sroirraw'''))
