





import warnings

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



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''
 lowercase_						=     ["image_processor", "tokenizer"]
 lowercase_						=     "CLIPImageProcessor"
 lowercase_						=     ("XLMRobertaTokenizer", "XLMRobertaTokenizerFast")

 def __init__(self							:  List[Any]			,					UpperCAmelCase_							:  int=None			,					UpperCAmelCase_							:  List[Any]=None			,					**UpperCAmelCase_							:  List[str])			->Optional[int]:



   '''simple docstring'''



   lowerCamelCase__: Union[str, Any]         =None
   if "feature_extractor" in kwargs:
     warnings.warn(
         "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
         " instead."			,					UpperCAmelCase_			,					)
     lowerCamelCase__: int         =kwargs.pop("feature_extractor")

   lowerCamelCase__: int         =image_processor if image_processor is not None else feature_extractor
   if image_processor is None:
     raise ValueError("You need to specify an `image_processor`.")
   if tokenizer is None:
     raise ValueError("You need to specify a `tokenizer`.")

   super().__init__(UpperCAmelCase_			,					UpperCAmelCase_)

 def __call__(self							:  List[Any]			,					UpperCAmelCase_							:  str=None			,					UpperCAmelCase_							:  Optional[Any]=None			,					UpperCAmelCase_							:  int=None			,					**UpperCAmelCase_							:  Any)			->Union[str, Any]:



   '''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:
     lowerCamelCase__: List[Any]         =self.tokenizer(UpperCAmelCase_			,					return_tensors=UpperCAmelCase_			,					**UpperCAmelCase_)

   if images is not None:
     lowerCamelCase__: int         =self.image_processor(UpperCAmelCase_			,					return_tensors=UpperCAmelCase_			,					**UpperCAmelCase_)

   if text is not None and images is not None:
     lowerCamelCase__: str         =image_features.pixel_values
     return encoding
   elif text is not None:
     return encoding
   else:
     return BatchEncoding(data=dict(**UpperCAmelCase_)			,					tensor_type=UpperCAmelCase_)

 def 				SCREAMING_SNAKE_CASE_   (self							:  List[str]			,					*UpperCAmelCase_							:  Optional[Any]			,					**UpperCAmelCase_							:  Optional[Any])			->Dict:



   '''simple docstring'''



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

 def 				SCREAMING_SNAKE_CASE_   (self							:  Optional[int]			,					*UpperCAmelCase_							:  int			,					**UpperCAmelCase_							:  Any)			->Optional[Any]:



   '''simple docstring'''



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







 @property
 def 				SCREAMING_SNAKE_CASE_   (self							:  Optional[Any])			->Optional[int]:



   '''simple docstring'''



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







'''simple docstring'''







import numpy as np

lowercase      :   str      =       [
    ["""a""", """b""", """c""", """d""", """e"""],
    ["""f""", """g""", """h""", """i""", """k"""],
    ["""l""", """m""", """n""", """o""", """p"""],
    ["""q""", """r""", """s""", """t""", """u"""],
    ["""v""", """w""", """x""", """y""", """z"""],
]







class 					_a :





     '''simple docstring'''



     def __init__(				self							)      ->				None:
          snake_case			:      Dict        =			np.array(__a							)







     def 			snake_case_      (				self							,__a							)      ->				np.ndarray:
          snake_case ,		snake_case			:      Optional[Any]        =			np.where(letter == self.SQUARE							)
          snake_case			:      List[Any]        =			np.concatenate([indexa + 1, indexa + 1]							)
          return indexes







     def 			snake_case_      (				self							,__a							,__a							)      ->				str:
          snake_case			:      List[Any]        =			self.SQUARE[indexa - 1, indexa - 1]
          return letter







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      List[Any]        =			message.lower()
          snake_case			:      Dict        =			message.replace(""" """							,""""""							)
          snake_case			:      List[str]        =			message.replace("""j"""							,"""i"""							)

          snake_case			:      Optional[int]        =			np.empty((2, len(__a							))							)
          for letter_index in range(len(__a							)							):
               snake_case			:      Tuple        =			self.letter_to_numbers(message[letter_index]							)

               snake_case			:      Optional[Any]        =			numbers[0]
               snake_case			:      List[str]        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape(2 * len(__a							)							)
          snake_case			:      List[Any]        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      List[str]        =			int(second_step[numbers_index * 2]							)
               snake_case			:      List[Any]        =			int(second_step[(numbers_index * 2) + 1]							)
               snake_case			:      str        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      Any        =			encoded_message + letter

          return encoded_message







     def 			snake_case_      (				self							,__a							)      ->				str:
          snake_case			:      Any        =			message.lower()
          message.replace(""" """							,""""""							)
          snake_case			:      Dict        =			np.empty(2 * len(__a							)							)
          for letter_index in range(len(__a							)							):
               snake_case			:      str        =			self.letter_to_numbers(message[letter_index]							)
               snake_case			:      Any        =			numbers[0]
               snake_case			:      int        =			numbers[1]

          snake_case			:      List[str]        =			first_step.reshape((2, len(__a							))							)
          snake_case			:      Dict        =			""""""
          for numbers_index in range(len(__a							)							):
               snake_case			:      Optional[Any]        =			int(second_step[0, numbers_index]							)
               snake_case			:      Optional[int]        =			int(second_step[1, numbers_index]							)
               snake_case			:      Tuple        =			self.numbers_to_letter(__a							,__a							)
               snake_case			:      int        =			decoded_message + letter

          return decoded_message



