




"""simple docstring"""







from __future__ import annotations

import random
import string






class  SCREAMING_SNAKE_CASE__   :


						def __init__(							self			:     Union[str, Any]  ,  lowerCAmelCase			:     str | None = None   ):
										lowerCAmelCase		=			passcode or self.__passcode_creator()
										lowerCAmelCase		=			self.__make_key_list()
										lowerCAmelCase		=			self.__make_shift_key()


						def __str__(							self			:     str   ):
										return "".join(self.__passcode   )


						def 					__lowercase	(							self			:     str  ,  lowerCAmelCase			:     list[int]   ):
										for i in range(1  ,  len(lowerCAmelCase   )  ,  2   ):
														iterlist[i] *= -1
										return iterlist


						def 					__lowercase	(							self			:     Any   ):
										lowerCAmelCase		=			string.ascii_letters + string.digits
										lowerCAmelCase		=			[random.choice(lowerCAmelCase   ) for _ in range(random.randint(10  ,  20   )   )]
										return password


						def 					__lowercase	(							self			:     Tuple   ):
										lowerCAmelCase		=			(
										    string.ascii_letters + string.digits + string.punctuation + """ \t\n"""
										)

										lowerCAmelCase		=			[]

										# creates points known as breakpoints to break the key_list_options at those
										# points and pivot each substring
										lowerCAmelCase		=			sorted(set(self.__passcode   )   )
										lowerCAmelCase		=			[]

										# algorithm for creating a new shuffled list, keys_l, out of key_list_options
										for i in key_list_options:
														temp_list.extend(lowerCAmelCase   )

														# checking breakpoints at which to pivot temporary sublist and add it into
														# keys_l
														if i in breakpoints or i == key_list_options[-1]:
																		keys_l.extend(temp_list[::-1]   )
																		temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
										return keys_l


						def 					__lowercase	(							self			:     Union[str, Any]   ):
										lowerCAmelCase		=			sum(self.__neg_pos([ord(lowerCAmelCase   ) for x in self.__passcode]   )   )
										return num if num > 0 else len(self.__passcode   )


						def 					__lowercase	(							self			:     int  ,  lowerCAmelCase			:     str   ):
										lowerCAmelCase		=			""""""

										# decoding shift like Caesar cipher algorithm implementing negative shift or
										# reverse shift or left shift
										for i in encoded_message:
														lowerCAmelCase		=			self.__key_list.index(lowerCAmelCase   )
														decoded_message += self.__key_list[
														    (position - self.__shift_key) % -len(self.__key_list   )
														]

										return decoded_message




						def 					__lowercase	(							self			:     Optional[int]  ,  lowerCAmelCase			:     str   ):
										lowerCAmelCase		=			""""""

										# encoding shift like Caesar cipher algorithm implementing positive shift or
										# forward shift or right shift
										for i in plaintext:
														lowerCAmelCase		=			self.__key_list.index(lowerCAmelCase   )
														encoded_message += self.__key_list[
														    (position + self.__shift_key) % len(self.__key_list   )
														]

										return encoded_message





def 							lowercase   (snake_case__				:	str = "Hello, this is a modified Caesar cipher"	)       ->					str:


				'''simple docstring'''






				lowerCAmelCase		=			ShuffledShiftCipher()
				return cipa.decrypt(cipa.encrypt(snake_case__	)	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()











"""simple docstring"""







import warnings

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






class  SCREAMING_SNAKE_CASE__   (   _a   ):
						_a        =  ['image_processor', 'tokenizer']
						_a        =  'VideoMAEImageProcessor'
						_a        =  ('CLIPTokenizer', 'CLIPTokenizerFast')


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

										lowerCAmelCase		=			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__(lowerCAmelCase  ,  lowerCAmelCase   )
										lowerCAmelCase		=			self.image_processor


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

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

										if text is not None:
														lowerCAmelCase		=			self.tokenizer(lowerCAmelCase  ,  return_tensors=lowerCAmelCase  ,  **lowerCAmelCase   )

										if videos is not None:
														lowerCAmelCase		=			self.image_processor(lowerCAmelCase  ,  return_tensors=lowerCAmelCase  ,  **lowerCAmelCase   )

										if text is not None and videos is not None:
														lowerCAmelCase		=			image_features.pixel_values
														return encoding
										elif text is not None:
														return encoding
										else:
														return BatchEncoding(data=dict(**lowerCAmelCase   )  ,  tensor_type=lowerCAmelCase   )


						def 					__lowercase	(							self			:     str  ,  *lowerCAmelCase			:     List[str]  ,  **lowerCAmelCase			:     int   ):
										return self.tokenizer.batch_decode(*lowerCAmelCase  ,  **lowerCAmelCase   )


						def 					__lowercase	(							self			:     List[str]  ,  *lowerCAmelCase			:     Any  ,  **lowerCAmelCase			:     List[Any]   ):
										return self.tokenizer.decode(*lowerCAmelCase  ,  **lowerCAmelCase   )


						@property
						def 					__lowercase	(							self			:     Dict   ):
										return ["input_ids", "attention_mask", "position_ids", "pixel_values"]


						@property
						def 					__lowercase	(							self			:     List[str]   ):
										warnings.warn(
										    """`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."""  ,  lowerCAmelCase  ,  )
										return self.image_processor_class




						@property
						def 					__lowercase	(							self			:     Tuple   ):
										warnings.warn(
										    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""  ,  lowerCAmelCase  ,  )
										return self.image_processor





