






import warnings

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







class 	A_       (      __lowerCamelCase       ):




	'''simple docstring'''


	_UpperCamelCase					:					Optional[Any]										=	["""image_processor""", """tokenizer"""]
	_UpperCamelCase					:					Dict										=	"""AutoImageProcessor"""
	_UpperCamelCase					:					Union[str, Any]										=	"""AutoTokenizer"""





	def __init__(	self		,   snake_case=None		,   snake_case=None		,   **snake_case	):
		lowercase					  =   None
		if "feature_extractor" in kwargs:
			warnings.warn(
			    'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
			    ' instead.'		,   snake_case		,   )
			lowercase					  =   kwargs.pop('feature_extractor'	)

		lowercase					  =   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__(snake_case		,   snake_case	)
		lowercase					  =   self.image_processor





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

		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:
			lowercase					  =   self.tokenizer(snake_case		,   return_tensors=snake_case		,   **snake_case	)

		if images is not None:
			lowercase					  =   self.image_processor(snake_case		,   return_tensors=snake_case		,   **snake_case	)

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





	def      SCREAMING_SNAKE_CASE__						(	self		,   *snake_case		,   **snake_case	):
		return self.tokenizer.batch_decode(*snake_case		,   **snake_case	)





	def      SCREAMING_SNAKE_CASE__						(	self		,   *snake_case		,   **snake_case	):
		return self.tokenizer.decode(*snake_case		,   **snake_case	)





	@property
	def      SCREAMING_SNAKE_CASE__						(	self	):
		lowercase					  =   self.tokenizer.model_input_names
		lowercase					  =   self.image_processor.model_input_names
		return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)





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





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



from string import ascii_uppercase






def 							UpperCAmelCase_		(							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE			,							__SCREAMING_SNAKE_CASE = False			,							__SCREAMING_SNAKE_CASE = ascii_uppercase							):
	lowercase					  =   keyword.upper()
	lowercase					  =   plaintext.upper()
	lowercase					  =   set(__SCREAMING_SNAKE_CASE							)

	# create a list of unique characters in the keyword - their order matters
	# it determines how we will map plaintext characters to the ciphertext
	lowercase					  =   []
	for char in keyword:
		if char in alphabet_set and char not in unique_chars:
			unique_chars.append(__SCREAMING_SNAKE_CASE							)
    # the number of those unique characters will determine the number of rows
	lowercase					  =   len(__SCREAMING_SNAKE_CASE							)

	# create a shifted version of the alphabet
	lowercase					  =   unique_chars + [
	    char for char in alphabet if char not in unique_chars
	]

	# create a modified alphabet by splitting the shifted alphabet into rows
	lowercase					  =   [
	    shifted_alphabet[k : k + num_unique_chars_in_keyword]
	    for k in range(0			,							26			,							__SCREAMING_SNAKE_CASE							)
	]

	# map the alphabet characters to the modified alphabet characters
	# going 'vertically' through the modified alphabet - consider columns first
	lowercase					  =   {}
	lowercase					  =   0
	for column in range(__SCREAMING_SNAKE_CASE							):
		for row in modified_alphabet:
			# if current row (the last one) is too short, break out of loop
			if len(__SCREAMING_SNAKE_CASE							) <= column:
				break

			# map current letter to letter in modified alphabet
			lowercase					  =   row[column]
			letter_index += 1

	if verbose:
		print(__SCREAMING_SNAKE_CASE							)
	# create the encrypted text by mapping the plaintext to the modified alphabet
	return "".join(mapping[char] if char in mapping else char for char in plaintext							)


if __name__ == "__main__":
	# example use
	print(mixed_keyword('''college''', '''UNIVERSITY'''))

