



import warnings

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






class    SCREAMING_SNAKE_CASE			(							lowerCamelCase__					):

							'''simple docstring'''





							__lowerCamelCase	:	List[str]    =['image_processor', 'tokenizer']
							__lowerCamelCase	:	Tuple    ='ViTImageProcessor'
							__lowerCamelCase	:	Optional[int]    =('CLIPTokenizer', 'CLIPTokenizerFast')





							def __init__(   self		:		Optional[int]      ,				__lowercase		:		int=None      ,				__lowercase		:		Any=None      ,				**__lowercase		:		Any	):

											'''simple docstring'''
											__a       =		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      ,				)
															__a       =		kwargs.pop("""feature_extractor"""	)

											__a       =		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__(__lowercase      ,				__lowercase	)





							def __call__(   self		:		List[Any]      ,				__lowercase		:		Optional[int]=None      ,				__lowercase		:		Optional[int]=None      ,				__lowercase		:		List[str]=None      ,				__lowercase		:		Tuple=None      ,				**__lowercase		:		Optional[int]	):

											'''simple docstring'''
											if text is None and visual_prompt is None and images is None:
															raise ValueError("""You have to specify either text, visual prompt or images."""	)

											if text is not None and visual_prompt is not None:
															raise ValueError("""You have to specify exactly one type of prompt. Either text or visual prompt."""	)

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

											if visual_prompt is not None:
															__a       =		self.image_processor(__lowercase      ,				return_tensors=__lowercase      ,				**__lowercase	)

											if images is not None:
															__a       =		self.image_processor(__lowercase      ,				return_tensors=__lowercase      ,				**__lowercase	)

											if visual_prompt is not None and images is not None:
															__a       =		{
															    """pixel_values""": image_features.pixel_values,
															    """conditional_pixel_values""": prompt_features.pixel_values,
															}
															return encoding
											elif text is not None and images is not None:
															__a       =		image_features.pixel_values
															return encoding
											elif text is not None:
															return encoding
											elif visual_prompt is not None:
															__a       =		{
															    """conditional_pixel_values""": prompt_features.pixel_values,
															}
															return encoding
											else:
															return BatchEncoding(data=dict(**__lowercase	)      ,				tensor_type=__lowercase	)





							def 						UpperCamelCase_					(   self		:		List[str]      ,				*__lowercase		:		int      ,				**__lowercase		:		List[str]	):

											'''simple docstring'''
											return self.tokenizer.batch_decode(*__lowercase      ,				**__lowercase	)





							def 						UpperCamelCase_					(   self		:		Optional[Any]      ,				*__lowercase		:		List[str]      ,				**__lowercase		:		Any	):

											'''simple docstring'''
											return self.tokenizer.decode(*__lowercase      ,				**__lowercase	)





							@property
							def 						UpperCamelCase_					(   self		:		Any	):

											'''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 						UpperCamelCase_					(   self		:		Optional[Any]	):

											'''simple docstring'''
											warnings.warn(
											    """`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead."""      ,				__lowercase      ,				)
											return self.image_processor





import itertools
import string
from collections.abc import Generator, Iterable

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			Iterable[str]				,     _SCREAMING_SNAKE_CASE       :			int    ):
				"""simple docstring"""







				__a       =		iter(_SCREAMING_SNAKE_CASE    )
				while True:
								__a       =		tuple(itertools.islice(_SCREAMING_SNAKE_CASE				,     _SCREAMING_SNAKE_CASE    )    )
								if not chunk:
												return
								yield chunk

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				__a       =		"""""".join([c.upper() for c in dirty if c in string.ascii_letters]    )
				__a       =		""""""

				if len(_SCREAMING_SNAKE_CASE    ) < 2:
								return dirty

				for i in range(len(_SCREAMING_SNAKE_CASE    ) - 1    ):
								clean += dirty[i]

								if dirty[i] == dirty[i + 1]:
												clean += "X"

				clean += dirty[-1]

				if len(_SCREAMING_SNAKE_CASE    ) & 1:
								clean += "X"

				return clean

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				__a       =		"""ABCDEFGHIKLMNOPQRSTUVWXYZ"""
				# we're using a list instead of a '2d' array because it makes the math
				# for setting up the table and doing the actual encoding/decoding simpler
				__a       =		[]

				# copy key chars into the table if they are in `alphabet` ignoring duplicates
				for char in key.upper():
								if char not in table and char in alphabet:
												table.append(_SCREAMING_SNAKE_CASE    )

    # fill the rest of the table in with the remaining alphabet chars
				for char in alphabet:
								if char not in table:
												table.append(_SCREAMING_SNAKE_CASE    )

				return table

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str				,     _SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				__a       =		generate_table(_SCREAMING_SNAKE_CASE    )
				__a       =		prepare_input(_SCREAMING_SNAKE_CASE    )
				__a       =		""""""

				# https://en.wikipedia.org/wiki/Playfair_cipher#Description
				for chara, chara in chunker(_SCREAMING_SNAKE_CASE				,     2    ):
								__a     ,					__a       =		divmod(table.index(_SCREAMING_SNAKE_CASE    )				,     5    )
								__a     ,					__a       =		divmod(table.index(_SCREAMING_SNAKE_CASE    )				,     5    )

								if rowa == rowa:
												ciphertext += table[rowa * 5 + (cola + 1) % 5]
												ciphertext += table[rowa * 5 + (cola + 1) % 5]
								elif cola == cola:
												ciphertext += table[((rowa + 1) % 5) * 5 + cola]
												ciphertext += table[((rowa + 1) % 5) * 5 + cola]
								else:  # rectangle
												ciphertext += table[rowa * 5 + cola]
												ciphertext += table[rowa * 5 + cola]

				return ciphertext

def   lowerCAmelCase__						(							_SCREAMING_SNAKE_CASE       :			str				,     _SCREAMING_SNAKE_CASE       :			str    ):
				"""simple docstring"""







				__a       =		generate_table(_SCREAMING_SNAKE_CASE    )
				__a       =		""""""

				# https://en.wikipedia.org/wiki/Playfair_cipher#Description
				for chara, chara in chunker(_SCREAMING_SNAKE_CASE				,     2    ):
								__a     ,					__a       =		divmod(table.index(_SCREAMING_SNAKE_CASE    )				,     5    )
								__a     ,					__a       =		divmod(table.index(_SCREAMING_SNAKE_CASE    )				,     5    )

								if rowa == rowa:
												plaintext += table[rowa * 5 + (cola - 1) % 5]
												plaintext += table[rowa * 5 + (cola - 1) % 5]
								elif cola == cola:
												plaintext += table[((rowa - 1) % 5) * 5 + cola]
												plaintext += table[((rowa - 1) % 5) * 5 + cola]
								else:  # rectangle
												plaintext += table[rowa * 5 + cola]
												plaintext += table[rowa * 5 + cola]

				return plaintext
