"""simple docstring"""



import warnings
from typing import List, Optional, Union

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






class 				snake_case__     (   snake_case_   ):
	_snake_case   :			str           =		["""image_processor""", """tokenizer"""]
	_snake_case   :			Optional[int]           =		"""FlavaImageProcessor"""
	_snake_case   :			Any           =		("""BertTokenizer""", """BertTokenizerFast""")


	def __init__(				self  ,						lowerCamelCase=None  ,						lowerCamelCase=None  ,						**lowerCamelCase		):
								__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."  ,						lowerCamelCase  ,						)
															__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__(lowerCamelCase  ,						lowerCamelCase		)
								__a     				=  self.image_processor


	def __call__(				self  ,						lowerCamelCase = None  ,						lowerCamelCase = None  ,						lowerCamelCase = True  ,						lowerCamelCase = False  ,						lowerCamelCase = False  ,						lowerCamelCase = None  ,						lowerCamelCase = 0  ,						lowerCamelCase = None  ,						lowerCamelCase = None  ,						lowerCamelCase = None  ,						lowerCamelCase = None  ,						lowerCamelCase = None  ,						lowerCamelCase = False  ,						lowerCamelCase = False  ,						lowerCamelCase = False  ,						lowerCamelCase = False  ,						lowerCamelCase = True  ,						lowerCamelCase = None  ,						**lowerCamelCase  ,						):

								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:
															__a     				=  self.tokenizer(
															    text=lowerCamelCase  ,						add_special_tokens=lowerCamelCase  ,						padding=lowerCamelCase  ,						truncation=lowerCamelCase  ,						max_length=lowerCamelCase  ,						stride=lowerCamelCase  ,						pad_to_multiple_of=lowerCamelCase  ,						return_token_type_ids=lowerCamelCase  ,						return_attention_mask=lowerCamelCase  ,						return_overflowing_tokens=lowerCamelCase  ,						return_special_tokens_mask=lowerCamelCase  ,						return_offsets_mapping=lowerCamelCase  ,						return_length=lowerCamelCase  ,						verbose=lowerCamelCase  ,						return_tensors=lowerCamelCase  ,						**lowerCamelCase  ,						)
								if images is not None:
															__a     				=  self.image_processor(
															    lowerCamelCase  ,						return_image_mask=lowerCamelCase  ,						return_codebook_pixels=lowerCamelCase  ,						return_tensors=lowerCamelCase  ,						**lowerCamelCase  ,						)

								if text is not None and images is not None:
															encoding.update(lowerCamelCase		)
															return encoding
								elif text is not None:
															return encoding
								else:
															return BatchEncoding(data=dict(**lowerCamelCase		)  ,						tensor_type=lowerCamelCase		)


	def 		a__ (				self  ,						*lowerCamelCase  ,						**lowerCamelCase		):
								return self.tokenizer.batch_decode(*lowerCamelCase  ,						**lowerCamelCase		)


	def 		a__ (				self  ,						*lowerCamelCase  ,						**lowerCamelCase		):
								return self.tokenizer.decode(*lowerCamelCase  ,						**lowerCamelCase		)


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


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

"""simple docstring"""



import string

# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
SCREAMING_SNAKE_CASE__:Any			=	{
    """E""": 12.70,
    """T""": 9.06,
    """A""": 8.17,
    """O""": 7.51,
    """I""": 6.97,
    """N""": 6.75,
    """S""": 6.33,
    """H""": 6.09,
    """R""": 5.99,
    """D""": 4.25,
    """L""": 4.03,
    """C""": 2.78,
    """U""": 2.76,
    """M""": 2.41,
    """W""": 2.36,
    """F""": 2.23,
    """G""": 2.02,
    """Y""": 1.97,
    """P""": 1.93,
    """B""": 1.29,
    """V""": 0.98,
    """K""": 0.77,
    """J""": 0.15,
    """X""": 0.15,
    """Q""": 0.10,
    """Z""": 0.07,
}
SCREAMING_SNAKE_CASE__:Optional[int]			=	"""ETAOINSHRDLCUMWFGYPBVKJXQZ"""
SCREAMING_SNAKE_CASE__:Tuple			=	"""ABCDEFGHIJKLMNOPQRSTUVWXYZ"""



def 					_lowerCamelCase(					a							):
       __a     				=  {letter: 0 for letter in string.ascii_uppercase}
       for letter in message.upper():
              if letter in LETTERS:
                     letter_count[letter] += 1

       return letter_count



def 					_lowerCamelCase(					a							):
       return x[0]



def 					_lowerCamelCase(					a							):
       __a     				=  get_letter_count(a							)
       __a     				=  {
           freq: [] for letter, freq in letter_to_freq.items()
       }
       for letter in LETTERS:
              freq_to_letter[letter_to_freq[letter]].append(a							)

       __a     				=  {}

       for freq in freq_to_letter:
              freq_to_letter[freq].sort(key=ETAOIN.find ,  reverse=a							)
              __a     				=  "".join(freq_to_letter[freq]							)

       __a     				=  list(freq_to_letter_str.items()							)
       freq_pairs.sort(key=a ,  reverse=a							)

       __a     				=  [freq_pair[1] for freq_pair in freq_pairs]

       return "".join(a							)



def 					_lowerCamelCase(					a							):
       __a     				=  get_frequency_order(a							)
       __a     				=  0
       for common_letter in ETAOIN[:6]:
              if common_letter in freq_order[:6]:
                     match_score += 1

       for uncommon_letter in ETAOIN[-6:]:
              if uncommon_letter in freq_order[-6:]:
                     match_score += 1

       return match_score


if __name__ == "__main__":
   import doctest

   doctest.testmod()
