



'''simple docstring'''





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    lowerCamelCase_       (							SCREAMING_SNAKE_CASE_	):
  """simple docstring"""




  a_				   =["""image_processor""", """tokenizer"""]
  a_				   ="""BlipImageProcessor"""
  a_				   =("""BertTokenizer""", """BertTokenizerFast""")




  def __init__(					self :      Tuple     ,      _a :      List[str]     ,      _a :      Tuple  )   ->   Tuple:
    __lowerCamelCase			:			Dict       			=					False
    super().__init__(_a     ,      _a  )
    __lowerCamelCase			:			str       			=					self.image_processor




  def __call__(					self :      str     ,      _a :      ImageInput = None     ,      _a :      Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None     ,      _a :      bool = True     ,      _a :      Union[bool, str, PaddingStrategy] = False     ,      _a :      Union[bool, str, TruncationStrategy] = None     ,      _a :      Optional[int] = None     ,      _a :      int = 0     ,      _a :      Optional[int] = None     ,      _a :      Optional[bool] = None     ,      _a :      bool = False     ,      _a :      bool = False     ,      _a :      bool = False     ,      _a :      bool = False     ,      _a :      bool = False     ,      _a :      bool = True     ,      _a :      Optional[Union[str, TensorType]] = None     ,      **_a :      List[Any]     ,      )   ->   BatchEncoding:
    if images is None and text is None:
      raise ValueError('You have to specify either images or text.'  )

    # Get only text
    if images is None:
      __lowerCamelCase			:			Tuple       			=					self.tokenizer
      __lowerCamelCase			:			Tuple       			=					self.tokenizer(
          text=_a     ,      add_special_tokens=_a     ,      padding=_a     ,      truncation=_a     ,      max_length=_a     ,      stride=_a     ,      pad_to_multiple_of=_a     ,      return_attention_mask=_a     ,      return_overflowing_tokens=_a     ,      return_special_tokens_mask=_a     ,      return_offsets_mapping=_a     ,      return_token_type_ids=_a     ,      return_length=_a     ,      verbose=_a     ,      return_tensors=_a     ,      **_a     ,      )
      return text_encoding

    # add pixel_values
    __lowerCamelCase			:			Dict       			=					self.image_processor(_a     ,      return_tensors=_a  )

    if text is not None:
      __lowerCamelCase			:			Tuple       			=					self.tokenizer(
          text=_a     ,      add_special_tokens=_a     ,      padding=_a     ,      truncation=_a     ,      max_length=_a     ,      stride=_a     ,      pad_to_multiple_of=_a     ,      return_attention_mask=_a     ,      return_overflowing_tokens=_a     ,      return_special_tokens_mask=_a     ,      return_offsets_mapping=_a     ,      return_token_type_ids=_a     ,      return_length=_a     ,      verbose=_a     ,      return_tensors=_a     ,      **_a     ,      )
    else:
      __lowerCamelCase			:			Optional[int]       			=					None

    if text_encoding is not None:
      encoding_image_processor.update(_a  )

    return encoding_image_processor




  def 		_lowercase	(					self :      Tuple     ,      *_a :      Dict     ,      **_a :      int  )   ->   Optional[int]:
    return self.tokenizer.batch_decode(*_a     ,      **_a  )




  def 		_lowercase	(					self :      Optional[int]     ,      *_a :      str     ,      **_a :      Dict  )   ->   List[Any]:
    return self.tokenizer.decode(*_a     ,      **_a  )




  @property
  def 		_lowercase	(					self :      Tuple  )   ->   Union[str, Any]:
    __lowerCamelCase			:			Dict       			=					self.tokenizer.model_input_names
    __lowerCamelCase			:			List[Any]       			=					self.image_processor.model_input_names
    return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names  )  )











'''simple docstring'''





import string

def 			a_	(				_lowerCAmelCase			) -> str:
  __lowerCamelCase			:			Union[str, Any]       			=					''
  for i in sequence:
    __lowerCamelCase			:			Tuple       			=					ord(_lowerCAmelCase			)
    if 65 <= extract <= 90:
      output += chr(155 - extract			)
    elif 97 <= extract <= 122:
      output += chr(219 - extract			)
    else:
      output += i
  return output

def 			a_	(				_lowerCAmelCase			) -> str:
  __lowerCamelCase			:			Optional[Any]       			=					string.ascii_letters
  __lowerCamelCase			:			str       			=					string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
  return "".join(
      letters_reversed[letters.index(_lowerCAmelCase			)] if c in letters else c for c in sequence			)

def 			a_	(				) -> None:
  from timeit import timeit

  print('Running performance benchmarks...'			)
  __lowerCamelCase			:			Tuple       			=					'from string import printable ; from __main__ import atbash, atbash_slow'
  print(F'> atbash_slow(): {timeit("atbash_slow(printable)"			,setup=_lowerCAmelCase			)} seconds'			)
  print(F'>      atbash(): {timeit("atbash(printable)"			,setup=_lowerCAmelCase			)} seconds'			)


if __name__ == "__main__":
   for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
      print(f'''{example} encrypted in atbash: {atbash(example)}''')
   benchmark()






