




'''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 		lowercase_   (			A       ):


   """simple docstring"""

   lowerCamelCase_      =						['''image_processor''', '''tokenizer''']
   lowerCamelCase_      =						'''BlipImageProcessor'''
   lowerCamelCase_      =						('''BertTokenizer''', '''BertTokenizerFast''')



   def __init__(   self :     List[str]  ,				__lowerCamelCase :     str  ,				__lowerCamelCase :     Optional[int]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				False
      super().__init__(__lowerCamelCase  ,				__lowerCamelCase   )
      _SCREAMING_SNAKE_CASE	=				self.image_processor



   def __call__(   self :     Tuple  ,				__lowerCamelCase :     ImageInput = None  ,				__lowerCamelCase :     Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None  ,				__lowerCamelCase :     bool = True  ,				__lowerCamelCase :     Union[bool, str, PaddingStrategy] = False  ,				__lowerCamelCase :     Union[bool, str, TruncationStrategy] = None  ,				__lowerCamelCase :     Optional[int] = None  ,				__lowerCamelCase :     int = 0  ,				__lowerCamelCase :     Optional[int] = None  ,				__lowerCamelCase :     Optional[bool] = None  ,				__lowerCamelCase :     bool = False  ,				__lowerCamelCase :     bool = False  ,				__lowerCamelCase :     bool = False  ,				__lowerCamelCase :     bool = False  ,				__lowerCamelCase :     bool = False  ,				__lowerCamelCase :     bool = True  ,				__lowerCamelCase :     Optional[Union[str, TensorType]] = None  ,				**__lowerCamelCase :     Dict  ,				):

      """simple docstring"""
      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:
         _SCREAMING_SNAKE_CASE	=				self.tokenizer
         _SCREAMING_SNAKE_CASE	=				self.tokenizer(
             text=__lowerCamelCase  ,				add_special_tokens=__lowerCamelCase  ,				padding=__lowerCamelCase  ,				truncation=__lowerCamelCase  ,				max_length=__lowerCamelCase  ,				stride=__lowerCamelCase  ,				pad_to_multiple_of=__lowerCamelCase  ,				return_attention_mask=__lowerCamelCase  ,				return_overflowing_tokens=__lowerCamelCase  ,				return_special_tokens_mask=__lowerCamelCase  ,				return_offsets_mapping=__lowerCamelCase  ,				return_token_type_ids=__lowerCamelCase  ,				return_length=__lowerCamelCase  ,				verbose=__lowerCamelCase  ,				return_tensors=__lowerCamelCase  ,				**__lowerCamelCase  ,				)
         return text_encoding

      # add pixel_values
      _SCREAMING_SNAKE_CASE	=				self.image_processor(__lowerCamelCase  ,				return_tensors=__lowerCamelCase   )

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

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

      return encoding_image_processor



   def 							lowerCAmelCase_      (   self :     str  ,				*__lowerCamelCase :     Dict  ,				**__lowerCamelCase :     List[Any]   ):

      """simple docstring"""
      return self.tokenizer.batch_decode(*__lowerCamelCase  ,				**__lowerCamelCase   )



   def 							lowerCAmelCase_      (   self :     List[str]  ,				*__lowerCamelCase :     Optional[Any]  ,				**__lowerCamelCase :     Union[str, Any]   ):

      """simple docstring"""
      return self.tokenizer.decode(*__lowerCamelCase  ,				**__lowerCamelCase   )



   @property
   def 							lowerCAmelCase_      (   self :     List[Any]   ):

      """simple docstring"""
      _SCREAMING_SNAKE_CASE	=				self.tokenizer.model_input_names
      _SCREAMING_SNAKE_CASE	=				self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )







'''simple docstring'''



def 			SCREAMING_SNAKE_CASE_			(							__A    :			list  )			->			list:
   if len(__A  ) <= 1:
      return lst

   _SCREAMING_SNAKE_CASE	=				1

   while i < len(__A  ):
      if lst[i - 1] <= lst[i]:
         i += 1
      else:
         _SCREAMING_SNAKE_CASE,	_SCREAMING_SNAKE_CASE	=				lst[i], lst[i - 1]
         i -= 1
         if i == 0:
            _SCREAMING_SNAKE_CASE	=				1

   return lst


if __name__ == "__main__":
 lowerCamelCase_			=						input('Enter numbers separated by a comma:\n').strip()
 lowerCamelCase_			=						[int(item) for item in user_input.split(',')]
 print(gnome_sort(unsorted))

