



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					(    A		):
			UpperCamelCase           =  ['''image_processor''', '''tokenizer''']
			UpperCamelCase           =  '''BlipImageProcessor'''
			UpperCamelCase           =  ('''BertTokenizer''', '''BertTokenizerFast''')



			def __init__(		self     :						str				,	A     :						str				,	A     :						List[Any])     ->					List[str]:



						"""simple docstring"""






						_UpperCAmelCase	 =     False
						super().__init__(A				,	A)
						_UpperCAmelCase	 =     self.image_processor



			def __call__(		self     :						Union[str, Any]				,	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     :						int				,	)     ->					BatchEncoding:



						"""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:
									_UpperCAmelCase	 =     self.tokenizer
									_UpperCAmelCase	 =     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
						_UpperCAmelCase	 =     self.image_processor(A				,	return_tensors=A)

						if text is not None:
									_UpperCAmelCase	 =     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:
									_UpperCAmelCase	 =     None

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

						return encoding_image_processor



			def 					_lowerCamelCase (		self     :						Optional[int]				,	*A     :						Union[str, Any]				,	**A     :						Optional[Any])     ->					List[str]:



						"""simple docstring"""






						return self.tokenizer.batch_decode(*A				,	**A)



			def 					_lowerCamelCase (		self     :						str				,	*A     :						str				,	**A     :						Tuple)     ->					Optional[int]:



						"""simple docstring"""






						return self.tokenizer.decode(*A				,	**A)



			@property
			def 					_lowerCamelCase (		self     :						Optional[Any])     ->					Optional[Any]:



						"""simple docstring"""






						_UpperCAmelCase	 =     self.tokenizer.model_input_names
						_UpperCAmelCase	 =     self.image_processor.model_input_names
						return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names))





def 							A			(  _UpperCAmelCase       :     list					)       ->				list:







			'''simple docstring'''
			if len(_UpperCAmelCase					) <= 1:
						return lst

			_UpperCAmelCase	 =     1

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

			return lst


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