


"""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 _lowerCAmelCase				(      a__	):
   __UpperCAmelCase :       str							  =  ['''image_processor''', '''tokenizer''']
   __UpperCAmelCase :       Dict							  =  '''FlavaImageProcessor'''
   __UpperCAmelCase :       Dict							  =  ('''BertTokenizer''', '''BertTokenizerFast''')







   def __init__(	self						,	UpperCamelCase__=None						,	UpperCamelCase__=None						,	**UpperCamelCase__						)	->		List[Any]:

       '''simple docstring'''




       snake_case    :      Optional[Any]      					=    None
       if "feature_extractor" in kwargs:
           warnings.warn(
               "The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`"
               " instead."						,	UpperCamelCase_						,	)
           snake_case    :      List[str]      					=    kwargs.pop("feature_extractor"						)

       snake_case    :      int      					=    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__(UpperCamelCase_						,	UpperCamelCase_						)
       snake_case    :      List[str]      					=    self.image_processor







   def __call__(	self						,	UpperCamelCase__ = None						,	UpperCamelCase__ = None						,	UpperCamelCase__ = True						,	UpperCamelCase__ = False						,	UpperCamelCase__ = False						,	UpperCamelCase__ = None						,	UpperCamelCase__ = 0						,	UpperCamelCase__ = None						,	UpperCamelCase__ = None						,	UpperCamelCase__ = None						,	UpperCamelCase__ = None						,	UpperCamelCase__ = None						,	UpperCamelCase__ = False						,	UpperCamelCase__ = False						,	UpperCamelCase__ = False						,	UpperCamelCase__ = False						,	UpperCamelCase__ = True						,	UpperCamelCase__ = None						,	**UpperCamelCase__						,	)	->		Optional[int]:

       '''simple docstring'''




       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:
           snake_case    :      Optional[Any]      					=    self.tokenizer(
               text=UpperCamelCase_						,	add_special_tokens=UpperCamelCase_						,	padding=UpperCamelCase_						,	truncation=UpperCamelCase_						,	max_length=UpperCamelCase_						,	stride=UpperCamelCase_						,	pad_to_multiple_of=UpperCamelCase_						,	return_token_type_ids=UpperCamelCase_						,	return_attention_mask=UpperCamelCase_						,	return_overflowing_tokens=UpperCamelCase_						,	return_special_tokens_mask=UpperCamelCase_						,	return_offsets_mapping=UpperCamelCase_						,	return_length=UpperCamelCase_						,	verbose=UpperCamelCase_						,	return_tensors=UpperCamelCase_						,	**UpperCamelCase_						,	)
       if images is not None:
           snake_case    :      str      					=    self.image_processor(
               UpperCamelCase_						,	return_image_mask=UpperCamelCase_						,	return_codebook_pixels=UpperCamelCase_						,	return_tensors=UpperCamelCase_						,	**UpperCamelCase_						,	)

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







   def  lowerCamelCase		(	self						,	*UpperCamelCase__						,	**UpperCamelCase__						)	->		List[Any]:

       '''simple docstring'''




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







   def  lowerCamelCase		(	self						,	*UpperCamelCase__						,	**UpperCamelCase__						)	->		List[str]:

       '''simple docstring'''




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







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

       '''simple docstring'''




       snake_case    :      List[Any]      					=    self.tokenizer.model_input_names
       snake_case    :      int      					=    self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)







   @property
   def  lowerCamelCase		(	self						)	->		Any:

       '''simple docstring'''




       warnings.warn(
           "`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead."						,	UpperCamelCase_						,	)
       return self.image_processor_class







   @property
   def  lowerCamelCase		(	self						)	->		str:

       '''simple docstring'''




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









"""simple docstring"""





def    _snake_case  (  _snake_case :	list	):

      def merge(_snake_case :	list       ,      _snake_case :	list	) -> list:

            def _merge():
                  while left and right:
                        yield (left if left[0] <= right[0] else right).pop(0	)
                  yield from left
                  yield from right

            return list(_merge()	)

      if len(_snake_case	) <= 1:
            return collection
      lowerCAmelCase    :		Union[str, Any]				=      len(_snake_case	) // 2
      return merge(merge_sort(collection[:mid]	)       ,      merge_sort(collection[mid:]	)	)


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 snake_case__						:   Optional[Any]			 = input('''Enter numbers separated by a comma:\n''').strip()
 snake_case__						:   Union[str, Any]			 = [int(item) for item in user_input.split(''',''')]
 print(*merge_sort(unsorted), sep=''',''')


