





import os
from typing import List, Optional, Union

from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
from ..auto import AutoTokenizer





class  lowerCAmelCase							(       lowercase_ ):
  __lowerCamelCase		=      ['image_processor', 'tokenizer']
  __lowerCamelCase		=      'BlipImageProcessor'
  __lowerCamelCase		=      'AutoTokenizer'







  def __init__(      self  :Tuple   ,							_lowercase  :Optional[int]   ,							_lowercase  :Any   ,							_lowercase  :Optional[int] ):






     '''simple docstring'''





     super().__init__(_lowercase   ,							_lowercase )

     # add QFormer tokenizer
     lowercase__			       =  qformer_tokenizer







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






     '''simple docstring'''





     if images is None and text is None:
        raise ValueError("You have to specify at least images or text." )

     lowercase__			       =  BatchFeature()

     if text is not None:
        lowercase__			       =  self.tokenizer(
            text=_lowercase   ,							add_special_tokens=_lowercase   ,							padding=_lowercase   ,							truncation=_lowercase   ,							max_length=_lowercase   ,							stride=_lowercase   ,							pad_to_multiple_of=_lowercase   ,							return_attention_mask=_lowercase   ,							return_overflowing_tokens=_lowercase   ,							return_special_tokens_mask=_lowercase   ,							return_offsets_mapping=_lowercase   ,							return_token_type_ids=_lowercase   ,							return_length=_lowercase   ,							verbose=_lowercase   ,							return_tensors=_lowercase   ,							**_lowercase   ,							)
        encoding.update(_lowercase )
        lowercase__			       =  self.qformer_tokenizer(
            text=_lowercase   ,							add_special_tokens=_lowercase   ,							padding=_lowercase   ,							truncation=_lowercase   ,							max_length=_lowercase   ,							stride=_lowercase   ,							pad_to_multiple_of=_lowercase   ,							return_attention_mask=_lowercase   ,							return_overflowing_tokens=_lowercase   ,							return_special_tokens_mask=_lowercase   ,							return_offsets_mapping=_lowercase   ,							return_token_type_ids=_lowercase   ,							return_length=_lowercase   ,							verbose=_lowercase   ,							return_tensors=_lowercase   ,							**_lowercase   ,							)
        lowercase__			       =  qformer_text_encoding.pop("input_ids" )
        lowercase__			       =  qformer_text_encoding.pop("attention_mask" )

     if images is not None:
        lowercase__			       =  self.image_processor(_lowercase   ,							return_tensors=_lowercase )
        encoding.update(_lowercase )

     return encoding







  def   UpperCAmelCase					(      self  :int   ,							*_lowercase  :int   ,							**_lowercase  :Optional[int] ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							*_lowercase  :Dict   ,							**_lowercase  :Union[str, Any] ):






     '''simple docstring'''





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







  @property
  # Copied from transformers.models.blip.processing_blip.BlipProcessor.model_input_names
  def   UpperCAmelCase					(      self  :List[str] ):






     '''simple docstring'''





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







  def   UpperCAmelCase					(      self  :Union[str, Any]   ,							_lowercase  :Optional[Any]   ,							**_lowercase  :int ):






     '''simple docstring'''





     if os.path.isfile(_lowercase ):
        raise ValueError(f'''Provided path ({save_directory}) should be a directory, not a file''' )
     os.makedirs(_lowercase   ,							exist_ok=_lowercase )
     lowercase__			       =  os.path.join(_lowercase   ,							"qformer_tokenizer" )
     self.qformer_tokenizer.save_pretrained(_lowercase )
     return super().save_pretrained(_lowercase   ,							**_lowercase )







  @classmethod
  def   UpperCAmelCase					(      cls  :Union[str, Any]   ,							_lowercase  :Optional[int]   ,							**_lowercase  :Optional[Any] ):






     '''simple docstring'''





     lowercase__			       =  AutoTokenizer.from_pretrained(_lowercase   ,							subfolder="qformer_tokenizer" )
     lowercase__			       =  cls._get_arguments_from_pretrained(_lowercase   ,							**_lowercase )
     args.append(_lowercase )
     return cls(*_lowercase )













def _A       (   __magic_name__	):
   try:
      lowercase__			       =  float(__magic_name__	)
   except ValueError:
      raise ValueError("Please enter a valid number"	)
   lowercase__			       =  decimal - int(__magic_name__	)
   if fractional_part == 0:
      return int(__magic_name__	), 1
   else:
      lowercase__			       =  len(str(__magic_name__	).split("."	)[1]	)
      lowercase__			       =  int(decimal * (10**number_of_frac_digits)	)
      lowercase__			       =  10**number_of_frac_digits
      lowercase__       ,							lowercase__			       =  denominator, numerator
      while True:
         lowercase__			       =  dividend % divisor
         if remainder == 0:
            break
         lowercase__       ,							lowercase__			       =  divisor, remainder
      lowercase__       ,							lowercase__			       =  numerator / divisor, denominator / divisor
      return int(__magic_name__	), int(__magic_name__	)


if __name__ == "__main__":
  print(F"""{decimal_to_fraction(2) = }""")
  print(F"""{decimal_to_fraction(89.0) = }""")
  print(F"""{decimal_to_fraction("67") = }""")
  print(F"""{decimal_to_fraction("45.0") = }""")
  print(F"""{decimal_to_fraction(1.5) = }""")
  print(F"""{decimal_to_fraction("6.25") = }""")
  print(F"""{decimal_to_fraction("78td") = }""")






