




import warnings

from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding






class 	A	(						_lowerCAmelCase						):
     """simple docstring"""

     _snake_case:		Optional[Any]   =["image_processor", "tokenizer"]
     _snake_case:		Any   ="AutoImageProcessor"
     _snake_case:		Any   ="AutoTokenizer"




     def __init__(			self     :      str		,     A__     :      List[Any]=None		,     A__     :      Dict=None		,     **A__     :      str	) ->				List[str]:
           lowerCamelCase__					     = None
           if "feature_extractor" in kwargs:
                 warnings.warn(
                     'The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'
                     ' instead.'		,     A__		,     )
                 lowerCamelCase__					     = kwargs.pop('feature_extractor'	)

           lowerCamelCase__					     = image_processor if image_processor is not None else feature_extractor
           if image_processor is None:
                 raise ValueError('You have to specify an image_processor.'	)
           if tokenizer is None:
                 raise ValueError('You have to specify a tokenizer.'	)

           super().__init__(A__		,     A__	)
           lowerCamelCase__					     = self.image_processor




     def __call__(			self     :      Tuple		,     A__     :      Optional[int]=None		,     A__     :      Optional[int]=None		,     A__     :      List[str]=None		,     **A__     :      Union[str, Any]	) ->				Dict:

           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:
                 lowerCamelCase__					     = self.tokenizer(A__		,     return_tensors=A__		,     **A__	)

           if images is not None:
                 lowerCamelCase__					     = self.image_processor(A__		,     return_tensors=A__		,     **A__	)

           if text is not None and images is not None:
                 lowerCamelCase__					     = image_features.pixel_values
                 return encoding
           elif text is not None:
                 return encoding
           else:
                 return BatchEncoding(data=dict(**A__	)		,     tensor_type=A__	)




     def        __snake_case      (			self     :      Any		,     *A__     :      Optional[Any]		,     **A__     :      Tuple	) ->				Optional[Any]:
           return self.tokenizer.batch_decode(*A__		,     **A__	)




     def        __snake_case      (			self     :      Dict		,     *A__     :      Dict		,     **A__     :      str	) ->				Any:
           return self.tokenizer.decode(*A__		,     **A__	)




     @property
     def        __snake_case      (			self     :      Any	) ->				List[Any]:
           lowerCamelCase__					     = self.tokenizer.model_input_names
           lowerCamelCase__					     = self.image_processor.model_input_names
           return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names	)	)




     @property
     def        __snake_case      (			self     :      List[str]	) ->				List[str]:
           warnings.warn(
               '`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.'		,     A__		,     )
           return self.image_processor_class




     @property
     def        __snake_case      (			self     :      Dict	) ->				str:
           warnings.warn(
               '`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.'		,     A__		,     )
           return self.image_processor





from __future__ import annotations

import sys






class 	A	:
     """simple docstring"""

     def __init__(			self     :      str		,     A__     :      str		,     A__     :      int	) ->				str:
           lowerCamelCase__					     = letter
           lowerCamelCase__					     = freq
           lowerCamelCase__					     = {}




     def __repr__(			self     :      Any	) ->				str:
           return F"""{self.letter}:{self.freq}"""






class 	A	:
     """simple docstring"""

     def __init__(			self     :      Optional[Any]		,     A__     :      int		,     A__     :      Letter | TreeNode		,     A__     :      Letter | TreeNode	) ->				Any:
           lowerCamelCase__					     = freq
           lowerCamelCase__					     = left
           lowerCamelCase__					     = right

def 	lowerCAmelCase_	(     lowerCamelCase:				str  )    ->	list[Letter]:


      '''simple docstring'''




      lowerCamelCase__					     = {}
      with open(lowerCamelCase  ) as f:
            while True:
                  lowerCamelCase__					     = f.read(1  )
                  if not c:
                        break
                  lowerCamelCase__					     = chars[c] + 1 if c in chars else 1
      return sorted((Letter(lowerCamelCase   , lowerCamelCase  ) for c, f in chars.items())   , key=lambda lowerCamelCase  : x.freq  )

def 	lowerCAmelCase_	(     lowerCamelCase:				list[Letter]  )    ->	Letter | TreeNode:


      '''simple docstring'''




      lowerCamelCase__					     = letters  # type: ignore
      while len(lowerCamelCase  ) > 1:
            lowerCamelCase__					     = response.pop(0  )
            lowerCamelCase__					     = response.pop(0  )
            lowerCamelCase__					     = left.freq + right.freq
            lowerCamelCase__					     = TreeNode(lowerCamelCase   , lowerCamelCase   , lowerCamelCase  )
            response.append(lowerCamelCase  )
            response.sort(key=lambda lowerCamelCase  : x.freq  )
      return response[0]

def 	lowerCAmelCase_	(     lowerCamelCase:				Letter | TreeNode   , lowerCamelCase:				str  )    ->	list[Letter]:


      '''simple docstring'''




      if isinstance(lowerCamelCase   , lowerCamelCase  ):
            lowerCamelCase__					     = bitstring
            return [root]
      lowerCamelCase__					     = root  # type: ignore
      lowerCamelCase__					     = []
      letters += traverse_tree(treenode.left   , bitstring + '0'  )
      letters += traverse_tree(treenode.right   , bitstring + '1'  )
      return letters

def 	lowerCAmelCase_	(     lowerCamelCase:				str  )    ->	None:


      '''simple docstring'''




      lowerCamelCase__					     = parse_file(lowerCamelCase  )
      lowerCamelCase__					     = build_tree(lowerCamelCase  )
      lowerCamelCase__					     = {
          k: v for letter in traverse_tree(lowerCamelCase   , ''  ) for k, v in letter.bitstring.items()
      }
      print(f"""Huffman Coding  of {file_path}: """  )
      with open(lowerCamelCase  ) as f:
            while True:
                  lowerCamelCase__					     = f.read(1  )
                  if not c:
                        break
                  print(letters[c]   , end=' '  )
      print()


if __name__ == "__main__":
      # pass the file path to the huffman function
      huffman(sys.argv[1])