





import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig


UpperCAmelCase_       : Optional[Any]							=    logging.get_logger(__name__)





class   lowercase__     (				__A	):
  __UpperCamelCase						  =	"""speech-encoder-decoder"""
  __UpperCamelCase						  =	True







  def __init__(						self     ,    **_lowercase    ):
       super().__init__(**_lowercase    )
       if "encoder" not in kwargs or "decoder" not in kwargs:
            raise ValueError(
                F'A configuraton of type {self.model_type} cannot be instantiated because not both `encoder` and'
                F' `decoder` sub-configurations are passed, but only {kwargs}'    )

       lowerCAmelCase_       :							Optional[int]			 =		kwargs.pop("""encoder"""    )
       lowerCAmelCase_       :							Optional[int]			 =		encoder_config.pop("""model_type"""    )
       lowerCAmelCase_       :							Any			 =		kwargs.pop("""decoder"""    )
       lowerCAmelCase_       :							Tuple			 =		decoder_config.pop("""model_type"""    )

       lowerCAmelCase_       :							Union[str, Any]			 =		AutoConfig.for_model(_lowercase     ,    **_lowercase    )
       lowerCAmelCase_       :							List[Any]			 =		AutoConfig.for_model(_lowercase     ,    **_lowercase    )
       lowerCAmelCase_       :							Optional[Any]			 =		True







  @classmethod
  def 						UpperCAmelCase__		(						cls     ,    _lowercase     ,    _lowercase     ,    **_lowercase    ):
       logger.info("""Setting `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"""    )
       lowerCAmelCase_       :							Optional[int]			 =		True
       lowerCAmelCase_       :							str			 =		True

       return cls(encoder=encoder_config.to_dict()     ,    decoder=decoder_config.to_dict()     ,    **_lowercase    )







  def 						UpperCAmelCase__		(						self    ):
       lowerCAmelCase_       :							Any			 =		copy.deepcopy(self.__dict__    )
       lowerCAmelCase_       :							Dict			 =		self.encoder.to_dict()
       lowerCAmelCase_       :							List[str]			 =		self.decoder.to_dict()
       lowerCAmelCase_       :							List[Any]			 =		self.__class__.model_type
       return output







from __future__ import annotations

import sys





class   lowercase__     :







  def __init__(						self     ,    _lowercase     ,    _lowercase    ):
       lowerCAmelCase_       :							str			 =		letter
       lowerCAmelCase_       :							int			 =		freq
       lowerCAmelCase_       :							dict[str, str]			 =		{}







  def __repr__(						self    ):
       return F'{self.letter}:{self.freq}'





class   lowercase__     :







  def __init__(						self     ,    _lowercase     ,    _lowercase     ,    _lowercase    ):
       lowerCAmelCase_       :							int			 =		freq
       lowerCAmelCase_       :							Letter | TreeNode			 =		left
       lowerCAmelCase_       :							Letter | TreeNode			 =		right






def 				_lowerCAmelCase			(	_a :       str      )						->      list[Letter]:
     lowerCAmelCase_       :							dict[str, int]			 =		{}
     with open(_a      ) as f:
          while True:
               lowerCAmelCase_       :							Any			 =		f.read(1      )
               if not c:
                    break
               lowerCAmelCase_       :							List[str]			 =		chars[c] + 1 if c in chars else 1
     return sorted((Letter(_a       , _a      ) for c, f in chars.items())       , key=lambda _a      : x.freq      )






def 				_lowerCAmelCase			(	_a :       list[Letter]      )						->      Letter | TreeNode:
     lowerCAmelCase_       :							list[Letter | TreeNode]			 =		letters  # type: ignore
     while len(_a      ) > 1:
          lowerCAmelCase_       :							Any			 =		response.pop(0      )
          lowerCAmelCase_       :							int			 =		response.pop(0      )
          lowerCAmelCase_       :							List[Any]			 =		left.freq + right.freq
          lowerCAmelCase_       :							Union[str, Any]			 =		TreeNode(_a       , _a       , _a      )
          response.append(_a      )
          response.sort(key=lambda _a      : x.freq      )
     return response[0]






def 				_lowerCAmelCase			(	_a :       Letter | TreeNode       , _a :       str      )						->      list[Letter]:
     if isinstance(_a       , _a      ):
          lowerCAmelCase_       :							Union[str, Any]			 =		bitstring
          return [root]
     lowerCAmelCase_       :							TreeNode			 =		root  # type: ignore
     lowerCAmelCase_       :							Tuple			 =		[]
     letters += traverse_tree(treenode.left       , bitstring + """0"""      )
     letters += traverse_tree(treenode.right       , bitstring + """1"""      )
     return letters






def 				_lowerCAmelCase			(	_a :       str      )						->      None:
     lowerCAmelCase_       :							Optional[Any]			 =		parse_file(_a      )
     lowerCAmelCase_       :							Optional[int]			 =		build_tree(_a      )
     lowerCAmelCase_       :							str			 =		{
         k: v for letter in traverse_tree(_a       , """"""      ) for k, v in letter.bitstring.items()
     }
     print(F'Huffman Coding  of {file_path}: '      )
     with open(_a      ) as f:
          while True:
               lowerCAmelCase_       :							Optional[Any]			 =		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])
