




from typing import Optional, Union

from ...file_utils import TensorType
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, TruncationStrategy
class 							__lowercase   (			a__    ):
     _lowerCAmelCase		       =						"MarkupLMFeatureExtractor"
     _lowerCAmelCase		       =						("MarkupLMTokenizer", "MarkupLMTokenizerFast")
     _lowerCAmelCase		       =						True



     def __call__(  self   :							str      ,		lowercase__   :							Tuple=None      ,		lowercase__   :							Optional[int]=None      ,		lowercase__   :							int=None      ,		lowercase__   :							int=None      ,		lowercase__   :							Any=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__   :							Optional[bool] = None      ,		lowercase__   :							bool = False      ,		lowercase__   :							bool = False      ,		lowercase__   :							bool = False      ,		lowercase__   :							bool = False      ,		lowercase__   :							bool = True      ,		lowercase__   :							Optional[Union[str, TensorType]] = None      ,		**lowercase__   :							str      ,		):
       # first, create nodes and xpaths
       if self.parse_html:
         if html_strings is None:
           raise ValueError('''Make sure to pass HTML strings in case `parse_html` is set to `True`'''       )

         if nodes is not None or xpaths is not None or node_labels is not None:
           raise ValueError(
               '''Please don\'t pass nodes, xpaths nor node labels in case `parse_html` is set to `True`'''       )

         a_		    =  self.feature_extractor(lowercase__       )
         a_		    =  features['''nodes''']
         a_		    =  features['''xpaths''']
       else:
         if html_strings is not None:
           raise ValueError('''You have passed HTML strings but `parse_html` is set to `False`.'''       )
         if nodes is None or xpaths is None:
           raise ValueError('''Make sure to pass nodes and xpaths in case `parse_html` is set to `False`'''       )

        # # second, apply the tokenizer
       if questions is not None and self.parse_html:
         if isinstance(lowercase__      ,		lowercase__       ):
           a_		    =  [questions]  # add batch dimension (as the feature extractor always adds a batch dimension)

       a_		    =  self.tokenizer(
           text=questions if questions is not None else nodes      ,		text_pair=nodes if questions is not None else None      ,		xpaths=lowercase__      ,		node_labels=lowercase__      ,		add_special_tokens=lowercase__      ,		padding=lowercase__      ,		truncation=lowercase__      ,		max_length=lowercase__      ,		stride=lowercase__      ,		pad_to_multiple_of=lowercase__      ,		return_token_type_ids=lowercase__      ,		return_attention_mask=lowercase__      ,		return_overflowing_tokens=lowercase__      ,		return_special_tokens_mask=lowercase__      ,		return_offsets_mapping=lowercase__      ,		return_length=lowercase__      ,		verbose=lowercase__      ,		return_tensors=lowercase__      ,		**lowercase__      ,		)

       return encoded_inputs



     def 				__magic_name__		(  self   :							Dict      ,		*lowercase__   :							Tuple      ,		**lowercase__   :							Optional[int]       ):
       return self.tokenizer.batch_decode(*lowercase__      ,		**lowercase__       )



     def 				__magic_name__		(  self   :							Dict      ,		*lowercase__   :							Union[str, Any]      ,		**lowercase__   :							List[Any]       ):
       return self.tokenizer.decode(*lowercase__      ,		**lowercase__       )



     @property
     def 				__magic_name__		(  self   :							int       ):
       a_		    =  self.tokenizer.model_input_names
       return tokenizer_input_names






from __future__ import annotations

import sys
class 							__lowercase   :



     def __init__(  self   :							Any      ,		lowercase__   :							str      ,		lowercase__   :							int       ):
       a_		    =  letter
       a_		    =  freq
       a_		    =  {}



     def __repr__(  self   :							List[Any]       ):
       return f"{self.letter}:{self.freq}"



class 							__lowercase   :



     def __init__(  self   :							Optional[int]      ,		lowercase__   :							int      ,		lowercase__   :							Letter | TreeNode      ,		lowercase__   :							Letter | TreeNode       ):
       a_		    =  freq
       a_		    =  left
       a_		    =  right






def 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


  a_		    =  {}
  with open(_A			) as f:
    while True:
      a_		    =  f.read(1			)
      if not c:
        break
      a_		    =  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 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


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






def 				UpperCAmelCase__  (							_A      ,      _A			):






  """simple docstring"""


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






def 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


  a_		    =  parse_file(_A			)
  a_		    =  build_tree(_A			)
  a_		    =  {
      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:
      a_		    =  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])
