code: 
  
  
  
  
  
  
  from typing import List, Optional, Tuple, Union
  
  from . import logging
  from .import_utils import is_torch_available, is_torch_version
  
  
  if is_torch_available():
     import torch
  
  lowerCamelCase										=  logging.get_logger(__name__)  # pylint: disable=invalid-name
  
  try:
     from torch._dynamo import allow_in_graph as maybe_allow_in_graph
  except (ImportError, ModuleNotFoundError):
     def        UpperCAmelCase      (   cls      ):
  
  
         '''simple docstring'''
  
  
  
         return cls
  def        UpperCAmelCase      (   _lowercase,      _lowercase = None,      _lowercase = None,      _lowercase = None,      _lowercase = None,      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	device
      _lowercase     =	shape[0]
  
      _lowercase     =	layout or torch.strided
      _lowercase     =	device or torch.device('cpu'      )
  
      if generator is not None:
          _lowercase     =	generator.device.type if not isinstance(lowercase__,      lowercase__      ) else generator[0].device.type
          if gen_device_type != device.type and gen_device_type == "cpu":
              _lowercase     =	'cpu'
              if device != "mps":
                  logger.info(
                      f'''The passed generator was created on \'cpu\' even though a tensor on {device} was expected.'''
                      f''' Tensors will be created on \'cpu\' and then moved to {device}. Note that one can probably'''
                      f''' slighly speed up this function by passing a generator that was created on the {device} device.'''      )
          elif gen_device_type != device.type and gen_device_type == "cuda":
              raise ValueError(f'''Cannot generate a {device} tensor from a generator of type {gen_device_type}.'''      )
  
      if isinstance(lowercase__,      lowercase__      ):
          _lowercase     =	(1,) + shape[1:]
          _lowercase     =	[
              torch.randn(lowercase__,      generator=generator[i],      device=lowercase__,      dtype=lowercase__,      layout=lowercase__      )
              for i in range(lowercase__      )
          ]
          _lowercase     =	torch.cat(lowercase__,      dim=0      ).to(lowercase__      )
      else:
          _lowercase     =	torch.randn(lowercase__,      generator=lowercase__,      device=lowercase__,      dtype=lowercase__,      layout=lowercase__      ).to(lowercase__      )
  
      return latents
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      if is_torch_version('<',      '2.0.0'      ) or not hasattr(lowercase__,      '_dynamo'      ):
          return False
      return isinstance(lowercase__,      torch._dynamo.eval_frame.OptimizedModule      )
  
style_context: 
  
  
  
  
  
  
  from __future__ import annotations
  
  import sys
  
  class 					snake_case_							:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     def __init__(    self:	Any   ,       snake_case__:	str   ,       snake_case__:	int	)  ->		Optional[Any]:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	letter
         _lowercase     =	freq
         _lowercase     =	{}
  
     def __repr__(    self:	Optional[int]	)  ->		str:
  
  
         """simple docstring"""
  
  
  
         return f'''{self.letter}:{self.freq}'''
  
  
  
  
  
  
  class 					snake_case_							:
  
  
  
  
  
  
  
     """simple docstring"""
  
  
  
     def __init__(    self:	Optional[int]   ,       snake_case__:	int   ,       snake_case__:	Letter | TreeNode   ,       snake_case__:	Letter | TreeNode	)  ->		List[Any]:
  
  
         """simple docstring"""
  
  
  
         _lowercase     =	freq
         _lowercase     =	left
         _lowercase     =	right
  
  
  
  
  
  
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	{}
      with open(_lowercase      ) as f:
          while True:
              _lowercase     =	f.read(1      )
              if not c:
                  break
              _lowercase     =	chars[c] + 1 if c in chars else 1
      return sorted((Letter(_lowercase,      _lowercase      ) for c, f in chars.items()),      key=lambda _lowercase      : x.freq      )
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	letters  # type: ignore
      while len(_lowercase      ) > 1:
          _lowercase     =	response.pop(0      )
          _lowercase     =	response.pop(0      )
          _lowercase     =	left.freq + right.freq
          _lowercase     =	TreeNode(_lowercase,      _lowercase,      _lowercase      )
          response.append(_lowercase      )
          response.sort(key=lambda _lowercase      : x.freq      )
      return response[0]
  def        UpperCAmelCase      (   _lowercase,      _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      if isinstance(_lowercase,      _lowercase      ):
          _lowercase     =	bitstring
          return [root]
      _lowercase     =	root  # type: ignore
      _lowercase     =	[]
      letters += traverse_tree(treenode.left,      bitstring + '0'      )
      letters += traverse_tree(treenode.right,      bitstring + '1'      )
      return letters
  def        UpperCAmelCase      (   _lowercase      ):
  
  
      '''simple docstring'''
  
  
  
      _lowercase     =	parse_file(_lowercase      )
      _lowercase     =	build_tree(_lowercase      )
      _lowercase     =	{
          k: v for letter in traverse_tree(_lowercase,      ''      ) for k, v in letter.bitstring.items()
      }
      print(f'''Huffman Coding  of {file_path}: '''      )
      with open(_lowercase      ) as f:
          while True:
              _lowercase     =	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])
  