






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      )








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])
