
from __future__ import annotations

import sys





class      UpperCamelCase_			:







      '''simple docstring'''



      def __init__( self       :Optional[int]		,						lowerCAmelCase__       :str		,						lowerCAmelCase__       :int    )     ->int:
          lowercase						    =			letter
          lowercase						    =			freq
          lowercase						    =			{}





      def __repr__( self       :Tuple    )     ->List[Any]:
          return F'''{self.letter}:{self.freq}'''





class      UpperCamelCase_			:







      '''simple docstring'''



      def __init__( self       :str		,						lowerCAmelCase__       :int		,						lowerCAmelCase__       :Letter | TreeNode		,						lowerCAmelCase__       :Letter | TreeNode    )     ->Dict:
          lowercase						    =			freq
          lowercase						    =			left
          lowercase						    =			right




def    __snake_case       (  __magic_name__	):







    '''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 __magic_name__	: x.freq	)

def    __snake_case       (  __magic_name__	):







    '''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 __magic_name__	: x.freq	)
    return response[0]

def    __snake_case       (  __magic_name__		,						__magic_name__	):







    '''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    __snake_case       (  __magic_name__	):







    '''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])


from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				if not inplace:
								lowercase						    =			ma + ma
				else:
								ma += ma

				return ma

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			-1 * len(__magic_name__	)
				lowercase						    =			list(range(len(tensor.shape[:zero_index]	)	)	)
				return tensor.permute(first_inds + [zero_index + i for i in inds]	)

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				return t.reshape(t.shape[:-no_dims] + (-1,)	)

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__		,						__magic_name__ = 1e-4	):







				'''simple docstring'''


				lowercase						    =			mask.expand(*value.shape	)
				return torch.sum(mask * value		,						dim=__magic_name__	) / (eps + torch.sum(__magic_name__		,						dim=__magic_name__	))

def    __snake_case       (  __magic_name__		,						__magic_name__ = 2.3_1_2_5		,						__magic_name__ = 2_1.6_8_7_5		,						__magic_name__ = 64	):







				'''simple docstring'''


				lowercase						    =			torch.linspace(__magic_name__		,						__magic_name__		,						no_bins - 1		,						device=pts.device	)
				lowercase						    =			torch.sqrt(torch.sum((pts.unsqueeze(-2	) - pts.unsqueeze(-3	)) ** 2		,						dim=-1	)	)
				return torch.bucketize(__magic_name__		,						__magic_name__	)

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			dicts[0]
				lowercase						    =			{}
				for k, v in first.items():
								lowercase						    =			[d[k] for d in dicts]
								if isinstance(__magic_name__		,						__magic_name__	):
												lowercase						    =			dict_multimap(__magic_name__		,						__magic_name__	)
								else:
												lowercase						    =			fn(__magic_name__	)

				return new_dict

def    __snake_case       (  __magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			v_bins.view(((1,) * len(x.shape	)) + (len(__magic_name__	),)	)
				lowercase						    =			x[..., None] - reshaped_bins
				lowercase						    =			torch.argmin(torch.abs(__magic_name__	)		,						dim=-1	)
				return nn.functional.one_hot(__magic_name__		,						num_classes=len(__magic_name__	)	).float()

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__ = 0		,						__magic_name__ = 0	):







				'''simple docstring'''


				lowercase						    =			[]
				for i, s in enumerate(data.shape[:no_batch_dims]	):
								lowercase						    =			torch.arange(__magic_name__	)
								lowercase						    =			r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape	) - i - 1)))	)
								ranges.append(__magic_name__	)

				lowercase						    =			[slice(__magic_name__	) for _ in range(len(data.shape	) - no_batch_dims	)]
				lowercase						    =			inds
				ranges.extend(__magic_name__	)
				# Matt note: Editing this to get around the behaviour of using a list as an array index changing
				# in recent Numpy versions
				return data[tuple(__magic_name__	)]


_snake_case			:       List[Any]      =						TypeVar("T")

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				lowercase						    =			{}
				for k, v in dic.items():
								if isinstance(__magic_name__		,						__magic_name__	):
												lowercase						    =			dict_map(__magic_name__		,						__magic_name__		,						__magic_name__	)
								else:
												lowercase						    =			tree_map(__magic_name__		,						__magic_name__		,						__magic_name__	)

				return new_dict

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

@overload
def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				...

def    __snake_case       (  __magic_name__		,						__magic_name__		,						__magic_name__	):







				'''simple docstring'''


				if isinstance(__magic_name__		,						__magic_name__	):
								return dict_map(__magic_name__		,						__magic_name__		,						__magic_name__	)
				elif isinstance(__magic_name__		,						__magic_name__	):
								return [tree_map(__magic_name__		,						__magic_name__		,						__magic_name__	) for x in tree]
				elif isinstance(__magic_name__		,						__magic_name__	):
								return tuple(tree_map(__magic_name__		,						__magic_name__		,						__magic_name__	) for x in tree	)
				elif isinstance(__magic_name__		,						__magic_name__	):
								return fn(__magic_name__	)
				else:
								print(type(__magic_name__	)	)
								raise ValueError("Not supported"	)




_snake_case			:       Union[str, Any]      =						partial(tree_map, leaf_type=torch.Tensor)
