





"""simple docstring"""




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  lowerCAmelCase__(		lowercase    :      int				,       lowercase    :      str				,       lowercase    :      Tuple			)	->      List[str]:




  if not inplace:
    __snake_case				:			int            =    ma + ma
  else:
    ma += ma

  return ma







def  lowerCAmelCase__(		lowercase    :      List[str]				,       lowercase    :      int			)	->      int:
  __snake_case				:			Any            =    -1 * len(_UpperCamelCase			)
  __snake_case				:			Any            =    list(range(len(tensor.shape[:zero_index]			)			)			)
  return tensor.permute(first_inds + [zero_index + i for i in inds]			)







def  lowerCAmelCase__(		lowercase    :      Optional[Any]				,       lowercase    :      List[Any]			)	->      Optional[int]:
  return t.reshape(t.shape[:-no_dims] + (-1,)			)







def  lowerCAmelCase__(		lowercase    :      Optional[Any]				,       lowercase    :      List[Any]				,       lowercase    :      List[Any]				,       lowercase    :      Optional[int] = 1E-4			)	->      Union[str, Any]:
  __snake_case				:			Dict            =    mask.expand(*value.shape			)
  return torch.sum(mask * value				,       dim=_UpperCamelCase			) / (eps + torch.sum(_UpperCamelCase				,       dim=_UpperCamelCase			))







def  lowerCAmelCase__(		lowercase    :      List[str]				,       lowercase    :      Any = 2.3_1_2_5				,       lowercase    :      Dict = 2_1.6_8_7_5				,       lowercase    :      Optional[Any] = 64			)	->      Union[str, Any]:
  __snake_case				:			Dict            =    torch.linspace(_UpperCamelCase				,       _UpperCamelCase				,       no_bins - 1				,       device=pts.device			)
  __snake_case				:			Optional[int]            =    torch.sqrt(torch.sum((pts.unsqueeze(-2			) - pts.unsqueeze(-3			)) ** 2				,       dim=-1			)			)
  return torch.bucketize(_UpperCamelCase				,       _UpperCamelCase			)







def  lowerCAmelCase__(		lowercase    :      Optional[Any]				,       lowercase    :      List[Any]			)	->      Union[str, Any]:
  __snake_case				:			List[str]            =    dicts[0]
  __snake_case				:			Optional[Any]            =    {}
  for k, v in first.items():
    __snake_case				:			int            =    [d[k] for d in dicts]
    if isinstance(_UpperCamelCase				,       _UpperCamelCase			):
      __snake_case				:			int            =    dict_multimap(_UpperCamelCase				,       _UpperCamelCase			)
    else:
      __snake_case				:			Any            =    fn(_UpperCamelCase			)

  return new_dict







def  lowerCAmelCase__(		lowercase    :      Dict				,       lowercase    :      List[Any]			)	->      Optional[Any]:
  __snake_case				:			List[Any]            =    v_bins.view(((1,) * len(x.shape			)) + (len(_UpperCamelCase			),)			)
  __snake_case				:			Any            =    x[..., None] - reshaped_bins
  __snake_case				:			List[str]            =    torch.argmin(torch.abs(_UpperCamelCase			)				,       dim=-1			)
  return nn.functional.one_hot(_UpperCamelCase				,       num_classes=len(_UpperCamelCase			)			).float()







def  lowerCAmelCase__(		lowercase    :      Tuple				,       lowercase    :      int				,       lowercase    :      Dict = 0				,       lowercase    :      int = 0			)	->      List[Any]:
  __snake_case				:			List[Union[slice, torch.Tensor]]            =    []
  for i, s in enumerate(data.shape[:no_batch_dims]			):
    __snake_case				:			Optional[int]            =    torch.arange(_UpperCamelCase			)
    __snake_case				:			Tuple            =    r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape			) - i - 1)))			)
    ranges.append(_UpperCamelCase			)

  __snake_case				:			List[Union[slice, torch.Tensor]]            =    [slice(_UpperCamelCase			) for _ in range(len(data.shape			) - no_batch_dims			)]
  __snake_case				:			List[Any]            =    inds
  ranges.extend(_UpperCamelCase			)
  # 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(_UpperCamelCase			)]


_UpperCamelCase    =	TypeVar('''T''')







def  lowerCAmelCase__(		lowercase    :      Tuple				,       lowercase    :      Tuple				,       lowercase    :      List[str]			)	->      Tuple:
  __snake_case				:			Dict[Any, Union[dict, list, tuple, Any]]            =    {}
  for k, v in dic.items():
    if isinstance(_UpperCamelCase				,       _UpperCamelCase			):
      __snake_case				:			Optional[Any]            =    dict_map(_UpperCamelCase				,       _UpperCamelCase				,       _UpperCamelCase			)
    else:
      __snake_case				:			Tuple            =    tree_map(_UpperCamelCase				,       _UpperCamelCase				,       _UpperCamelCase			)

  return new_dict







@overload
def  lowerCAmelCase__(		lowercase    :      str				,       lowercase    :      List[Any]				,       lowercase    :      Any			)	->      Tuple:
  ...







@overload
def  lowerCAmelCase__(		lowercase    :      Dict				,       lowercase    :      Optional[int]				,       lowercase    :      int			)	->      Dict:
  ...







@overload
def  lowerCAmelCase__(		lowercase    :      Optional[Any]				,       lowercase    :      int				,       lowercase    :      int			)	->      Any:
  ...







@overload
def  lowerCAmelCase__(		lowercase    :      Union[str, Any]				,       lowercase    :      Dict				,       lowercase    :      Dict			)	->      Dict:
  ...







def  lowerCAmelCase__(		lowercase    :      Optional[Any]				,       lowercase    :      List[Any]				,       lowercase    :      Union[str, Any]			)	->      Any:




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




_UpperCamelCase    =	partial(tree_map, leaf_type=torch.Tensor)








from __future__ import annotations

import sys




class 			_lowerCamelCase	:



      """simple docstring"""






      def __init__(	self			,  UpperCAmelCase			,  UpperCAmelCase				)    ->				Union[str, Any]:






        '''simple docstring'''






        __snake_case				:			str            =    letter
        __snake_case				:			int            =    freq
        __snake_case				:			dict[str, str]            =    {}







      def __repr__(	self				)    ->				str:






        '''simple docstring'''






        return F"""{self.letter}:{self.freq}"""




class 			_lowerCamelCase	:



      """simple docstring"""






      def __init__(	self			,  UpperCAmelCase			,  UpperCAmelCase			,  UpperCAmelCase				)    ->				Any:






        '''simple docstring'''






        __snake_case				:			int            =    freq
        __snake_case				:			Letter | TreeNode            =    left
        __snake_case				:			Letter | TreeNode            =    right







def  lowerCAmelCase__(		lowercase    :      str			)	->      list[Letter]:
  __snake_case				:			dict[str, int]            =    {}
  with open(lowercase			) as f:
    while True:
      __snake_case				:			List[Any]            =    f.read(1			)
      if not c:
        break
      __snake_case				:			Optional[Any]            =    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  lowerCAmelCase__(		lowercase    :      list[Letter]			)	->      Letter | TreeNode:
  __snake_case				:			list[Letter | TreeNode]            =    letters  # type: ignore
  while len(lowercase			) > 1:
    __snake_case				:			Any            =    response.pop(0			)
    __snake_case				:			Optional[int]            =    response.pop(0			)
    __snake_case				:			str            =    left.freq + right.freq
    __snake_case				:			Dict            =    TreeNode(lowercase				,       lowercase				,       lowercase			)
    response.append(lowercase			)
    response.sort(key=lambda lowercase			: x.freq			)
  return response[0]







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







def  lowerCAmelCase__(		lowercase    :      str			)	->      None:
  __snake_case				:			List[Any]            =    parse_file(lowercase			)
  __snake_case				:			List[str]            =    build_tree(lowercase			)
  __snake_case				:			Optional[int]            =    {
      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:
      __snake_case				:			int            =    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])

