




"""simple docstring"""



from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE							=			logging.get_logger(__name__)

SCREAMING_SNAKE_CASE							=			{
    "squeezebert/squeezebert-uncased": (
        "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"
    ),
    "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json",
    "squeezebert/squeezebert-mnli-headless": (
        "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"
    ),
}




class       UpperCAmelCase_    (		A_				):
    lowercase__		   = SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
    lowercase__		   = '''squeezebert'''




    def __init__(       self		:			Any      ,					snake_case_		:			Tuple=30_522      ,					snake_case_		:			Optional[int]=768      ,					snake_case_		:			Tuple=12      ,					snake_case_		:			List[str]=12      ,					snake_case_		:			str=3_072      ,					snake_case_		:			str="gelu"      ,					snake_case_		:			List[str]=0.1      ,					snake_case_		:			int=0.1      ,					snake_case_		:			List[str]=512      ,					snake_case_		:			str=2      ,					snake_case_		:			Tuple=0.02      ,					snake_case_		:			Optional[Any]=1e-12      ,					snake_case_		:			List[Any]=0      ,					snake_case_		:			Dict=768      ,					snake_case_		:			Optional[int]=4      ,					snake_case_		:			Union[str, Any]=4      ,					snake_case_		:			Tuple=4      ,					snake_case_		:			List[Any]=1      ,					snake_case_		:			List[str]=4      ,					snake_case_		:			str=4      ,					**snake_case_		:			Dict      ,					) ->				Optional[Any]:




     '''simple docstring'''

     super().__init__(pad_token_id=snake_case_      ,					**snake_case_ )

     A__			=							vocab_size
     A__			=							hidden_size
     A__			=							num_hidden_layers
     A__			=							num_attention_heads
     A__			=							hidden_act
     A__			=							intermediate_size
     A__			=							hidden_dropout_prob
     A__			=							attention_probs_dropout_prob
     A__			=							max_position_embeddings
     A__			=							type_vocab_size
     A__			=							initializer_range
     A__			=							layer_norm_eps
     A__			=							embedding_size
     A__			=							q_groups
     A__			=							k_groups
     A__			=							v_groups
     A__			=							post_attention_groups
     A__			=							intermediate_groups
     A__			=							output_groups






class       UpperCAmelCase_    (		A_				):




    @property
    def 				__magic_name__				(       self		:			Any ) ->				Mapping[str, Mapping[int, str]]:




     '''simple docstring'''

     if self.task == "multiple-choice":
      A__			=							{0: "batch", 1: "choice", 2: "sequence"}
     else:
      A__			=							{0: "batch", 1: "sequence"}
     return OrderedDict(
         [
             ("input_ids", dynamic_axis),
             ("attention_mask", dynamic_axis),
             ("token_type_ids", dynamic_axis),
         ] )











"""simple docstring"""



from __future__ import annotations

import sys




class       UpperCAmelCase_    :




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




     '''simple docstring'''

     A__			=							letter
     A__			=							freq
     A__			=							{}




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




     '''simple docstring'''

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






class       UpperCAmelCase_    :




    def __init__(       self		:			Dict      ,					snake_case_		:			int      ,					snake_case_		:			Letter | TreeNode      ,					snake_case_		:			Letter | TreeNode ) ->				Optional[Any]:




     '''simple docstring'''

     A__			=							freq
     A__			=							left
     A__			=							right







def     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						list[Letter]:
 A__			=							{}
 with open(lowercase_		) 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(lowercase_     ,					lowercase_		) for c, f in chars.items())     ,					key=lambda lowercase_		: x.freq		)







def     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						Letter | TreeNode:
 A__			=							letters  # type: ignore
 while len(lowercase_		) > 1:
  A__			=							response.pop(0		)
  A__			=							response.pop(0		)
  A__			=							left.freq + right.freq
  A__			=							TreeNode(lowercase_     ,					lowercase_     ,					lowercase_		)
  response.append(lowercase_		)
  response.sort(key=lambda lowercase_		: x.freq		)
 return response[0]







def     _SCREAMING_SNAKE_CASE  (				lowercase_     ,					lowercase_		)		->						list[Letter]:
 if isinstance(lowercase_     ,					lowercase_		):
  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     _SCREAMING_SNAKE_CASE  (				lowercase_		)		->						None:
 A__			=							parse_file(lowercase_		)
 A__			=							build_tree(lowercase_		)
 A__			=							{
     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:
   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])





