






import os
from shutil import copyfile
from typing import Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
				from .tokenization_reformer import ReformerTokenizer
else:
				UpperCamelCase__						:      Any								=					None


UpperCamelCase__						:      Dict								=					logging.get_logger(__name__)


UpperCamelCase__						:      List[Any]								=					"""▁"""

UpperCamelCase__						:      Union[str, Any]								=					{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

UpperCamelCase__						:      Union[str, Any]								=					{
    """vocab_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model"""
        )
    },
    """tokenizer_file""": {
        """google/reformer-crime-and-punishment""": (
            """https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json"""
        )
    },
}

UpperCamelCase__						:      Optional[int]								=					{
    """google/reformer-crime-and-punishment""": 524_288,
}







class 				lowerCamelCase_     (	a_     ):
							SCREAMING_SNAKE_CASE_						     =			VOCAB_FILES_NAMES
							SCREAMING_SNAKE_CASE_						     =			PRETRAINED_VOCAB_FILES_MAP
							SCREAMING_SNAKE_CASE_						     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							SCREAMING_SNAKE_CASE_						     =			['input_ids', 'attention_mask']
							SCREAMING_SNAKE_CASE_						     =			ReformerTokenizer
							def __init__(						self		:					Union[str, Any]							,__lowerCamelCase		:					List[Any]=None							,__lowerCamelCase		:					Optional[Any]=None							,__lowerCamelCase		:					int="</s>"							,__lowerCamelCase		:					List[str]="<unk>"							,__lowerCamelCase		:					Optional[Any]=[]							,**__lowerCamelCase		:					Optional[Any]							,):





								'''simple docstring'''



								super().__init__(
								    __lowerCamelCase							,tokenizer_file=__lowerCamelCase							,eos_token=__lowerCamelCase							,unk_token=__lowerCamelCase							,additional_special_tokens=__lowerCamelCase							,**__lowerCamelCase							,)

								a		=			vocab_file
								a		=			False if not self.vocab_file else True




							def  SCREAMING_SNAKE_CASE_ (						self		:					Dict							,__lowerCamelCase		:					str							,__lowerCamelCase		:					Optional[str] = None					):





								'''simple docstring'''



								if not self.can_save_slow_tokenizer:
									raise ValueError(
									    '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
									    '''tokenizer.'''					)

								if not os.path.isdir(__lowerCamelCase					):
									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""					)
									return
								a		=			os.path.join(
								    __lowerCamelCase							,(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

								if os.path.abspath(self.vocab_file					) != os.path.abspath(__lowerCamelCase					):
									copyfile(self.vocab_file							,__lowerCamelCase					)

								return (out_vocab_file,)













from __future__ import annotations

import sys







class 				lowerCamelCase_     :
							def __init__(						self		:					Optional[int]							,__lowerCamelCase		:					str							,__lowerCamelCase		:					int					):





								'''simple docstring'''



								a		=			letter
								a		=			freq
								a		=			{}




							def __repr__(						self		:					List[str]					):





								'''simple docstring'''



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







class 				lowerCamelCase_     :
							def __init__(						self		:					Dict							,__lowerCamelCase		:					int							,__lowerCamelCase		:					Letter | TreeNode							,__lowerCamelCase		:					Letter | TreeNode					):





								'''simple docstring'''



								a		=			freq
								a		=			left
								a		=			right





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  list[Letter]:


	"""simple docstring"""



	a		=			{}
	with open(snake_case_  ) 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(snake_case_,  snake_case_  ) for c, f in chars.items()),  key=lambda snake_case_  : x.freq  )





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  Letter | TreeNode:


	"""simple docstring"""



	a		=			letters  # type: ignore
	while len(snake_case_  ) > 1:
		a		=			response.pop(0  )
		a		=			response.pop(0  )
		a		=			left.freq + right.freq
		a		=			TreeNode(snake_case_,  snake_case_,  snake_case_  )
		response.append(snake_case_  )
		response.sort(key=lambda snake_case_  : x.freq  )
	return response[0]





def   SCREAMING_SNAKE_CASE__						(   snake_case_,  snake_case_  )   ->  list[Letter]:


	"""simple docstring"""



	if isinstance(snake_case_,  snake_case_  ):
		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__						(   snake_case_  )   ->  None:


	"""simple docstring"""



	a		=			parse_file(snake_case_  )
	a		=			build_tree(snake_case_  )
	a		=			{
	    k: v for letter in traverse_tree(snake_case_,  ''''''  ) for k, v in letter.bitstring.items()
	}
	print(f"""Huffman Coding  of {file_path}: """  )
	with open(snake_case_  ) 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])





