
'''simple docstring'''





import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE     =       logging.get_logger(__name__)

SCREAMING_SNAKE_CASE     =       """▁"""

SCREAMING_SNAKE_CASE     =       {"""vocab_file""": """sentencepiece.bpe.model"""}

SCREAMING_SNAKE_CASE     =       {
    """vocab_file""": {
        """facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model""",
    }
}

SCREAMING_SNAKE_CASE     =       {
    """facebook/xglm-564M""": 2_0_4_8,
}






class 							UpperCAmelCase_							(    A				):

 '''simple docstring'''
 lowercase_					:    str				=							VOCAB_FILES_NAMES
 lowercase_					:    Any				=							PRETRAINED_VOCAB_FILES_MAP
 lowercase_					:    Optional[Any]				=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowercase_					:    Any				=							["input_ids", "attention_mask"]







 def __init__(					self		:  List[str]			,				snake_case__		:  List[str]			,				snake_case__		:  int="<s>"			,				snake_case__		:  List[str]="</s>"			,				snake_case__		:  Union[str, Any]="</s>"			,				snake_case__		:  List[str]="<s>"			,				snake_case__		:  List[str]="<unk>"			,				snake_case__		:  Optional[int]="<pad>"			,				snake_case__		:  Optional[Dict[str, Any]] = None			,				**snake_case__		:  Tuple			,				):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							{} if sp_model_kwargs is None else sp_model_kwargs

   # Compatibility with the original tokenizer
   UpperCAmelCase__      :					int				       =							7
   UpperCAmelCase__      :					List[Any]				       =							[F"""<madeupword{i}>""" for i in range(self.num_madeup_words )]

   UpperCAmelCase__      :					List[str]				       =							kwargs.get("additional_special_tokens"			,				[] )
   kwargs["additional_special_tokens"] += [
       word for word in madeup_words if word not in kwargs["additional_special_tokens"]
   ]

   super().__init__(
       bos_token=snake_case__			,				eos_token=snake_case__			,				unk_token=snake_case__			,				sep_token=snake_case__			,				cls_token=snake_case__			,				pad_token=snake_case__			,				sp_model_kwargs=self.sp_model_kwargs			,				**snake_case__			,				)

   UpperCAmelCase__      :					List[str]				       =							spm.SentencePieceProcessor(**self.sp_model_kwargs )
   self.sp_model.Load(str(snake_case__ ) )
   UpperCAmelCase__      :					List[Any]				       =							vocab_file

   # Original fairseq vocab and spm vocab must be "aligned":
   # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
   # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
   # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
   # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

   # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
   UpperCAmelCase__      :					Dict				       =							1

   # Mimic fairseq token-to-id alignment for the first 4 token
   UpperCAmelCase__      :					List[Any]				       =							{"<s>": 0, "<pad>": 1, "</s>": 2, "<unk>": 3}

   UpperCAmelCase__      :					int				       =							len(self.sp_model )
   UpperCAmelCase__      :					int				       =							{F"""<madeupword{i}>""": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words )}
   self.fairseq_tokens_to_ids.update(snake_case__ )

   UpperCAmelCase__      :					str				       =							{v: k for k, v in self.fairseq_tokens_to_ids.items()}







 def __getstate__(					self		:  int ):



   '''simple docstring'''




   UpperCAmelCase__      :					str				       =							self.__dict__.copy()
   UpperCAmelCase__      :					Tuple				       =							None
   UpperCAmelCase__      :					Optional[Any]				       =							self.sp_model.serialized_model_proto()
   return state







 def __setstate__(					self		:  Optional[Any]			,				snake_case__		:  Tuple ):



   '''simple docstring'''




   UpperCAmelCase__      :					Tuple				       =							d

   # for backward compatibility
   if not hasattr(self			,				"sp_model_kwargs" ):
     UpperCAmelCase__      :					str				       =							{}

   UpperCAmelCase__      :					Tuple				       =							spm.SentencePieceProcessor(**self.sp_model_kwargs )
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto )







 def 							UpperCamelCase  (					self		:  Optional[Any]			,				snake_case__		:  List[int]			,				snake_case__		:  Optional[List[int]] = None ):



   '''simple docstring'''




   if token_ids_a is None:
     return [self.sep_token_id] + token_ids_a
   UpperCAmelCase__      :					List[str]				       =							[self.sep_token_id]
   return sep + token_ids_a + sep + sep + token_ids_a







 def 							UpperCamelCase  (					self		:  List[Any]			,				snake_case__		:  List[int]			,				snake_case__		:  Optional[List[int]] = None			,				snake_case__		:  bool = False ):



   '''simple docstring'''




   if already_has_special_tokens:
     return super().get_special_tokens_mask(
         token_ids_a=snake_case__			,				token_ids_a=snake_case__			,				already_has_special_tokens=snake_case__ )

   if token_ids_a is None:
     return [1] + ([0] * len(snake_case__ ))
   return [1] + ([0] * len(snake_case__ )) + [1, 1] + ([0] * len(snake_case__ ))







 def 							UpperCamelCase  (					self		:  List[str]			,				snake_case__		:  List[int]			,				snake_case__		:  Optional[List[int]] = None ):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							[self.sep_token_id]

   if token_ids_a is None:
     return len(sep + token_ids_a ) * [0]
   return len(sep + token_ids_a + sep + sep + token_ids_a ) * [0]







 @property
 def 							UpperCamelCase  (					self		:  List[Any] ):



   '''simple docstring'''




   return len(self.sp_model ) + self.fairseq_offset + self.num_madeup_words







 def 							UpperCamelCase  (					self		:  Dict ):



   '''simple docstring'''




   UpperCAmelCase__      :					Any				       =							{self.convert_ids_to_tokens(snake_case__ ): i for i in range(self.vocab_size )}
   vocab.update(self.added_tokens_encoder )
   return vocab







 def 							UpperCamelCase  (					self		:  Tuple			,				snake_case__		:  str ):



   '''simple docstring'''




   return self.sp_model.encode(snake_case__			,				out_type=snake_case__ )







 def 							UpperCamelCase  (					self		:  Optional[int]			,				snake_case__		:  str ):



   '''simple docstring'''




   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   UpperCAmelCase__      :					int				       =							self.sp_model.PieceToId(snake_case__ )

   # Need to return unknown token if the SP model returned 0
   return spm_id + self.fairseq_offset if spm_id else self.unk_token_id







 def 							UpperCamelCase  (					self		:  Any			,				snake_case__		:  int ):



   '''simple docstring'''




   if index in self.fairseq_ids_to_tokens:
     return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset )







 def 							UpperCamelCase  (					self		:  Dict			,				snake_case__		:  Any ):



   '''simple docstring'''




   UpperCAmelCase__      :					Optional[Any]				       =							"".join(snake_case__ ).replace(snake_case__			,				" " ).strip()
   return out_string







 def 							UpperCamelCase  (					self		:  str			,				snake_case__		:  str			,				snake_case__		:  Optional[str] = None ):



   '''simple docstring'''




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

   if os.path.abspath(self.vocab_file ) != os.path.abspath(snake_case__ ) and os.path.isfile(self.vocab_file ):
     copyfile(self.vocab_file			,				snake_case__ )
   elif not os.path.isfile(self.vocab_file ):
     with open(snake_case__			,				"wb" ) as fi:
       UpperCAmelCase__      :					Union[str, Any]				       =							self.sp_model.serialized_model_proto()
       fi.write(snake_case__ )

   return (out_vocab_file,)





'''simple docstring'''





def snake_case_     (					lowercase__		):
  return sum(i for i in range(1   ,       number // 2 + 1		) if number % i == 0		) == number


if __name__ == "__main__":
      print("""Program to check whether a number is a Perfect number or not...""")
      SCREAMING_SNAKE_CASE     =       int(input("""Enter number: """).strip())
      print(F'{number} is {"" if perfect(number) else "not "}a Perfect Number.')



