






"""simple docstring"""







from __future__ import annotations

from collections.abc import Sequence
from typing import Literal

def _a			(		_snake_case				,	_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	list(_snake_case							)
      UpperCAmelCase          =	list(_snake_case							)
      UpperCAmelCase          =	0
      for i in range(len(_snake_case							)							):
            if lista[i] != lista[i]:
                  count += 1
                  UpperCAmelCase          =	"""_"""
      if count > 1:
            return False
      else:
            return "".join(_snake_case							)

def _a			(		_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]
      while True:
            UpperCAmelCase          =	["""$"""] * len(_snake_case							)
            UpperCAmelCase          =	[]
            for i in range(len(_snake_case							)							):
                  for j in range(i + 1				,	len(_snake_case							)							):
                        UpperCAmelCase          =	compare_string(binary[i]				,	binary[j]							)
                        if k is False:
                              UpperCAmelCase          =	"""*"""
                              UpperCAmelCase          =	"""*"""
                              temp.append("""X"""							)
            for i in range(len(_snake_case							)							):
                  if checka[i] == "$":
                        pi.append(binary[i]							)
            if len(_snake_case							) == 0:
                  return pi
            UpperCAmelCase          =	list(set(_snake_case							)							)

def _a			(		_snake_case				,	_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]
      for minterm in minterms:
            UpperCAmelCase          =	""""""
            for _ in range(_snake_case							):
                  UpperCAmelCase          =	str(minterm % 2							) + string
                  minterm //= 2
            temp.append(_snake_case							)
      return temp

def _a			(		_snake_case				,	_snake_case				,	_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	list(_snake_case							)
      UpperCAmelCase          =	list(_snake_case							)
      UpperCAmelCase          =	0
      for i in range(len(_snake_case							)							):
            if lista[i] != lista[i]:
                  count_n += 1
      return count_n == count

def _a			(		_snake_case				,	_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[]
      UpperCAmelCase          =	[0] * len(_snake_case							)
      for i in range(len(chart[0]							)							):
            UpperCAmelCase          =	0
            UpperCAmelCase          =	-1
            for j in range(len(_snake_case							)							):
                  if chart[j][i] == 1:
                        count += 1
                        UpperCAmelCase          =	j
            if count == 1:
                  UpperCAmelCase          =	1
      for i in range(len(_snake_case							)							):
            if select[i] == 1:
                  for j in range(len(chart[0]							)							):
                        if chart[i][j] == 1:
                              for k in range(len(_snake_case							)							):
                                    UpperCAmelCase          =	0
                  temp.append(prime_implicants[i]							)
      while True:
            UpperCAmelCase          =	0
            UpperCAmelCase          =	-1
            UpperCAmelCase          =	0
            for i in range(len(_snake_case							)							):
                  UpperCAmelCase          =	chart[i].count(1							)
                  if count_n > max_n:
                        UpperCAmelCase          =	count_n
                        UpperCAmelCase          =	i

            if max_n == 0:
                  return temp

            temp.append(prime_implicants[rem]							)

            for i in range(len(chart[0]							)							):
                  if chart[rem][i] == 1:
                        for j in range(len(_snake_case							)							):
                              UpperCAmelCase          =	0

def _a			(		_snake_case				,	_snake_case							):







      """simple docstring"""






      UpperCAmelCase          =	[[0 for x in range(len(_snake_case							)							)] for x in range(len(_snake_case							)							)]
      for i in range(len(_snake_case							)							):
            UpperCAmelCase          =	prime_implicants[i].count("""_"""							)
            for j in range(len(_snake_case							)							):
                  if is_for_table(prime_implicants[i]				,	binary[j]				,	_snake_case							):
                        UpperCAmelCase          =	1

      return chart

def _a			(		):







      """simple docstring"""






      UpperCAmelCase          =	int(input("""Enter the no. of variables\n"""							)							)
      UpperCAmelCase          =	[
          float(_snake_case							)
          for x in input(
              """Enter the decimal representation of Minterms 'Spaces Separated'\n"""							).split()
      ]
      UpperCAmelCase          =	decimal_to_binary(_snake_case				,	_snake_case							)

      UpperCAmelCase          =	check(_snake_case							)
      print("""Prime Implicants are:"""							)
      print(_snake_case							)
      UpperCAmelCase          =	prime_implicant_chart(_snake_case				,	_snake_case							)

      UpperCAmelCase          =	selection(_snake_case				,	_snake_case							)
      print("""Essential Prime Implicants are:"""							)
      print(_snake_case							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()











"""simple docstring"""







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

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_UpperCamelCase					      =  logging.get_logger(__name__)

_UpperCamelCase					      =  """▁"""

_UpperCamelCase					      =  {"""vocab_file""": """sentencepiece.bpe.model""", """monolingual_vocab_file""": """dict.txt"""}

_UpperCamelCase					      =  {
    """vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/sentencepiece.bpe.model""",
    },
    """monolingual_vocab_file""": {
        """vinai/bartpho-syllable""": """https://huggingface.co/vinai/bartpho-syllable/resolve/main/dict.txt""",
    },
}

_UpperCamelCase					      =  {"""vinai/bartpho-syllable""": 1024}







class  lowerCamelCase__ (	snake_case			):
    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''']






    def __init__(			self     ,A     ,A     ,A="<s>"     ,A="</s>"     ,A="</s>"     ,A="<s>"     ,A="<unk>"     ,A="<pad>"     ,A="<mask>"     ,A = None     ,**A     ,):
          # Mask token behave like a normal word, i.e. include the space before it
          UpperCAmelCase          =	AddedToken(A     ,lstrip=A     ,rstrip=A ) if isinstance(A     ,A ) else mask_token

          UpperCAmelCase          =	{} if sp_model_kwargs is None else sp_model_kwargs

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

          UpperCAmelCase          =	vocab_file
          UpperCAmelCase          =	monolingual_vocab_file
          UpperCAmelCase          =	spm.SentencePieceProcessor(**self.sp_model_kwargs )
          self.sp_model.Load(str(A ) )

          # Load the reduced vocab

          # Keep order of special tokens for backward compatibility
          UpperCAmelCase          =	{}
          UpperCAmelCase          =	0
          for token in [bos_token, pad_token, eos_token, unk_token, sep_token, cls_token]:
                if str(A ) not in self.fairseq_tokens_to_ids:
                      UpperCAmelCase          =	cnt
                      cnt += 1
          with open(A     ,"""r"""     ,encoding="""utf-8""" ) as f:
                for line in f.readlines():
                      UpperCAmelCase          =	line.strip().split()[0]
                      UpperCAmelCase          =	len(self.fairseq_tokens_to_ids )
          if str(A ) not in self.fairseq_tokens_to_ids:
                UpperCAmelCase          =	len(self.fairseq_tokens_to_ids )

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






    def __getstate__(			self ):
          UpperCAmelCase          =	self.__dict__.copy()
          UpperCAmelCase          =	None
          UpperCAmelCase          =	self.sp_model.serialized_model_proto()
          return state






    def __setstate__(			self     ,A ):
          UpperCAmelCase          =	d

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

          UpperCAmelCase          =	spm.SentencePieceProcessor(**self.sp_model_kwargs )
          self.sp_model.LoadFromSerializedProto(self.sp_model_proto )






    def     _UpperCamelCase							(			self     ,A     ,A = None ):

          if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          UpperCAmelCase          =	[self.cls_token_id]
          UpperCAmelCase          =	[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep






    def     _UpperCamelCase							(			self     ,A     ,A = None     ,A = False ):

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

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






    def     _UpperCamelCase							(			self     ,A     ,A = None ):
          UpperCAmelCase          =	[self.sep_token_id]
          UpperCAmelCase          =	[self.cls_token_id]

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






    @property
    def     _UpperCamelCase							(			self ):
          return len(self.fairseq_ids_to_tokens )






    def     _UpperCamelCase							(			self ):
          UpperCAmelCase          =	{self.convert_ids_to_tokens(A ): i for i in range(self.vocab_size )}
          vocab.update(self.added_tokens_encoder )
          return vocab






    def     _UpperCamelCase							(			self     ,A ):
          return self.sp_model.encode(A     ,out_type=A )






    def     _UpperCamelCase							(			self     ,A ):
          if token in self.fairseq_tokens_to_ids:
                return self.fairseq_tokens_to_ids[token]
          else:
                return self.unk_token_id






    def     _UpperCamelCase							(			self     ,A ):
          return self.fairseq_ids_to_tokens[index]






    def     _UpperCamelCase							(			self     ,A ):
          UpperCAmelCase          =	"""""".join(A ).replace(A     ,""" """ ).strip()
          return out_string






    def     _UpperCamelCase							(			self     ,A     ,A = None ):
          if not os.path.isdir(A ):
                logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
                return
          UpperCAmelCase          =	os.path.join(
              A     ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""] )
          UpperCAmelCase          =	os.path.join(
              A     ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""monolingual_vocab_file"""]     ,)

          if os.path.abspath(self.vocab_file ) != os.path.abspath(A ) and os.path.isfile(self.vocab_file ):
                copyfile(self.vocab_file     ,A )
          elif not os.path.isfile(self.vocab_file ):
                with open(A     ,"""wb""" ) as fi:
                      UpperCAmelCase          =	self.sp_model.serialized_model_proto()
                      fi.write(A )

          if os.path.abspath(self.monolingual_vocab_file ) != os.path.abspath(
              A ) and os.path.isfile(self.monolingual_vocab_file ):
                copyfile(self.monolingual_vocab_file     ,A )
          elif not os.path.isfile(self.monolingual_vocab_file ):
                with open(A     ,"""w"""     ,encoding="""utf-8""" ) as fp:
                      for token in self.fairseq_tokens_to_ids:
                            if token not in self.all_special_tokens:
                                  fp.write(F'''{str(A )} \n''' )

          return out_vocab_file, out_monolingual_vocab_file



