




from __future__ import annotations

from collections.abc import Sequence
from typing import Literal



def 						lowerCAmelCase		(		_lowerCAmelCase							:   str						,							_lowerCAmelCase							:   str	):




 """simple docstring"""







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



def 						lowerCAmelCase		(		_lowerCAmelCase							:   list[str]	):




 """simple docstring"""







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



def 						lowerCAmelCase		(		_lowerCAmelCase							:   int						,							_lowerCAmelCase							:   Sequence[float]	):




 """simple docstring"""







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



def 						lowerCAmelCase		(		_lowerCAmelCase							:   str						,							_lowerCAmelCase							:   str						,							_lowerCAmelCase							:   int	):




 """simple docstring"""







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



def 						lowerCAmelCase		(		_lowerCAmelCase							:   list[list[int]]						,							_lowerCAmelCase							:   list[str]	):




 """simple docstring"""







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



def 						lowerCAmelCase		(		_lowerCAmelCase							:   list[str]						,							_lowerCAmelCase							:   list[str]	):




 """simple docstring"""







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

 return chart



def 						lowerCAmelCase		(		):




 """simple docstring"""







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

 UpperCAmelCase__							 =						check(_lowerCAmelCase	)
 print("Prime Implicants are:"	)
 print(_lowerCAmelCase	)
 UpperCAmelCase__							 =						prime_implicant_chart(_lowerCAmelCase						,							_lowerCAmelCase	)

 UpperCAmelCase__							 =						selection(_lowerCAmelCase						,							_lowerCAmelCase	)
 print("Essential Prime Implicants are:"	)
 print(_lowerCAmelCase	)


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()











import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
  from transformers.pipelines.conversational import Conversation


_lowerCAmelCase						:   str		=   logging.get_logger(__name__)

_lowerCAmelCase						:   List[Any]		=   {"tokenizer_file": "tokenizer.json"}

_lowerCAmelCase						:   Tuple		=   {
    "tokenizer_file": {
        "bigscience/tokenizer": "https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json",
        "bigscience/bloom-560m": "https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json",
        "bigscience/bloom-1b1": "https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json",
        "bigscience/bloom-1b7": "https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json",
        "bigscience/bloom-3b": "https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json",
        "bigscience/bloom-7b1": "https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json",
        "bigscience/bloom": "https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json",
    },
}
class 			_UpperCamelCase      (				lowerCAmelCase		):
      UpperCAmelCase_        =		VOCAB_FILES_NAMES
      UpperCAmelCase_        =		PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase_        =		["""input_ids""", """attention_mask"""]
      UpperCAmelCase_        =		None
      def __init__(			self   :List[Any] ,      lowerCamelCase   :Union[str, Any]=None ,      lowerCamelCase   :Optional[Any]=None ,      lowerCamelCase   :List[Any]=None ,      lowerCamelCase   :Union[str, Any]="<unk>" ,      lowerCamelCase   :Union[str, Any]="<s>" ,      lowerCamelCase   :Union[str, Any]="</s>" ,      lowerCamelCase   :str="<pad>" ,      lowerCamelCase   :Any=False ,      lowerCamelCase   :Optional[Any]=False ,      **lowerCamelCase   :Optional[Any] ,      )     ->			Any:
       super().__init__(
           lowerCamelCase ,      lowerCamelCase ,      tokenizer_file=lowerCamelCase ,      unk_token=lowerCamelCase ,      bos_token=lowerCamelCase ,      eos_token=lowerCamelCase ,      pad_token=lowerCamelCase ,      add_prefix_space=lowerCamelCase ,      clean_up_tokenization_spaces=lowerCamelCase ,      **lowerCamelCase ,      )
       UpperCAmelCase__							 =						json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()      )
       if pre_tok_state.get("add_prefix_space" ,      lowerCamelCase      ) != add_prefix_space:
        UpperCAmelCase__							 =						getattr(lowerCamelCase ,      pre_tok_state.pop("type"      )      )
        UpperCAmelCase__							 =						add_prefix_space
        UpperCAmelCase__							 =						pre_tok_class(**lowerCamelCase      )

       UpperCAmelCase__							 =						add_prefix_space
      def 	UpperCAmelCase_						(			self   :int ,      *lowerCamelCase   :Any ,      **lowerCamelCase   :int      )     ->			BatchEncoding:
       UpperCAmelCase__							 =						kwargs.get("is_split_into_words" ,      lowerCamelCase      )
       if not (self.add_prefix_space or not is_split_into_words):
        raise Exception(
            f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'''
            " pretokenized inputs."      )

       return super()._batch_encode_plus(*lowerCamelCase ,      **lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Any ,      *lowerCamelCase   :List[Any] ,      **lowerCamelCase   :Union[str, Any]      )     ->			BatchEncoding:
       UpperCAmelCase__							 =						kwargs.get("is_split_into_words" ,      lowerCamelCase      )

       if not (self.add_prefix_space or not is_split_into_words):
        raise Exception(
            f'''You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with'''
            " pretokenized inputs."      )

       return super()._encode_plus(*lowerCamelCase ,      **lowerCamelCase      )
      def 	UpperCAmelCase_						(			self   :Tuple ,      lowerCamelCase   :str ,      lowerCamelCase   :Optional[str] = None      )     ->			Tuple[str]:
       UpperCAmelCase__							 =						self._tokenizer.model.save(lowerCamelCase ,      name=lowerCamelCase      )
       return tuple(lowerCamelCase      )







      def 	UpperCAmelCase_						(			self   :List[str] ,      lowerCamelCase   :"Conversation"      )     ->			List[int]:
       UpperCAmelCase__							 =						[]
       for is_user, text in conversation.iter_texts():
        input_ids.extend(self.encode(lowerCamelCase ,      add_special_tokens=lowerCamelCase      ) + [self.eos_token_id]      )

       if len(lowerCamelCase      ) > self.model_max_length:
        UpperCAmelCase__							 =						input_ids[-self.model_max_length :]
       return input_ids





