



"""simple docstring"""




from __future__ import annotations

import random
from collections.abc import Iterable


class   a__		:


   def __init__(							self      :							Optional[Any],     lowerCAmelCase      :							list[str]			)    ->       None:
         lowercase  :      dict[str, bool | None]					=   {literal: None for literal in literals}


   def __str__(							self      :							Tuple			)    ->       str:
         return "{" + " , ".join(self.literals			) + "}"


   def __len__(							self      :							Union[str, Any]			)    ->       int:
         return len(self.literals			)


   def        lowercase				(							self      :							Optional[Any],     lowerCAmelCase      :							dict[str, bool | None]			)    ->       None:
         for literal in self.literals:
               lowercase  :      Any					=   literal[:2]
               if symbol in model:
                     lowercase  :      List[Any]					=   model[symbol]
               else:
                     continue
               if value is not None:
                     # Complement assignment if literal is in complemented form
                     if literal.endswith('\''			):
                           lowercase  :      str					=   not value
               lowercase  :      Tuple					=   value






   def        lowercase				(							self      :							Tuple,     lowerCAmelCase      :							dict[str, bool | None]			)    ->       bool | None:
         for literal in self.literals:
               lowercase  :      Tuple					=   literal.rstrip('\''			) if literal.endswith('\''			) else literal + '\''
               if symbol in self.literals:
                     return True

         self.assign(lowerCAmelCase			)
         for value in self.literals.values():
               if value in (True, None):
                     return value
         return any(self.literals.values()			)




class   a__		:


   def __init__(							self      :							Union[str, Any],     lowerCAmelCase      :							Iterable[Clause]			)    ->       None:
         lowercase  :      Dict					=   list(lowerCAmelCase			)






   def __str__(							self      :							Optional[Any]			)    ->       str:
         return "{" + " , ".join(str(lowerCAmelCase			) for clause in self.clauses			) + "}"




def   lowercase__     (			)     ->			Clause:






      '''simple docstring'''


      lowercase  :      str					=   []
      lowercase  :      List[Any]					=   random.randint(1	,      5				)
      lowercase  :      str					=   'A'
      lowercase  :      int					=   0
      while i < no_of_literals:
            lowercase  :      Dict					=   random.randint(1	,      5				)
            lowercase  :      List[Any]					=   base_var + str(_UpperCAmelCase				)
            lowercase  :      Optional[Any]					=   random.randint(0	,      1				)
            if var_complement == 1:
                  var_name += "'"
            if var_name in literals:
                  i -= 1
            else:
                  literals.append(_UpperCAmelCase				)
            i += 1
      return Clause(_UpperCAmelCase				)


def   lowercase__     (			)     ->			Formula:






      '''simple docstring'''


      lowercase  :      set[Clause]					=   set()
      lowercase  :      List[Any]					=   random.randint(1	,      10				)
      while len(_UpperCAmelCase				) < no_of_clauses:
            clauses.add(generate_clause()				)
      return Formula(_UpperCAmelCase				)


def   lowercase__     (			_UpperCAmelCase				)     ->			tuple[list[Clause], list[str]]:






      '''simple docstring'''


      lowercase  :      Dict					=   formula.clauses
      lowercase  :      Optional[int]					=   []
      for clause in formula.clauses:
            for literal in clause.literals:
                  lowercase  :      Optional[Any]					=   literal[:2]
                  if symbol not in symbols_set:
                        symbols_set.append(_UpperCAmelCase				)
      return clauses, symbols_set


def   lowercase__     (			_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)     ->			tuple[list[str], dict[str, bool | None]]:






      '''simple docstring'''


      lowercase  :      int					=   []
      lowercase  :      dict[str, bool | None]					=   {}
      lowercase  :      Union[str, Any]					=   []

      for clause in clauses:
            if clause.evaluate(_UpperCAmelCase				):
                  continue
            for literal in clause.literals:
                  literals.append(_UpperCAmelCase				)

      for s in symbols:
            lowercase  :      List[str]					=   s + '\''
            if (s in literals and sym not in literals) or (
                s not in literals and sym in literals
            ):
                  pure_symbols.append(_UpperCAmelCase				)
      for p in pure_symbols:
            lowercase  :      List[str]					=   None
      for s in pure_symbols:
            lowercase  :      List[Any]					=   s + '\''
            if s in literals:
                  lowercase  :      Any					=   True
            elif sym in literals:
                  lowercase  :      Optional[int]					=   False
      return pure_symbols, assignment


def   lowercase__     (			_UpperCAmelCase	,      _UpperCAmelCase				)     ->			tuple[list[str], dict[str, bool | None]]:






      '''simple docstring'''


      lowercase  :      Union[str, Any]					=   []
      for clause in clauses:
            if len(_UpperCAmelCase				) == 1:
                  unit_symbols.append(list(clause.literals.keys()				)[0]				)
            else:
                  lowercase	,    lowercase  :      str					=   0, 0
                  for literal, value in clause.literals.items():
                        if value is False:
                              f_count += 1
                        elif value is None:
                              lowercase  :      Tuple					=   literal
                              n_count += 1
                  if f_count == len(_UpperCAmelCase				) - 1 and n_count == 1:
                        unit_symbols.append(_UpperCAmelCase				)
      lowercase  :      dict[str, bool | None]					=   {}
      for i in unit_symbols:
            lowercase  :      List[str]					=   i[:2]
            lowercase  :      Union[str, Any]					=   len(_UpperCAmelCase				) == 2
      lowercase  :      Optional[Any]					=   [i[:2] for i in unit_symbols]

      return unit_symbols, assignment


def   lowercase__     (			_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)     ->			tuple[bool | None, dict[str, bool | None] | None]:






      '''simple docstring'''


      lowercase  :      List[str]					=   True
      for clause in clauses:
            lowercase  :      Union[str, Any]					=   clause.evaluate(_UpperCAmelCase				)
            if clause_check is False:
                  return False, None
            elif clause_check is None:
                  lowercase  :      Optional[Any]					=   False
                  continue

      if check_clause_all_true:
            return True, model

      try:
            lowercase	,    lowercase  :      List[Any]					=   find_pure_symbols(_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)
      except RecursionError:
            print('raises a RecursionError and is'				)
            return None, {}
      lowercase  :      Union[str, Any]					=   None
      if len(_UpperCAmelCase				) > 0:
            lowercase	,    lowercase  :      Dict					=   pure_symbols[0], assignment[pure_symbols[0]]

      if p:
            lowercase  :      List[Any]					=   model
            lowercase  :      Tuple					=   value
            lowercase  :      Dict					=   list(_UpperCAmelCase				)
            if p in tmp_symbols:
                  tmp_symbols.remove(_UpperCAmelCase				)
            return dpll_algorithm(_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)

      lowercase	,    lowercase  :      int					=   find_unit_clauses(_UpperCAmelCase	,      _UpperCAmelCase				)
      lowercase  :      List[Any]					=   None
      if len(_UpperCAmelCase				) > 0:
            lowercase	,    lowercase  :      Any					=   unit_symbols[0], assignment[unit_symbols[0]]
      if p:
            lowercase  :      Optional[int]					=   model
            lowercase  :      Tuple					=   value
            lowercase  :      Tuple					=   list(_UpperCAmelCase				)
            if p in tmp_symbols:
                  tmp_symbols.remove(_UpperCAmelCase				)
            return dpll_algorithm(_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)
      lowercase  :      Any					=   symbols[0]
      lowercase  :      List[Any]					=   symbols[1:]
      lowercase	,    lowercase  :      Tuple					=   model, model
      lowercase	,    lowercase  :      Any					=   True, False

      return dpll_algorithm(_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				) or dpll_algorithm(_UpperCAmelCase	,      _UpperCAmelCase	,      _UpperCAmelCase				)


if __name__ == "__main__":
     import doctest

     doctest.testmod()

     _UpperCamelCase:				int    							=  generate_formula()
     print(f'''The formula {formula} is''', end=' ')

     _UpperCamelCase							,					_UpperCamelCase:				int    							=  generate_parameters(formula)
     _UpperCamelCase							,					_UpperCamelCase:				List[str]    							=  dpll_algorithm(clauses, symbols, {})

     if solution:
          print(f'''satisfiable with the assignment {model}.''')
     else:
          print('not satisfiable.')





"""simple docstring"""




from arguments import TokenizerTrainingArguments
from datasets import load_dataset
from tqdm import tqdm

from transformers import AutoTokenizer, HfArgumentParser
from transformers.models.gpta.tokenization_gpta import bytes_to_unicode


def   lowercase__     (			_UpperCAmelCase=10				)     ->			Any:






      '''simple docstring'''


      for _ in tqdm(range(0	,      args.n_examples	,      _UpperCAmelCase				)				):
            yield [next(_UpperCAmelCase				)[args.text_column] for _ in range(_UpperCAmelCase				)]


# Configuration
_UpperCamelCase:				Union[str, Any]    							=  HfArgumentParser(TokenizerTrainingArguments)
_UpperCamelCase:				Dict    							=  parser.parse_args()

# Base tokenizer
_UpperCamelCase:				List[Any]    							=  AutoTokenizer.from_pretrained(args.base_tokenizer)
_UpperCamelCase:				int    							=  list(bytes_to_unicode().values())

# Load dataset
_UpperCamelCase:				Union[str, Any]    							=  load_dataset(args.dataset_name, split='train', streaming=True)
_UpperCamelCase:				Union[str, Any]    							=  iter(dataset)


# Training and saving
_UpperCamelCase:				Union[str, Any]    							=  tokenizer.train_new_from_iterator(
    batch_iterator(), vocab_size=args.vocab_size, initial_alphabet=base_vocab
)





new_tokenizer.save_pretrained(args.tokenizer_name, push_to_hub=args.push_to_hub)
