






'''simple docstring'''


from __future__ import annotations

import random
from collections.abc import Iterable




class 							lowerCAmelCase					:







   """simple docstring"""







   def __init__( self   ,   _A			)    ->   None:
    __a    :	dict[str, bool | None]									=						{literal: None for literal in literals}



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



   def __len__( self			)    ->   int:
    return len(self.literals			)



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



   def    __magic_name__    ( self   ,   _A			)    ->   bool | None:
    for literal in self.literals:
     __a    :	Dict									=						literal.rstrip('\''			) if literal.endswith('\''			) else literal + '\''
     if symbol in self.literals:
      return True

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




class 							lowerCAmelCase					:







   """simple docstring"""







   def __init__( self   ,   _A			)    ->   None:
    __a    :	Any									=						list(_A			)



   def __str__( self			)    ->   str:
    return "{" + " , ".join(str(_A			) for clause in self.clauses			) + "}"






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






def   lowerCAmelCase__			(					):
 __a    :	set[Clause]									=						set()
 __a    :	Any									=						random.randint(1       ,		10		)
 while len(SCREAMING_SNAKE_CASE__		) < no_of_clauses:
  clauses.add(generate_clause()		)
 return Formula(SCREAMING_SNAKE_CASE__		)






def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__		):
 __a    :	Optional[int]									=						formula.clauses
 __a    :	int									=						[]
 for clause in formula.clauses:
  for literal in clause.literals:
   __a    :	Tuple									=						literal[:2]
   if symbol not in symbols_set:
    symbols_set.append(SCREAMING_SNAKE_CASE__		)
 return clauses, symbols_set






def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		):
 __a    :	Union[str, Any]									=						[]
 __a    :	dict[str, bool | None]									=						{}
 __a    :	Union[str, Any]									=						[]

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

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






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

 return unit_symbols, assignment






def   lowerCAmelCase__			(					SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		):
 __a    :	Dict									=						True
 for clause in clauses:
  __a    :	Union[str, Any]									=						clause.evaluate(SCREAMING_SNAKE_CASE__		)
  if clause_check is False:
   return False, None
  elif clause_check is None:
   __a    :	Tuple									=						False
   continue

 if check_clause_all_true:
  return True, model

 try:
  __a			,    __a    :	int									=						find_pure_symbols(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		)
 except RecursionError:
  print('raises a RecursionError and is'		)
  return None, {}
 __a    :	int									=						None
 if len(SCREAMING_SNAKE_CASE__		) > 0:
  __a			,    __a    :	List[Any]									=						pure_symbols[0], assignment[pure_symbols[0]]

 if p:
  __a    :	Union[str, Any]									=						model
  __a    :	Optional[Any]									=						value
  __a    :	Tuple									=						list(SCREAMING_SNAKE_CASE__		)
  if p in tmp_symbols:
   tmp_symbols.remove(SCREAMING_SNAKE_CASE__		)
  return dpll_algorithm(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		)

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

 return dpll_algorithm(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		) or dpll_algorithm(SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__       ,		SCREAMING_SNAKE_CASE__		)


if __name__ == "__main__":
  import doctest

  doctest.testmod()

  SCREAMING_SNAKE_CASE_				      =							generate_formula()
  print(F"The formula {formula} is", end=" ")

  SCREAMING_SNAKE_CASE_      ,				SCREAMING_SNAKE_CASE_				      =							generate_parameters(formula)
  SCREAMING_SNAKE_CASE_      ,				SCREAMING_SNAKE_CASE_				      =							dpll_algorithm(clauses, symbols, {})

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












'''simple docstring'''


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE_				      =							logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				      =							{
    "squeezebert/squeezebert-uncased": (
        "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/config.json"
    ),
    "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/config.json",
    "squeezebert/squeezebert-mnli-headless": (
        "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/config.json"
    ),
}




class 							lowerCAmelCase					(							lowerCamelCase__   ):







   """simple docstring"""







   _A						=   SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP
   _A						=   'squeezebert'



   def __init__( self   ,   _A=30522   ,   _A=768   ,   _A=12   ,   _A=12   ,   _A=3072   ,   _A="gelu"   ,   _A=0.1   ,   _A=0.1   ,   _A=512   ,   _A=2   ,   _A=0.02   ,   _A=1E-1_2   ,   _A=0   ,   _A=768   ,   _A=4   ,   _A=4   ,   _A=4   ,   _A=1   ,   _A=4   ,   _A=4   ,   **_A   ,   )    ->   List[Any]:
    super().__init__(pad_token_id=_A   ,   **_A			)

    __a    :	Optional[int]									=						vocab_size
    __a    :	Optional[int]									=						hidden_size
    __a    :	int									=						num_hidden_layers
    __a    :	int									=						num_attention_heads
    __a    :	Tuple									=						hidden_act
    __a    :	Optional[Any]									=						intermediate_size
    __a    :	Any									=						hidden_dropout_prob
    __a    :	List[Any]									=						attention_probs_dropout_prob
    __a    :	List[str]									=						max_position_embeddings
    __a    :	Tuple									=						type_vocab_size
    __a    :	Tuple									=						initializer_range
    __a    :	List[str]									=						layer_norm_eps
    __a    :	str									=						embedding_size
    __a    :	Any									=						q_groups
    __a    :	Any									=						k_groups
    __a    :	Union[str, Any]									=						v_groups
    __a    :	List[str]									=						post_attention_groups
    __a    :	Dict									=						intermediate_groups
    __a    :	Optional[Any]									=						output_groups




class 							lowerCAmelCase					(							lowerCamelCase__   ):







   """simple docstring"""







   @property
   def    __magic_name__    ( self			)    ->   Mapping[str, Mapping[int, str]]:
    if self.task == "multiple-choice":
     __a    :	Tuple									=						{0: 'batch', 1: 'choice', 2: 'sequence'}
    else:
     __a    :	List[Any]									=						{0: 'batch', 1: 'sequence'}
    return OrderedDict(
        [
            ('input_ids', dynamic_axis),
            ('attention_mask', dynamic_axis),
            ('token_type_ids', dynamic_axis),
        ]			)




