code: 
  
  
  import argparse
  import logging
  import math
  import time
  
  import torch
  
  from transformers import TransfoXLCorpus, TransfoXLLMHeadModel
  
  
  logging.basicConfig(
      format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
  )
  _SCREAMING_SNAKE_CASE    :				Tuple       =					logging.getLogger(__name__)
  def     UpperCAmelCase__		():
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       argparse.ArgumentParser(description='''PyTorch Transformer Language Model'''       )
       parser.add_argument('''--model_name'''							,type=UpperCamelCase_							,default='''transfo-xl-wt103'''							,help='''pretrained model name'''       )
       parser.add_argument(
           '''--split'''							,type=UpperCamelCase_							,default='''test'''							,choices=['''all''', '''valid''', '''test''']							,help='''which split to evaluate'''       )
       parser.add_argument('''--batch_size'''							,type=UpperCamelCase_							,default=10							,help='''batch size'''       )
       parser.add_argument('''--tgt_len'''							,type=UpperCamelCase_							,default=1_28							,help='''number of tokens to predict'''       )
       parser.add_argument('''--ext_len'''							,type=UpperCamelCase_							,default=0							,help='''length of the extended context'''       )
       parser.add_argument('''--mem_len'''							,type=UpperCamelCase_							,default=16_00							,help='''length of the retained previous heads'''       )
       parser.add_argument('''--clamp_len'''							,type=UpperCamelCase_							,default=10_00							,help='''max positional embedding index'''       )
       parser.add_argument('''--no_cuda'''							,action='''store_true'''							,help='''Do not use CUDA even though CUA is available'''       )
       parser.add_argument('''--work_dir'''							,type=UpperCamelCase_							,required=UpperCamelCase_							,help='''path to the work_dir'''       )
       parser.add_argument('''--no_log'''							,action='''store_true'''							,help='''do not log the eval result'''       )
       parser.add_argument('''--same_length'''							,action='''store_true'''							,help='''set same length attention with masking'''       )
       parser.add_argument('''--server_ip'''							,type=UpperCamelCase_							,default=''''''							,help='''Can be used for distant debugging.'''       )
       parser.add_argument('''--server_port'''							,type=UpperCamelCase_							,default=''''''							,help='''Can be used for distant debugging.'''       )
       snake_case					=       parser.parse_args()
       assert args.ext_len >= 0, "extended context length must be non-negative"
  
       if args.server_ip and args.server_port:
            # Distant debugging - see https://code.visualstudio.com/docs/python/debugging#_attach-to-a-local-script
            import ptvsd
  
            print('''Waiting for debugger attach'''       )
            ptvsd.enable_attach(address=(args.server_ip, args.server_port)							,redirect_output=UpperCamelCase_       )
            ptvsd.wait_for_attach()
  
       snake_case					=       torch.device('''cuda''' if torch.cuda.is_available() and not args.no_cuda else '''cpu'''       )
       logger.info('''device: {}'''.format(UpperCamelCase_       )       )
  
       # Load a pre-processed dataset
       # You can also build the corpus yourself using TransfoXLCorpus methods
       # The pre-processing involve computing word frequencies to prepare the Adaptive input and SoftMax
       # and tokenizing the dataset
       # The pre-processed corpus is a convertion (using the conversion script )
       snake_case					=       TransfoXLCorpus.from_pretrained(args.model_name       )
  
       snake_case					=       corpus.get_iterator('''valid'''							,args.batch_size							,args.tgt_len							,device=UpperCamelCase_							,ext_len=args.ext_len       )
       snake_case					=       corpus.get_iterator('''test'''							,args.batch_size							,args.tgt_len							,device=UpperCamelCase_							,ext_len=args.ext_len       )
  
       # Load a pre-trained model
       snake_case					=       TransfoXLLMHeadModel.from_pretrained(args.model_name       )
       model.to(UpperCamelCase_       )
  
       logger.info(
           '''Evaluating with bsz {} tgt_len {} ext_len {} mem_len {} clamp_len {}'''.format(
               args.batch_size							,args.tgt_len							,args.ext_len							,args.mem_len							,args.clamp_len       )       )
  
       model.reset_memory_length(args.mem_len       )
       if args.clamp_len > 0:
            snake_case					=       args.clamp_len
       if args.same_length:
            snake_case					=       True
  
       ###############################################################################
       # Evaluation code
       ###############################################################################
       def evaluate(UpperCamelCase_       ):
            # Turn on evaluation mode which disables dropout.
            model.eval()
            snake_case				,						snake_case					=       0, 0.0
            snake_case					=       time.time()
            with torch.no_grad():
                 snake_case					=       None
                 for idx, (data, target, seq_len) in enumerate(UpperCamelCase_       ):
                      snake_case					=       model(UpperCamelCase_							,lm_labels=UpperCamelCase_							,mems=UpperCamelCase_       )
                      snake_case				,						snake_case				,						snake_case					=       ret
                      snake_case					=       loss.mean()
                      total_loss += seq_len * loss.item()
                      total_len += seq_len
                 snake_case					=       time.time() - start_time
            logger.info('''Time : {:.2f}s, {:.2f}ms/segment'''.format(UpperCamelCase_							,10_00 * total_time / (idx + 1)       )       )
            return total_loss / total_len
  
       # Run on test data.
       if args.split == "all":
            snake_case					=       evaluate(UpperCamelCase_       )
            snake_case					=       evaluate(UpperCamelCase_       )
       elif args.split == "valid":
            snake_case					=       evaluate(UpperCamelCase_       )
            snake_case					=       None
       elif args.split == "test":
            snake_case					=       evaluate(UpperCamelCase_       )
            snake_case					=       None
  
       def format_log(UpperCamelCase_							,UpperCamelCase_       ):
            snake_case					=       '''| {0} loss {1:5.2f} | {0} ppl {2:9.3f} '''.format(UpperCamelCase_							,UpperCamelCase_							,math.exp(UpperCamelCase_       )       )
            return log_str
  
       snake_case					=       ''''''
       if valid_loss is not None:
            log_str += format_log(UpperCamelCase_							,'''valid'''       )
       if test_loss is not None:
            log_str += format_log(UpperCamelCase_							,'''test'''       )
  
       logger.info('''=''' * 1_00       )
       logger.info(UpperCamelCase_       )
       logger.info('''=''' * 1_00       )
  
  
  if __name__ == "__main__":
   main()
  
  
  
  
  
style_context: 
  
  
  from __future__ import annotations
  
  import random
  from collections.abc import Iterable
  
  class 						A__      :
  
  
  
  
  
  
  
      """simple docstring"""
  
      def __init__( self    ,      __snake_case					):
           snake_case					=       {literal: None for literal in literals}
      def __str__( self					):
           return "{" + " , ".join(self.literals					) + "}"
      def __len__( self					):
           return len(self.literals					)
      def 	a_    ( self    ,      __snake_case					):
           for literal in self.literals:
                snake_case					=       literal[:2]
                if symbol in model:
                     snake_case					=       model[symbol]
                else:
                     continue
                if value is not None:
                     # Complement assignment if literal is in complemented form
                     if literal.endswith('''\''''					):
                          snake_case					=       not value
                snake_case					=       value
  
  
  
  
      def 	a_    ( self    ,      __snake_case					):
           for literal in self.literals:
                snake_case					=       literal.rstrip('''\''''					) if literal.endswith('''\''''					) else literal + '''\''''
                if symbol in self.literals:
                     return True
  
           self.assign(__snake_case					)
           for value in self.literals.values():
                if value in (True, None):
                     return value
           return any(self.literals.values()					)
  
  
  
  
  
  
  class 						A__      :
  
  
  
  
  
  
  
      """simple docstring"""
  
      def __init__( self    ,      __snake_case					):
           snake_case					=       list(__snake_case					)
  
  
  
  
      def __str__( self					):
           return "{" + " , ".join(str(__snake_case					) for clause in self.clauses					) + "}"
  
  
  
  
  
  
  def     UpperCAmelCase__		():
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       []
       snake_case					=       random.randint(1							,5       )
       snake_case					=       '''A'''
       snake_case					=       0
       while i < no_of_literals:
            snake_case					=       random.randint(1							,5       )
            snake_case					=       base_var + str(UpperCamelCase_       )
            snake_case					=       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     UpperCAmelCase__		():
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       set()
       snake_case					=       random.randint(1							,10       )
       while len(UpperCamelCase_       ) < no_of_clauses:
            clauses.add(generate_clause()       )
       return Formula(UpperCamelCase_       )
  def     UpperCAmelCase__		(UpperCamelCase_       ):
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       formula.clauses
       snake_case					=       []
       for clause in formula.clauses:
            for literal in clause.literals:
                 snake_case					=       literal[:2]
                 if symbol not in symbols_set:
                      symbols_set.append(UpperCamelCase_       )
       return clauses, symbols_set
  def     UpperCAmelCase__		(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       ):
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       []
       snake_case					=       {}
       snake_case					=       []
  
       for clause in clauses:
            if clause.evaluate(UpperCamelCase_       ):
                 continue
            for literal in clause.literals:
                 literals.append(UpperCamelCase_       )
  
       for s in symbols:
            snake_case					=       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:
            snake_case					=       None
       for s in pure_symbols:
            snake_case					=       s + '''\''''
            if s in literals:
                 snake_case					=       True
            elif sym in literals:
                 snake_case					=       False
       return pure_symbols, assignment
  def     UpperCAmelCase__		(UpperCamelCase_							,UpperCamelCase_       ):
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       []
       for clause in clauses:
            if len(UpperCamelCase_       ) == 1:
                 unit_symbols.append(list(clause.literals.keys()       )[0]       )
            else:
                 snake_case				,						snake_case					=       0, 0
                 for literal, value in clause.literals.items():
                      if value is False:
                           f_count += 1
                      elif value is None:
                           snake_case					=       literal
                           n_count += 1
                 if f_count == len(UpperCamelCase_       ) - 1 and n_count == 1:
                      unit_symbols.append(UpperCamelCase_       )
       snake_case					=       {}
       for i in unit_symbols:
            snake_case					=       i[:2]
            snake_case					=       len(UpperCamelCase_       ) == 2
       snake_case					=       [i[:2] for i in unit_symbols]
  
       return unit_symbols, assignment
  def     UpperCAmelCase__		(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       ):
  
  
  
       """simple docstring"""
  
  
  
  
  
  
       snake_case					=       True
       for clause in clauses:
            snake_case					=       clause.evaluate(UpperCamelCase_       )
            if clause_check is False:
                 return False, None
            elif clause_check is None:
                 snake_case					=       False
                 continue
  
       if check_clause_all_true:
            return True, model
  
       try:
            snake_case				,						snake_case					=       find_pure_symbols(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       )
       except RecursionError:
            print('''raises a RecursionError and is'''       )
            return None, {}
       snake_case					=       None
       if len(UpperCamelCase_       ) > 0:
            snake_case				,						snake_case					=       pure_symbols[0], assignment[pure_symbols[0]]
  
       if p:
            snake_case					=       model
            snake_case					=       value
            snake_case					=       list(UpperCamelCase_       )
            if p in tmp_symbols:
                 tmp_symbols.remove(UpperCamelCase_       )
            return dpll_algorithm(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       )
  
       snake_case				,						snake_case					=       find_unit_clauses(UpperCamelCase_							,UpperCamelCase_       )
       snake_case					=       None
       if len(UpperCamelCase_       ) > 0:
            snake_case				,						snake_case					=       unit_symbols[0], assignment[unit_symbols[0]]
       if p:
            snake_case					=       model
            snake_case					=       value
            snake_case					=       list(UpperCamelCase_       )
            if p in tmp_symbols:
                 tmp_symbols.remove(UpperCamelCase_       )
            return dpll_algorithm(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       )
       snake_case					=       symbols[0]
       snake_case					=       symbols[1:]
       snake_case				,						snake_case					=       model, model
       snake_case				,						snake_case					=       True, False
  
       return dpll_algorithm(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       ) or dpll_algorithm(UpperCamelCase_							,UpperCamelCase_							,UpperCamelCase_       )
  
  
  if __name__ == "__main__":
   import doctest
  
   doctest.testmod()
  
   _SCREAMING_SNAKE_CASE    :				Dict       =					generate_formula()
   print(f'''The formula {formula} is''', end=" ")
  
   _SCREAMING_SNAKE_CASE   ,     _SCREAMING_SNAKE_CASE    :				Any       =					generate_parameters(formula)
   _SCREAMING_SNAKE_CASE   ,     _SCREAMING_SNAKE_CASE    :				Optional[Any]       =					dpll_algorithm(clauses, symbols, {})
  
   if solution:
    print(f'''satisfiable with the assignment {model}.''')
   else:
    print("not satisfiable.")
  
  
  
  
  