






'''simple docstring'''







from __future__ import annotations

import random
from collections.abc import Iterable






class        a__     :
     '''simple docstring'''







     def __init__(self     :						List[str]					,					lowercase__     :						list[str]       )	->							None:
           __A		 =   {literal: None for literal in literals}






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






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






     def      _UpperCamelCase (self     :						Any					,					lowercase__     :						dict[str, bool | None]       )	->							None:
           for literal in self.literals:
                 __A		 =   literal[:2]
                 if symbol in model:
                       __A		 =   model[symbol]
                 else:
                       continue
                 if value is not None:
                       # Complement assignment if literal is in complemented form
                       if literal.endswith("'"       ):
                             __A		 =   not value
                 __A		 =   value






     def      _UpperCamelCase (self     :						Optional[int]					,					lowercase__     :						dict[str, bool | None]       )	->							bool | None:
           for literal in self.literals:
                 __A		 =   literal.rstrip("'"       ) if literal.endswith("'"       ) else literal + "'"
                 if symbol in self.literals:
                       return True

           self.assign(lowercase__       )
           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     :						Any					,					lowercase__     :						Iterable[Clause]       )	->							None:
           __A		 =   list(lowercase__       )






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







def     _UpperCamelCase				(  ):
      __A		 =   []
      __A		 =   random.randint(1				,      5				)
      __A		 =   "A"
      __A		 =   0
      while i < no_of_literals:
            __A		 =   random.randint(1				,      5				)
            __A		 =   base_var + str(snake_case__				)
            __A		 =   random.randint(0				,      1				)
            if var_complement == 1:
                  var_name += "'"
            if var_name in literals:
                  i -= 1
            else:
                  literals.append(snake_case__				)
            i += 1
      return Clause(snake_case__				)


def     _UpperCamelCase				(  ):
      __A		 =   set()
      __A		 =   random.randint(1				,      10				)
      while len(snake_case__				) < no_of_clauses:
            clauses.add(generate_clause()				)
      return Formula(snake_case__				)


def     _UpperCamelCase				(  snake_case__				):
      __A		 =   formula.clauses
      __A		 =   []
      for clause in formula.clauses:
            for literal in clause.literals:
                  __A		 =   literal[:2]
                  if symbol not in symbols_set:
                        symbols_set.append(snake_case__				)
      return clauses, symbols_set


def     _UpperCamelCase				(  snake_case__				,      snake_case__				,      snake_case__				):
      __A		 =   []
      __A		 =   {}
      __A		 =   []

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

      for s in symbols:
            __A		 =   s + "'"
            if (s in literals and sym not in literals) or (
                s not in literals and sym in literals
            ):
                  pure_symbols.append(snake_case__				)
      for p in pure_symbols:
            __A		 =   None
      for s in pure_symbols:
            __A		 =   s + "'"
            if s in literals:
                  __A		 =   True
            elif sym in literals:
                  __A		 =   False
      return pure_symbols, assignment


def     _UpperCamelCase				(  snake_case__				,      snake_case__				):
      __A		 =   []
      for clause in clauses:
            if len(snake_case__				) == 1:
                  unit_symbols.append(list(clause.literals.keys()				)[0]				)
            else:
                  __A ,					__A		 =   0, 0
                  for literal, value in clause.literals.items():
                        if value is False:
                              f_count += 1
                        elif value is None:
                              __A		 =   literal
                              n_count += 1
                  if f_count == len(snake_case__				) - 1 and n_count == 1:
                        unit_symbols.append(snake_case__				)
      __A		 =   {}
      for i in unit_symbols:
            __A		 =   i[:2]
            __A		 =   len(snake_case__				) == 2
      __A		 =   [i[:2] for i in unit_symbols]

      return unit_symbols, assignment


def     _UpperCamelCase				(  snake_case__				,      snake_case__				,      snake_case__				):
      __A		 =   True
      for clause in clauses:
            __A		 =   clause.evaluate(snake_case__				)
            if clause_check is False:
                  return False, None
            elif clause_check is None:
                  __A		 =   False
                  continue

      if check_clause_all_true:
            return True, model

      try:
            __A ,					__A		 =   find_pure_symbols(snake_case__				,      snake_case__				,      snake_case__				)
      except RecursionError:
            print("raises a RecursionError and is"				)
            return None, {}
      __A		 =   None
      if len(snake_case__				) > 0:
            __A ,					__A		 =   pure_symbols[0], assignment[pure_symbols[0]]

      if p:
            __A		 =   model
            __A		 =   value
            __A		 =   list(snake_case__				)
            if p in tmp_symbols:
                  tmp_symbols.remove(snake_case__				)
            return dpll_algorithm(snake_case__				,      snake_case__				,      snake_case__				)

      __A ,					__A		 =   find_unit_clauses(snake_case__				,      snake_case__				)
      __A		 =   None
      if len(snake_case__				) > 0:
            __A ,					__A		 =   unit_symbols[0], assignment[unit_symbols[0]]
      if p:
            __A		 =   model
            __A		 =   value
            __A		 =   list(snake_case__				)
            if p in tmp_symbols:
                  tmp_symbols.remove(snake_case__				)
            return dpll_algorithm(snake_case__				,      snake_case__				,      snake_case__				)
      __A		 =   symbols[0]
      __A		 =   symbols[1:]
      __A ,					__A		 =   model, model
      __A ,					__A		 =   True, False

      return dpll_algorithm(snake_case__				,      snake_case__				,      snake_case__				) or dpll_algorithm(snake_case__				,      snake_case__				,      snake_case__				)


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       __A   :							Optional[Any]     	=						generate_formula()
       print(F"""The formula {formula} is""", end=' ')

       __A	,		__A   :							Optional[int]     	=						generate_parameters(formula)
       __A	,		__A   :							Any     	=						dpll_algorithm(clauses, symbols, {})

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










'''simple docstring'''







import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List

from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.info_utils import VerificationMode


def     _UpperCamelCase				(  snake_case__				,      **snake_case__				):
      return RunBeamCommand(
          args.dataset				,      args.name				,      args.cache_dir				,      args.beam_pipeline_options				,      args.data_dir				,      args.all_configs				,      args.save_info or args.save_infos				,      args.ignore_verifications				,      args.force_redownload				,      **snake_case__				,      )






class        a__     (      lowerCamelCase    ):
     '''simple docstring'''







     @staticmethod
     def      _UpperCamelCase (lowercase__     :						ArgumentParser       )	->							List[Any]:
           __A		 =   parser.add_parser("run_beam"					,					help="Run a Beam dataset processing pipeline"       )
           run_beam_parser.add_argument("dataset"					,					type=lowercase__					,					help="Name of the dataset to download"       )
           run_beam_parser.add_argument("--name"					,					type=lowercase__					,					default=lowercase__					,					help="Dataset config name"       )
           run_beam_parser.add_argument(
               "--cache_dir"					,					type=lowercase__					,					default=lowercase__					,					help="Cache directory where the datasets are stored"					,					)
           run_beam_parser.add_argument(
               "--beam_pipeline_options"					,					type=lowercase__					,					default=""					,					help="Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`"					,					)
           run_beam_parser.add_argument(
               "--data_dir"					,					type=lowercase__					,					default=lowercase__					,					help="Can be used to specify a manual directory to get the files from"					,					)
           run_beam_parser.add_argument("--all_configs"					,					action="store_true"					,					help="Test all dataset configurations"       )
           run_beam_parser.add_argument("--save_info"					,					action="store_true"					,					help="Save the dataset infos file"       )
           run_beam_parser.add_argument(
               "--ignore_verifications"					,					action="store_true"					,					help="Run the test without checksums and splits checks"       )
           run_beam_parser.add_argument("--force_redownload"					,					action="store_true"					,					help="Force dataset redownload"       )
           # aliases
           run_beam_parser.add_argument("--save_infos"					,					action="store_true"					,					help="alias for save_info"       )
           run_beam_parser.set_defaults(func=lowercase__       )






     def __init__(self     :						Any					,					lowercase__     :						str					,					lowercase__     :						str					,					lowercase__     :						str					,					lowercase__     :						str					,					lowercase__     :						str					,					lowercase__     :						bool					,					lowercase__     :						bool					,					lowercase__     :						bool					,					lowercase__     :						bool					,					**lowercase__     :						Tuple					,					)	->							List[Any]:
           __A		 =   dataset
           __A		 =   name
           __A		 =   cache_dir
           __A		 =   beam_pipeline_options
           __A		 =   data_dir
           __A		 =   all_configs
           __A		 =   save_infos
           __A		 =   ignore_verifications
           __A		 =   force_redownload
           __A		 =   config_kwargs






     def      _UpperCamelCase (self     :						int       )	->							Dict:
           import apache_beam as beam

           if self._name is not None and self._all_configs:
                 print("Both parameters `name` and `all_configs` can't be used at once."       )
                 exit(1       )
           __A ,					__A		 =   self._dataset, self._name
           __A		 =   dataset_module_factory(lowercase__       )
           __A		 =   import_main_class(dataset_module.module_path       )
           __A		 =   []
           if self._beam_pipeline_options:
                 __A		 =   beam.options.pipeline_options.PipelineOptions(
                     flags=[f"--{opt.strip()}" for opt in self._beam_pipeline_options.split(","       ) if opt]       )
           else:
                 __A		 =   None
           if self._all_configs and len(builder_cls.BUILDER_CONFIGS       ) > 0:
                 for builder_config in builder_cls.BUILDER_CONFIGS:
                       builders.append(
                           builder_cls(
                               config_name=builder_config.name					,					data_dir=self._data_dir					,					hash=dataset_module.hash					,					beam_options=lowercase__					,					cache_dir=self._cache_dir					,					base_path=dataset_module.builder_kwargs.get("base_path"       )					,					)       )
           else:
                 builders.append(
                     builder_cls(
                         config_name=lowercase__					,					data_dir=self._data_dir					,					beam_options=lowercase__					,					cache_dir=self._cache_dir					,					base_path=dataset_module.builder_kwargs.get("base_path"       )					,					**self._config_kwargs					,					)       )

           for builder in builders:
                 builder.download_and_prepare(
                     download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                     if not self._force_redownload
                     else DownloadMode.FORCE_REDOWNLOAD					,					download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH       )					,					verification_mode=VerificationMode.NO_CHECKS
                     if self._ignore_verifications
                     else VerificationMode.ALL_CHECKS					,					try_from_hf_gcs=lowercase__					,					)
                 if self._save_infos:
                       builder._save_infos()

           print("Apache beam run successful."       )

           # If save_infos=True, the dataset infos file is created next to the loaded module file.
           # Let's move it to the original directory of the dataset script, to allow the user to
           # upload them on S3 at the same time afterwards.
           if self._save_infos:
                 __A		 =   os.path.join(builder_cls.get_imported_module_dir()					,					config.DATASETDICT_INFOS_FILENAME       )

                 __A		 =   Path(lowercase__       ).name + ".py"

                 __A		 =   os.path.join(lowercase__					,					lowercase__       )
                 if os.path.isfile(lowercase__       ):
                       __A		 =   os.path.dirname(lowercase__       )
                 elif os.path.isfile(lowercase__       ):
                       __A		 =   path
                 else:  # in case of a remote dataset
                       print(f"Dataset Infos file saved at {dataset_infos_path}"       )
                       exit(1       )

                 # Move datasetinfo back to the user
                 __A		 =   os.path.join(lowercase__					,					config.DATASETDICT_INFOS_FILENAME       )
                 copyfile(lowercase__					,					lowercase__       )
                 print(f"Dataset Infos file saved at {user_dataset_infos_path}"       )


