


'''simple docstring'''







import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator

import datasets.config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.filelock import logger as fl_logger
from datasets.utils.info_utils import VerificationMode
from datasets.utils.logging import ERROR, get_logger


A__:   List[Any]    =	get_logger(__name__)


def      SCREAMING_SNAKE_CASE_ (  _UpperCAmelCase     :     Tuple  )  ->      Dict:
       return TestCommand(
           args.dataset   ,args.name   ,args.cache_dir   ,args.data_dir   ,args.all_configs   ,args.save_info or args.save_infos   ,args.ignore_verifications   ,args.force_redownload   ,args.clear_cache   ,)







class A__	(						SCREAMING_SNAKE_CASE__				):
      __UpperCamelCase	:  Union[str, Any]     	=							False  # to tell pytest it's not a test class






      @staticmethod
      def __UpperCAmelCase	(			SCREAMING_SNAKE_CASE      :str     )	-> Any:




             '''simple docstring'''
             _a   :			Union[str, Any]					 =parser.add_parser("""test"""					,						help="""Test dataset implementation."""     )
             test_parser.add_argument("""--name"""					,						type=_UpperCAmelCase					,						default=_UpperCAmelCase					,						help="""Dataset processing name"""     )
             test_parser.add_argument(
                 """--cache_dir"""					,						type=_UpperCAmelCase					,						default=_UpperCAmelCase					,						help="""Cache directory where the datasets are stored."""					,						)
             test_parser.add_argument(
                 """--data_dir"""					,						type=_UpperCAmelCase					,						default=_UpperCAmelCase					,						help="""Can be used to specify a manual directory to get the files from."""					,						)
             test_parser.add_argument("""--all_configs"""					,						action="""store_true"""					,						help="""Test all dataset configurations"""     )
             test_parser.add_argument(
                 """--save_info"""					,						action="""store_true"""					,						help="""Save the dataset infos in the dataset card (README.md)"""     )
             test_parser.add_argument(
                 """--ignore_verifications"""					,						action="""store_true"""					,						help="""Run the test without checksums and splits checks."""					,						)
             test_parser.add_argument("""--force_redownload"""					,						action="""store_true"""					,						help="""Force dataset redownload"""     )
             test_parser.add_argument(
                 """--clear_cache"""					,						action="""store_true"""					,						help="""Remove downloaded files and cached datasets after each config test"""					,						)
             # aliases
             test_parser.add_argument("""--save_infos"""					,						action="""store_true"""					,						help="""alias to save_info"""     )
             test_parser.add_argument("""dataset"""					,						type=_UpperCAmelCase					,						help="""Name of the dataset to download"""     )
             test_parser.set_defaults(func=_test_command_factory     )






      def __init__(			self      :int					,						SCREAMING_SNAKE_CASE      :Optional[Any]					,						SCREAMING_SNAKE_CASE      :List[Any]					,						SCREAMING_SNAKE_CASE      :str					,						SCREAMING_SNAKE_CASE      :List[str]					,						SCREAMING_SNAKE_CASE      :Optional[int]					,						SCREAMING_SNAKE_CASE      :Any					,						SCREAMING_SNAKE_CASE      :int					,						SCREAMING_SNAKE_CASE      :Optional[Any]					,						SCREAMING_SNAKE_CASE      :Optional[Any]					,						)	-> int:




             '''simple docstring'''
             _a   :			int					 =dataset
             _a   :			str					 =name
             _a   :			Union[str, Any]					 =cache_dir
             _a   :			Optional[int]					 =data_dir
             _a   :			Any					 =all_configs
             _a   :			Union[str, Any]					 =save_infos
             _a   :			Any					 =ignore_verifications
             _a   :			Tuple					 =force_redownload
             _a   :			Any					 =clear_cache
             if clear_cache and not cache_dir:
                    print(
                        """When --clear_cache is used, specifying a cache directory is mandatory.\n"""
                        """The 'download' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n"""
                        """Please provide a --cache_dir that will be used to test the dataset script."""     )
                    exit(1     )
             if save_infos:
                    _a   :			str					 =True






      def __UpperCAmelCase	(			self      :List[str]     )	-> Any:




             '''simple docstring'''
             fl_logger().setLevel(_UpperCAmelCase     )
             if self._name is not None and self._all_configs:
                    print("""Both parameters `config` and `all_configs` can't be used at once."""     )
                    exit(1     )
             _a   :			List[str]					 =self._dataset, self._name
             _a   :			List[str]					 =dataset_module_factory(_UpperCAmelCase     )
             _a   :			Optional[Any]					 =import_main_class(module.module_path     )
             _a   :			Dict					 =len(builder_cls.BUILDER_CONFIGS     ) if self._all_configs and builder_cls.BUILDER_CONFIGS else 1

             def get_builders() -> Generator[DatasetBuilder, None, None]:
                    if self._all_configs and builder_cls.BUILDER_CONFIGS:
                           for i, config in enumerate(builder_cls.BUILDER_CONFIGS     ):
                                  if "config_name" in module.builder_kwargs:
                                         yield builder_cls(
                                             cache_dir=self._cache_dir					,						data_dir=self._data_dir					,						**module.builder_kwargs					,						)
                                  else:
                                         yield builder_cls(
                                             config_name=config.name					,						cache_dir=self._cache_dir					,						data_dir=self._data_dir					,						**module.builder_kwargs					,						)
                    else:
                           if "config_name" in module.builder_kwargs:
                                  yield builder_cls(cache_dir=self._cache_dir					,						data_dir=self._data_dir					,						**module.builder_kwargs     )
                           else:
                                  yield builder_cls(
                                      config_name=_UpperCAmelCase					,						cache_dir=self._cache_dir					,						data_dir=self._data_dir					,						**module.builder_kwargs					,						)

             for j, builder in enumerate(get_builders()     ):
                    print(f"Testing builder '{builder.config.name}' ({j + 1}/{n_builders})"     )
                    _a   :			Union[str, Any]					 =os.path.exists(
                        os.path.join(builder.get_imported_module_dir()					,						datasets.config.DATASETDICT_INFOS_FILENAME     )     )  # record checksums only if we need to update a (deprecated) dataset_infos.json
                    builder.download_and_prepare(
                        download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                        if not self._force_redownload
                        else DownloadMode.FORCE_REDOWNLOAD					,						verification_mode=VerificationMode.NO_CHECKS
                        if self._ignore_verifications
                        else VerificationMode.ALL_CHECKS					,						try_from_hf_gcs=_UpperCAmelCase					,						)
                    builder.as_dataset()
                    if self._save_infos:
                           builder._save_infos()

                    # If save_infos=True, the dataset card (README.md) is created next to the loaded module file.
                    # The dataset_infos are saved in the YAML part of the README.md

                    # 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   :			Any					 =os.path.join(builder_cls.get_imported_module_dir()					,						"""README.md"""     )
                           _a   :			Tuple					 =Path(_UpperCAmelCase     ).name + ".py"
                           _a   :			List[Any]					 =os.path.join(_UpperCAmelCase					,						_UpperCAmelCase     )
                           if os.path.isfile(_UpperCAmelCase     ):
                                  _a   :			int					 =os.path.dirname(_UpperCAmelCase     )
                           elif os.path.isfile(_UpperCAmelCase     ):
                                  _a   :			int					 =path
                           elif os.path.isdir(_UpperCAmelCase     ):  # for local directories containing only data files
                                  _a   :			Optional[Any]					 =path
                           else:  # in case of a remote dataset
                                  _a   :			Optional[Any]					 =None
                                  print(f"Dataset card saved at {dataset_readme_path}"     )

                           # Move dataset_info back to the user
                           if dataset_dir is not None:
                                  _a   :			int					 =os.path.join(_UpperCAmelCase					,						"""README.md"""     )
                                  copyfile(_UpperCAmelCase					,						_UpperCAmelCase     )
                                  print(f"Dataset card saved at {user_dataset_readme_path}"     )

            # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
                    if self._clear_cache:
                           if os.path.isdir(builder._cache_dir     ):
                                  logger.warning(f"Clearing cache at {builder._cache_dir}"     )
                                  rmtree(builder._cache_dir     )
                           _a   :			Dict					 =os.path.join(self._cache_dir					,						datasets.config.DOWNLOADED_DATASETS_DIR     )
                           if os.path.isdir(_UpperCAmelCase     ):
                                  logger.warning(f"Clearing cache at {download_dir}"     )
                                  rmtree(_UpperCAmelCase     )

             print("""Test successful."""     )










'''simple docstring'''







import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment







class A__	(						unittest.TestCase				):






      def __UpperCAmelCase	(			self      :List[Any]     )	-> List[str]:




             '''simple docstring'''
             _a   :			Union[str, Any]					 =inspect.getfile(accelerate.test_utils     )
             _a   :			Any					 =os.path.sep.join(mod_file.split(os.path.sep     )[:-1] + ["""scripts""", """test_sync.py"""]     )






      @require_cpu
      def __UpperCAmelCase	(			self      :List[str]     )	-> Optional[Any]:




             '''simple docstring'''
             debug_launcher(test_sync.main					,						num_processes=1     )






      @require_cpu
      def __UpperCAmelCase	(			self      :int     )	-> Union[str, Any]:




             '''simple docstring'''
             debug_launcher(test_sync.main     )






      @require_single_gpu
      def __UpperCAmelCase	(			self      :Any     )	-> Optional[int]:




             '''simple docstring'''
             test_sync.main()






      @require_multi_gpu
      def __UpperCAmelCase	(			self      :Optional[Any]     )	-> int:




             '''simple docstring'''
             print(f"Found {torch.cuda.device_count()} devices."     )
             _a   :			int					 =["""torchrun""", f"--nproc_per_node={torch.cuda.device_count()}", self.test_file_path]
             with patch_environment(omp_num_threads=1     ):
                    execute_subprocess_async(SCREAMING_SNAKE_CASE					,						env=os.environ.copy()     )


